determinants of career decision-making...

DETERMINANTS OF CAREER DECISION-MAKING AMONG

HIGHER SECONDARY LEVEL STUDENTS OF KARACHI

BY

IKRAM SHAH

DEPARTMENT OF SOCIOLOGY

FACULTY OF SOCIAL SCIENCES

UNIVERSITY OF KARACHI, KARACHI

PAKISTAN

2015

DETERMINANTS OF CAREER DECISION-MAKING AMONG

HIGHER SECONDARY LEVEL STUDENTS OF KARACHI

BY

IKRAM SHAH

A THSIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENT

FOR THE DEGREE OF

DOCTOR IN PHILOSOPHY

IN

SOCIOLOGY

DEPARTMENT OF SOCIOLOGY

FACULTY OF SOCIAL SCIENCES

UNIVERSITY OF KARACHI, KARACHI

PAKISTAN

2015

III

Certificate

This to certify that I have examined the above PhD thesis and have found that it is

complete and satisfactory in all respect. The views expressed in it are those of the

researcher. He has completed the thesis as a requirement of the PhD in Sociology.

Professor Dr. Rana Saba Sultan

To

My Family

Specially My Brother and Sisters

For Their Unconditional Support

ACKNOWLEDGMENT

There is a lot of people whom I would like to pay thanks for various reasons because

without their support it would be not possible to complete this uphill task. First of all

I bow my head before Almighty Allah thanks giving for the completion of my doctoral

research work.

The lion’s share of my heartfelt gratitude I owe to my mentor and research supervisor

Prof. Dr. Rana Saba Sultan (Ex-Chairperson of Department of Sociology University

of Karachi). It has been an honour to be her Ph.D. student. She has been supportive

since the days I begun working. I would like to express my appreciations and thanks

for her advice, ideas, moral support and patience in guiding me throughout the thesis.

I deeply indebted to Mr. Amjad Javaed (Assistant Professor Department of Sociology

University of Karachi), for his fundamental role in my doctoral work. Who has

provided insightful discussions about research and the primary source of probing and

developing the initial idea for the thesis. You have been very supportive and helped

me to think clearly, when I have found it difficult to do so. I owe a great debt of

gratitude to Prof. Dr. Arab Naz (Ex-Chairman Department of Sociology and Social

Work University of Malakand), who has provided me with every bit of guidance and

expertise that I needed. He was always there, to proofread and mark up my thesis

chapters and gave his valuable feedback on my thesis. I also acknowledge and thank

Prof. Dr. Farah Iqbal (Professor Psychology Department, University of Karachi), who

has taught me different ways to approach data analysis and to employ required

statistical tests to draw a logical conclusion. I would also like to thank my teachers at

Department of Sociology University of Karachi for their continuous support and

encouragement. I am also thankful to Mr. Naseerullah Khan for his help in proof

reading of this dissertation.

I extended my sincere gratitude to friend and class fellow Mr. Hosh Muhammad

Junejo (Lecturer National College for Science and Commerce Karachi) for his time

and patience when we were spending most of our time in the basement of campus

library. I am also thankful to Ms. Huma and Ms. Naveeda Erum (Lecturer Department

of Sociology, University of Baluchistan), they taught me implication of different

statistical tests during the course work. I am thankful to Ms. Nori Marai Samuel (Ph.D.

Student Department of Microbiology, University of Karachi) for her time, patience

and support in data analysis on SPSS. I also appreciate and acknowledge the support

of Mrs. Aisha Zia the founder of a non-profit organization, where I spent the last three

years of my doctoral study. People like her, are genuinely nice and want to help you

out, I am glade to work with her for the last three years.

I am extended my thanks to Prof. Shahnaz (Principal For Women College Karachi)

and Prof. Mrs. Najma Tayyab (Principal Sir Syed College for Girls), Prof. Naseem

Hayder (Principal of Adamjee College), Mr. Alexander D’Souza (Principal of Saint

Patrick College) and all those college administrators who had directly or indirectly

facilitated me in data collection process.

I would like to express my appreciation to Dr. Nabi Shah (Post-doctoral Research

Assistant, Pat McPherson Centre for Pharmacogenomics and Pharmacogenetic

Dundee Scotland) for all his help, advice and encouragement and giving me the

necessary pep-talks whenever I started doubting myself. I acknowledge the efforts of

Mr. Ahmed Kamal for making arrangement and permission for data collection, from

day first, he has been involved in data collection process till its completion.

My heartfelt thanks to Mr. Allah Dad Khan and my aunty, for their devotion,

unconditional love and support during my stay in Karachi. Without their support this

doctoral work would never have been completed. I would like to thank my cousins

Mr. Azizullah Shah, Mr. Shahid Kamal, and the rest of my family elders and relatives

whose prayers and good wishes were always with me.

Last but not least, I thank my family: my hardworking brother Mr. Inam Shah, who

has scarified his life for my sisters and myself and provided unconditional support and

encouragement in all my pursuits. My sisters are my best friends all of my life and I

love them and thank them for all their special prayers and support. I thank to my uncle

Mr. Raheem Shah Mian for his continuous support, well wishes and prayers for the

completion of my doctoral work. I know I always have on my family when time are

rough.

IKRAM SHAH

Department of Sociology

University of Karachi

Abstract

In recent years sociological research has provided greater insight into the role of forces

that mould the career choices of students. Education is seen as stepping stone for status

attainment in social hierarchy. Studies have identified career preferences as one of the

major area of concern for young people entering into college level education. Because

choices are the fundamental process of human existence and the manifestation of

human individuality through which one expresses their personal values, belief and

preferences. Therefore, greater emphasis is placed on those forces which precipitate

students to choose one career over other. The present study investigated the

determinants of career decision-making among higher secondary level students of

Karachi. Particular attention was paid to examine the role of parental education,

parental income, family background influences, parental occupational backgrounds

characteristics, peer group influences, gender differences, psychological and

economic factors influences in career decision-making. Field of study was categorized

into four groups i.e. pre-medical, pre-engineering, commerce group and general

group. Through convenient and stratified random sampling techniques data was

collected from 512 students of 4 government and 4 private colleges located in Karachi

city. Both the gender were equally represented in the study. A structured questionnaire

was used to elicit the related information from students. Both descriptive and bivariate

analysis were conducted to establish the association of relationship between

dependent and independent variables. Data was analysed with aid of statistical

package (SPSS) version-20. Findings from the descriptive analyses suggested mean

age of 17.99 years for male students and 17.75 years for female students. Majority of

students living within nuclear family (male 57.8% and female students 53.5%) and

for both students secondary education was the mean category of parental education.

The mean score of parental income was higher for female students (3.48) than male

students (3.07). The bivariate analysis indicated that variables in question had

statistically significant association and to a large extent determine the students

anticipating career choices. Chi-square analysis shows that unlike mother, father was

the most influential person to affect students’ career decision-making process.

Father’s level of education and income were closely linked with students’ choices but

the effects were more robust for male students than female. Female students were

found to make their career decision more in conformity with their family expectations

and traditions. Across gender father’s occupational background characteristics exerted

strong effects on students choices. Ties with friends particularly the peer group was

emerged as both modeler and definer of students’ aspirations and perceptions. Female

students were more sensitive to peer group influences than male students. The study

also revealed that socialization in specific gender role had a greater extent influenced

students’ career decision-making. Unlike male, female students were found more

sensitive to gender influences and valued the gender identity in their decision.

Students are found to lay emphasis on their personal interests, choices and abilities in

their decision. The opportunity structure and economic advantages associated within

the career to a greater extent shape students choices. Female students were found less

sensitive to this effects in their career decision-making process.

List of Publication

1. Naz, A., Rehaman, H., Khan, Qaiser and Shah, I., (2011). An analytical study

of peer influence on behavioural modification and academic performance of

students in higher education of Pakistan. Indian Journal of Health and

Wellbeing, 2 (4), 704-710.

X

TABLE OF CONTENTS

Chapter

#

Title Page

#

Certificate……………………………….……………..……………….. I

Dedication……………………………………………………………… II

Acknowledgment……………………….……………….……………… III

Abstract English………………………………………………………… V

Abstract Urdu…………………………………………………………… VII

List of Publication……………………………………………………… IX

Table of Content………..…………….………………………………… X

List of Simple Tables…………………...………………………………. XIII

List of Contingency Tables…………………...………………………… XVI

List of Diagrams...…...……………………..…………………………... XVII

List of Figures……………...……....………………………...…………. XIX

1. Introduction…………………………………………………………… 1

1.1. Social Determinants of Career Decision-making…………………... 3

1.1.1. Family Background……..……………………………………... 7

1.1.2. Parental Education………….…………………………………. 9

1.1.3. Parental Occupation…...………...…………………………….. 10

1.1.4. Peer Group Influences…………......…………………………... 12

1.1.5. The Influences of Gender Differences.…….………..…………. 14

1.2. Psychological Determinants………..………………………………. 15

1.3. Economic Determinants……...……...……………………………... 16

1.4. Education System of Pakistan…………………...…………………. 17

1.5. Significance of the Study…………………..………………………. 18

1.6. Objectives of the Study………………..…………………………… 19

1.7. Hypothesis of the Study……………..……………………………... 20

1.8. Variables of the Study……………….……………………………... 21

1.9. Key Concepts………………...…………………………………….. 21

2. Theoretical Background and Review of Literature………………….. 24

2.1. Theoretical Background…………...……………………………….. 24

2.2.1. Rational Choice Theory……………..…………………………. 25

2.2.2. Social Reproduction Theory………………..………………….. 27

2.2.3. Life Course Theory…………………..………………………… 29

2.2.4. Social Learning Theory…….……………...…………………… 31

2.3. Review of Literature…………………..…………………………… 33

2.3.1. Family Background Influences……………..………………….. 33

2.3.2. Parental Education Influences………...………………………... 38

2.3.3. Parental Occupational Influences………..…………………….. 43

2.3.4. Peer Group Influences………………...………………………... 48

2.3.5. Influence of Gender Differences……………..………………… 52

2.3.6. Psychological Factors Influences……….……..……………….. 56

2.3.7. Economic Factors Influences…………….…..………………… 58

2.4 Conceptual Framework…………………………………………… 61

3. Research Methodology…………………..……………………………. 62

3.1. Research Methodology……………………..……………………… 62

3.2. Research Design…………………………..……………….……….. 62

3.2.1. Exploratory Research Design………………..……….………… 63

3.3. Type of Study……………………..…….………………………….. 63

3.4. Population………………………………………………………….. 64

3.5. Sampling Method…………………...……………………………… 64

3.6. Sample Size…………………………...……………………………. 65

3.7. Method of Data Collection………………...……………………….. 66

3.8. Pre-Testing……………………...…………………..……………… 67

3.9. Measurement……………...………………………..………………. 67

3.9.1. Demographic Profile……………………...………..…………….. 67

3.9.2. Parental Education………………..………………...……………. 67

3.9.3. Parental Occupation…………………...……………..…………... 68

3.9.4. Parental Income………………………..……………..………….. 68

3.9.5. Family Background Influences…………………..……...……….. 68

3.9.6. Parental Occupational Background Characteristics Influences...… 69

3.9.7. Peer Group Influences………..………………………………….. 69

3.9.8. Influence of Gender Differences……………...………………….. 69

3.9.9. Psychological Factors Influences……………...………………..... 69

3.9.10. Economic Factors Influences…………………………………… 69

3.10. Coding and Tabulation……………..…………………………….. 70

3.11. Statistical Methods of Data Analysis……………..………………. 70

3.11.1. Descriptive Analysis……………………………………..……... 70

3.11.2. Bivariate Analysis………………………….………….……….. 70

3.11.3. Chi-Square…………………………..………………….………. 71

3.11.4. Degree of Freedom……………………………………………… 71

3.12. P-Value……………………………………..…………………….. 71

3.13. Measurement of Correlation………………….……………….….. 72

3.14. Interpretation of Results…………………..……………………… 72

4. Analysis and Interpretation of Data…………….…………………… 73

4.1. Descriptive Analysis…………………..…………………………… 73

4.2. Bivariate Analysis…….……………..……………………………... 139

5. Summary……………..………………………………………………... 173

5.1. Summary……………...……………………………………………. 173

5.1.1. Parental Education Influences…………..……………………... 173

5.1.2. Parental Income Influences…………………….……………..... 174

5.1.3. Family Background Influences…………..….…………………. 175

5.1.4. Parental Occupational Background Influences………..………. 177

5.1.5. Peer Group Influences…………………..……………………... 178

5.1.6. Gender Differences Influences………………..……………….. 179

5.1.7. Psychological Factors Influences………………………..…….. 180

5.1.8. Economic Factors Influences………………………...………… 181

5.2 Theoretical Implication……………………………………………... 182

5.3. Conclusion……………………………………………..…………... 182

5.4. Limitations of the Study……………………………………..…….. 184

5.5. Recommendations…………………………………………...……... 185

5.6 Suggestions for Future Research……………………………………. 186

5.7. Implications………………………………………………..………. 187

6. Bibliography............................................................................................ 189

7. Appendix................................................................................................. 204

XIII

LIST OF SIMPLE TABLES

Table

#

Title Page

#

4.1 Frequency and percentage distribution of students with respect to

college type

74

4.2 Frequency and Percentage distribution of students according to

class

75

4.3 Frequency and percentage distribution of students according to

field of study

76

4.4 Frequency and percentage distribution of students according to

gender

77

4.5 Frequency and percentage distribution of students according to age

78

4.6 Frequency and percentage distribution of students with respect to

family type

79

4.7 Frequency and percentage distribution of male students according

to parental education

80


to father’s occupation

81


to mother’s occupation

82


to parental income

83

4.11 Frequency and percentage distribution of female students according

to parental education

84

4.12 Frequency and percentage distribution of female students’

according to father’s occupation

85


to mother’s occupation

86


to parental income

87

4.15 Frequency and percentage distribution of students’ knowledge

about career decision-making

88

4.16 Frequency and percentage distribution of male students’

perception about career decision-making

89


perception about career decision-making

90

4.18 Frequency and percentage distribution of students’ responses on the

important role of career decision-making in one’s life

91

4.19 Frequency and percentage distribution of students’ responses on the

level of importance of career decision-making

92

4.20 Frequency and percentage distribution of students’ responses on

what stage of life they have made career decision

93

4.21 Frequency and percentage distribution of students’ according to

their first career of choice

94

4.22 Frequency and percentage distribution of students’ responses on

any other choice of career

95

4.23 Frequency and percentage distribution of students’ according to

what was their first choice of career

96

4.24 Frequency and percentage distribution of students’ satisfaction

from their decision

97

4.25 Frequency and percentage distribution of students’ level of

satisfaction from their career decision

98

4.26 Frequency and percentage distribution of male students’ responses

with respect to the role of family background in career decision-

making

99


with respect to family background influences

100

4.28 Frequency and percentage distribution of female students with

respect to the role of family background in career decision-making

102


responses with respect to family background influences

103


with respect to the role of parental occupational background

characteristics

105


with respect of role of father’s occupational background

characteristics influences

106


with respect to role of mother’s occupational influences

108


responses with respect of role of parental occupational background

110


responses with respect of role of father’s occupational influences

111


responses with respect of role of mother’s occupational influences

113


regarding the role of peer group influences

115


with respect to peer group influences

116


responses regarding the role of peer group influences

118


responses with respect to peer group influences

119


regarding the role of gender differences

121


with respect to influence of gender differences

122


responses regarding the role of gender differences

124


responses with respect to influence of gender differences

125


regarding the role of psychological factors influences

127


with regarding the psychological factors influences

128


responses regarding the role of psychological factors influences

130


responses with regarding the psychological factors influences

131


regarding the role of economic factors influences

133


with respect to economic factors influences

134


responses regarding the role of economic factors influences

136


responses with respect to economic factors influences

137

4.52 Summary of Reliability Estimate 139

LIST OF CONTINGENCY TABLES

Table

#

Title Page

#

4.1.1 Association between parental education and male students’ career

decision-making

140

4.1.2 Association between parental education and female students’

career decision-making

142

4.2.1 Association between parental income and male students’ career

decision-making

144

4.2.2 Association between parental and female students’ career

decision-making

146

4.3.1 Association between family background influences and male

students’ career decision-making

148

4.3.2 Association between family background influences and female


150

4.4.1 Association between parental occupational background and male


152

4.4.2 Analysis of bivariate relationship between parental occupational

influences and female students’ career decision-making

154

4.5.1 Association between peer group influences and male students’


156

4.5.2 Association between peer group influences and female students’


158

4.6.1 Association between the influence of gender differences and male


160

4.6.2 Association between the gender influences and female students’


162

4.7.1 Association between psychological factors influences and male


164

4.7.2 Association between psychological factors influences and female


162

4.8.1 Association between economic factors influences and male


164

4.8.2 Association between economic factors influences and female


166

LIST OF DAIGRAMS

Table

#

Title Page

#

4.1 Percentage distribution of students according to college type 74

4.2 Percentage distribution of students with respect to class 75

4.3 Percentage distribution of students according to field of study 76

4.4 Percentage distribution according to gender

77

4.5 Percentage distribution of students according to age 78

4.6 Percentage distribution of students with respect to family type 79

4.7 Percentage distribution of male students according to parental

education

80

4.8 Percentage distribution of male students’ according to father’s

occupation

81

4.9 Percentage distribution of male students with respect to mother’s

occupation

82

4.10 Percentage distribution of male students according to parental

income

83

4.11 Percentage distribution of female students according to parental

education

84

4.12 Percentage distribution of female students according to father’s

occupation

85

4.13 Percentage distribution of students’ according to mother’s

Occupation

86

4.14 Percentage distribution of female students’ according to parental

income

87

4.15 Percentage distribution of students’ knowledge about career

decision-making

88

4.16 Percentage distribution of male students’ perception about career

decision-making

89

4.17 Percentage distribution of female students’ perception about


90

4.18 Percentage distribution of students’ responses on the important

role of career decision-making in one’s life

91

4.19 Percentage distribution of students’ responses on the level of

importance of career decision-making

92

4.20 Percentage distribution of students’ responses on what stage of life

they have made career decision

93

4.21 Percentage distribution of students’ according to their first career

of choice

94

4.22 Percentage distribution of students’ responses on any other choice

of career

95

4.23 Percentage distribution of students’ according to what was their

first choice of career

96

4.24 Percentage distribution of students’ satisfaction from their

decision

97

4.25 Percentage distribution of students’ level of satisfaction from their

career decision

98

4.26 Percentage distribution of male students’ responses with respect to

the role of family background in career decision-making

99

4.28 Percentage distribution of female students’ with respect to the role

of family background in career decision-making

102


the role of parental occupational background characteristics

105

4.33 Percentage distribution of female students’ responses with respect

to the role of parental occupational background characteristics

110

4.36 Percentage distribution of male students’ responses regarding the

role of peer group influences

115

4.38 Percentage distribution of female students’ responses regarding

the role of peer group influences

118


gender differences role in career decision-making

121

4.42 Percentage distribution of female students’ responses with respect

to gender differences role

124


role of psychological factors in career decision-making

127


the role of psychological factors in career decision-making

130


role of economic factors in career decision-making

133


the role of economic factors influences

136

4.1.1 Association between parental education and male students’ career

decision-making

140

4.1.2 Association between parental education and female students’ career

decision-making

142

4.2.1 Association between parental income and male students’ career

decision making

144

4.2.2 Association between parental income and female students’ career

decision-making

146

4.3.1 Association between family background and male students’ career

decision-making

148

4.3.2 Association between family background and female students’


150

4.4.1 Association between parental occupational background

characteristics and male students’ career decision-making

152

4.4.2 Association between parental occupational background

characteristics and female students’ career decision-making

154

4.5.1 Association between peer group influences and male students’


156

4.5.2 Association between peer group influences and female students’


158

4.6.1 Association between the influence of gender differences and male


160

4.6.2 Association between the influence of gender differences and female


162

4.7.1 Association between psychological factors influences on male

students’ career decision

164

4.7.2 Association between psychological factors influences on female

students’ career decision

166

4.8.1 Association between economic factors influences and male


168

4.8.2 Association between economic factors influences and female


170

LIST OF FIGURE

Figure

#

Title Page

#

2.1 Conceptual Framework 61

3.1 Sampling Plan 65

1

CHAPTER 1

INTRODUCTION

Education selection is a crucial decision and plays a strategic role in the process of

status attainment and social stratification in society. As decision-making is one of the

complex mechanism of hum thinking process, as different factors and courses of

action intervene in it, with different results. According to Foskett and Hemsley-Brown

(2001:1) choices are the fundamental processes of human existence and the

manifestation of human individuality through which one expresses his/her values,

beliefs and individual preferences. Bourdieu and Wacquant (1992:18) argue that we

all are born into a social setting and our actions and beliefs must be suited to the social

and cultural environment. Saljo (2003:315) views career decision-making is a learning

process within the social milieu in which people operate. Arnold (2004) viewed the

students’ choices or preferences as the students’ intention to pursue their career in the

particular occupation. It is contended that there are five steps to be followed to reach

a decision: one must realize that it is necessary to make a decision, determine the goal

to be achieved, generate alternatives that lead to attaining the proposed goals, evaluate

these alternatives whether these alternatives meet one’s expectations and choose the

best alternative (Halpern, 1997: 190-191).

Giddens (1991:81) argues that young people perceive the career decision-making

process as individual choice because traditions have lost its hold and the collective

identities and certainties have weakened. In the post-modern world, individual is

constantly engaged in constituting and reconstituting of their self-identity to respond

to emerging risks and opportunities by preparing themselves for future course of

actions which Giddens termed as strategic life planning. In the postmodern world the

openness of social life becomes more significant and individual has the choices in a

greater degree than before. According to Hodkinson and Sparkes (1997:34) individual

makes the career decisions within the horizons for action, which means the social

structure in which individual takes actions and makes his decisions. The horizons for

action shaped the individual’s perception of the range of opportunities available to

him and what a person perceives as possible and appropriate for him. They argue that

career decision-making of young people is bounded by a person’s horizons for action.

The term career decision-making process is a meta concept and it occurs throughout

life cycle of individual. According to Super (1981) career decision-making is the

sequence of major positions occupied by a person throughout his pre-occupational,

occupational, post-occupational roles; including work related roles such as those of

student, employee, and pensioner, familial and civil role.

Sociologists are primarily interested in the ways social institutions affect the life

choices of individual such as educational attainments, occupational choices, work

orientations and attainments as a person moves through the life courses (Brown,

2002:40). Moreover, sociologists are interested in career choice selection of

individuals because of its consequences for socioeconomic inequalities and mobility,

as occupation is the best predictor of one’s status within society, earnings and life

style. In the last several decades the vertical dimension of occupation has remained

the central point of inquiry in many sociological discourses and it is linked with one’s

placement in the socioeconomic ladder (Brown, 2002:37-38). The growing rate of

changes in the field of work has increased career pathways options for young people

and entry into different career routs are largely dependent on the qualification gained

at post-secondary level (Bait and Riseborough, 1993). Therefore, choice of major has

important link with options available to students for further education and future

career development. Thus, choice of college major is both immediate outcomes of the

educational process and a determinant of later outcomes of many kinds (Turner and

Brown, 1999). Evidences continue to grow concerning the identification,

understanding and empirically validation of the determinants that precipitate students

in career decision-making process (Gianakos, 1999; Turner and Bowen, 1999; Palos

and Drobot, 2010).

National level studies have confirmed deep-seated differences and inequalities among

young people’s career choices selection. Studies also describe the process through

which different career pathways are stratified and preferences are given to one over

others. Such studies help us to understand that how and why such variations persist in

career routs selection among students and identify the associated factors that either

restrict or ease the opportunities for young people in their career choices (Ashton and

Field, 1976; Furlong, 1992; Kerckhoff, 1993; Bates and Riseborough, 1993; Johnes,

1999; Hallissey et al., 2000; and Buchmann and Dalton, 2002).

Career choice is a multifaceted concept that has attracted many researchers and

academics from various fields and spurred considerable research over the past couple

of decades. The body of research which does explain the career decision of young

people has primarily focused on the overall correlation of determinants that

conditioned entry into different majors at secondary and postsecondary education. It

is revealed from the literature that polarity of explanations exists in both theoretical

and empirical understanding about how career decisions are made among students and

why certain careers are preferred than other (Choy, 2002). All the above definitions

and different explanations indicate that career decision-making is a complex process

and one of the crucial decisions which has many outcomes in the later stages of life.

1.1 Social Determinants of Career Decision-making

In sociological discourses the subject of career choice is extensively studied and the

individuals preferred career rout is most closely associated with subsequent placement

in social hierarchy. The sociological literature which does exist, much concentrated

on the patterned life chances and career trajectories that are seen as the result of social

and structural settings of individuals (Hodkinson and Sparkes, 1997:29). Describing

individual choices Bourdieu profoundly contributed in this regard and views the

individual career choices are the outcome of cultural capital. He contends that cultural

capital enables the social reproduction of hierarchies and inequalities between elite

and lees privileged backgrounds students enrolling in different fields at secondary and

post-secondary education. Students from high privileged families receive high

cultural capital from their homes, this acquisition of cultural capital is strongly linked

with students’ academic success and career choice trajectories, which then strongly

contributed to secure the privileged students positions in social structure. They argue

that less privileged students are more likely to pursue their careers in vocational and

technical fields (Bourdieu and Passeron, 1977 & 1979). In Britain Archer and Francis

(2006) study found association between Bourdieu concept of cultural capital and

academic success of British Chinese students.

Career decision-making is an area where the importance of lifestyle choices is also

identified and examined; for example, Giddens (1991:80) argues that individuals have

the potential for selecting their personal lifestyle and identities. Individuals can take

control over their future and maximize the employment opportunities by engaging in

strategic life planning. Williams (1995) presented a theoretical explanation to the

relationship of class, health and lifestyles choices of individuals. Based on the

Bourdieu concept of practical logic and logic of practice, the study identifies and finds

significant relationship between social class and health related lifestyle choices of

individuals.

Sociologists who studied the process by which individuals actually select career routs

have focused primarily on the stages when individuals actually choose to enter jobs,

rather than on the decisions to move into activities at earlier stages on the paths leading

to specific career (Correll, 2001:1693). Therefore, key inquiries are conducted in three

areas i.e. gender and race disparities in career pathways selection, influencing factors

in entry into science fields and the occupational outcomes associated with different

majors (Goyette and Mullen, 2006:499). Thus, the decision of college major at

secondary and post-secondary level is of critical importance because it is considered

as a step toward implementing career decision-making (Lappel et al., 2001:373; and

Sewell et al., 1970:1023).

Recent studies describe variations in the career pathways selection process of young

people and assert relationship between background variables such as social class,

socioeconomic background, gender, level of academic achievements, significant

others and one’s career decision-making process (Tang et al., 1999; Goyette and

Mullen, 2006; Porter and Umbach, 2006; Anderson and Gilbride, 2005). Study

conducted by Leppel et al., (2001) reported that socioeconomic status and parental

occupation play significant role in determining students’ choice of college majors.

It is well documented that cultural values have been identified to determine and exert

strong effects on individual career decision-making behavior and later career

progression. Variations were found in career pathways selection among students

belong from different cultural backgrounds. Examined the career choices of students

across cultures , it was found that career trajectories selection of students are largely

constrained by their cultural backgrounds (Ozbilgin et al., 2005; Swason and Gore,

2000; and Hardin et al., 2001).

In individual oriented cultures students are less responsive to social factors influences

in career decision-making process; students were found independent, autonomous and

rational in career decision-making. Students lay emphasis on and looking for personal

advantages of their career decision-making. In collectivistic cultures, social factors

may exert significant influences on individuals’ career trajectories selection. It is

documented that in collectivistic culture students view their decision in terms of

collective advantages; they give more preference to social conformity and group

advantages. Students from collective oriented culture were found dependent and

facing difficulty in career decision-making (Mau, 2004; and Agrawala, 2008).

Previous studies have suggested that acculturation does have effect on career decision-

making process because it is considered as a moderator for career development.

Students with high acculturation have tendency to choose lees typical careers and

navigate effectively for a better career rout selection; those with less acculturation

have a propensity to select high typical careers for their futures (Tang et al., 1999; and

Yeh, 2003).

The social background variable in educational attainment and career trajectories

selection has long been the focus of sociological enquiries. Studies suggest that social

background strongly affects the level of education that one attains and determines

ones career pathways in future. There is considerable research that shows that

advantaged social background students tend to select more prestigious majors in

secondary and post-secondary level (Shwed and Shavit, 2006; and Werthforst et al.,

2003 and Lucas, 2001). Students belong from manual labor background have

tendency to enroll in less prestigious, less selective fields and choose field of study of

shorter duration that require less grade point requirement (Reimer and Pollak, 2005;

and Hallsten, 2010). Halaby (2003) compares US students’ preference of bureaucratic

career; which has high job security and pension rights in the later stage of life and

entrepreneurial career of high pay and having attractive career. He found that less

advantaged social background students have the tendency to value the bureaucratic

career over entrepreneurial career. Similar findings were revealed from Johnson

(2002) study, who found that in the US high school seniors from the less advantaged

social background have rated career security as important element in career selection.

Understanding the influence of ethnic and racial background of young people and

their career choices Goyette and Mullen (2006) study suggests that ethnic and racial

backgrounds of students play a significant role to determine one’s choice for further

education and career trajectories. For instance, Xie and Goyette (2003) study found

that the racial background of Asian Americans students’ does exert influences on

career rout selection process. They may choose those fields for their future education

and career development with high earning potential as a way to ensure their upward

social mobility. Non-Hispanic students were found less sensitive to economic returns

effects, while choosing their career in vocational fields.

Similar findings were also revealed by Tang et al., (1999) study conducted on the

Asian American students’ career choice process, the study contends that regardless of

other variables Asian American students pursue their careers in traditional fields.

American students were found dependent in their career decision-making, while

Taiwanese students lay emphasis on social conformity and collectivity in their career

decisions. Simpson (2000) coded different fields into five broad types and find

differences in college major preference between racial and ethnic groups. In the recent

years considerable attention has been paid to underrepresentation of female and Asian

minority in science majors. It was found that they are less likely to choose science

majors as compared to White students (Mullen 2001). Compare the Asian American,

Hispanic and Black students’ decision to enter into Science, Engineering and Math

disciplines, the study yields comprehensive evidences to connect students’ racial

origin and career routs selection process (Auyeung and Sands, 1997).

Moreover, a large body of research has included the exploration of socioeconomic

background effects on students’ career pathways selection. The studies figure out that

socioeconomic status is important element in career rout selection; for instance,

students belong from lower socioeconomic background are more likely to pursue a

career in more lucrative fields of study (Trusty et al., 2000; and Leppel et al., 2001).

It is reported that the effects of socioeconomic status on choice of college majors

varied by gender, as female students were found more sensitive to this effect, while

regardless of socioeconomic status male students considered the anticipated pecuniary

returns to enter into Science and Engineering disciplines (Goldrick-Rab, 2006).

Moreover, socioeconomic status of female students decreases the probability to enter

into high payoff disciplines (Leppel et al., 2001). Monetary returns and social status

attached with majors have strongly determined the male students career pathways

selection process (Trusty et al., 2000).

Describing the students’ major choices Goyette and Mullen (2006) argue that

socioeconomic status has significantly shaped the students decision of majors.

Affluent background students have tendency to major in Science and Arts fields,

whereas less affluent background students were found to enroll in vocational fields

for future career progression. Because of gender stereotyping persists in career

trajectories selection, female students were found more conservative and responsive

to social milieu in career decision process and are less likely to enter into male

dominated fields, consequently this increases female underrepresentation in some

fields (Francis, 2002; Leppel et al., 2008; and Osoro et al., 2000). Growing evidences

associated careers stereotyping by sex with many kinds of out comes in later stages of

career progression and development (Reskin and Bielby, 2005). The discussion

indicates that sociologists viewed educational attainment as a means for upward social

mobility and career choices are correlated with social and structural milieu of

individual. The next section is related to the current study hypothesized determinants

that precipitate students in their career decision-making process at post-secondary

level.

1.1.1 Family Background

A substantial body of research literature affirms the association between family

background variables and students different career trajectories selection process. It is

argued that students likely to choose major that is corresponding to parental social,

cultural and economic positions; students take the parents social position as a point of

reference for aspirations (van De Werthforst et al., 2001). Sociologists generally

explain and associate the family background with social, economic and cultural

capitals that is considered as prerequisite for further educational attainment (Bourdieu

and Passeron, 1977-1979; Colmen, 1988: and DiMaggio, 1982). Particularly, studies

have focused on the transition from secondary to postsecondary/college level

education and reflection of family backgrounds variable was not only documented but

polarity of effects was also documented for students belong from different family

backgrounds (Karen, 2002).

It is also suggested that family background capitals not only provide opportunities for

educational success and ways to alternatives career options but also constitute social

relations and networks that generate resources for various outcomes (Bryant et al.,

2006; Palos and Drobot, 2010; Teske and Schneider, 2001; Corell, 2004; Emerich and

Francesconi, 2000). According to Lucas (2001) that parents who have more social,

economic and cultural capitals and access to useful information, they act to promote

their children toward different kind of choices and career pathways that consequently

secure qualitative advantages for their children. Students who have lack of such

capitals and less access to useful information can be assumed to have high uncertainty

and less educational commitment. Resultantly, it minimizes their educational efforts,

develop lower future ambitions; students choose their career routs in more random

fashion; without considering the anticipated results in the later stages of life

(Archbald, 2000; and Morgan, 2005). It is also revealed from the literature that

advantaged background families have the tendency to exercise institutions choices

and choose more prestigious institutions for their children education (Teske and

Schneider, 2001; and Archblad, 2000).

Throughout career decision-making process family plays salient role in negotiating

different career choices with children and provide them resources in the home and

managing children’s educational careers (Conley, 2004; and Furstengburg et al.,

1999). Family involvement and engagement in the career choice process is associated

with high career aspirations and high level of confidence among students (Salami,

2004). Earlier studies show that family structure may depict differences in educational

choices among students’; parents’ attachment and presence are positively associated

with postsecondary educational choices, while parents’ separations or family

dissolution lead to greater educational inequality among students (Laftman, 2008).

Lower test score, lower marks at secondary level, high dropout and lower propensity

to choose a major at the postsecondary educational level have been suggested among

students who have experienced parental separation or family dissolution (Weitoft et,

al., 2004; and Mahlar and Winkelmann, 2005).

Students belong from manual workers background families are less likely to stay on

for further education and choose the prestigious subjects for their future concentration

than the professional backgrounds families (Werthforst et al., 2003; Thomas and

Webber, 2009). It is also contended that family size exerts negative effects on

students’ academic success and career development (Rochat and Demeulemeester,

2001). Parental attitudes significantly contribute towards the development of social,

cognitive and intellectual abilities among students. Parental attitudes are perceived as

both definer and shaper of students’ career aspirations and career readiness. Negative

parental behavior is associated with lower career aspirations and career indecision

among students (Palos and Drobot, 2010; and Buchmann and Dalton, 2002). To

conclude the discussion, family background influences are well documented in the

literature and students career aspirations and expectations are to a greater extent

shaped by their familial social, cultural and economic capitals.

1.1.2 Parental Education

A large stream of literature demonstrates the intergenerational transmission of fields

of study of parents to children and similarities were found to some degree between

the parents and children educational selection (Kalmijn and Kraaykamp, 1996; van

De Werthforst et al., 2001; and Jonsson et al., 2009). The influential role of parents

over the offspring’s educational decision is fairly stable in all societies over time.

Students’ early educational decisions and later different career trajectories selection

process is strongly affected by their parental educational background (Ermisch and

Francesconi, 2001).

It is generally believed that parental years of schooling is not only a contributing

element in children educational decisions but students of better educated parents are

more likely to obtain a high and better education than students who have less educated

parents. Parents are assumed as role model and found to be significantly influential

on the offspring’s decision to enter into the same field of study as they are educated.

In fact, when child choose similar educational fields of their parents, parents see their

own resources are reproduced. Parents educated in the same field are able to provide

the relevant useful information to their children about the difficulties and

opportunities of their own particular field (Kalmijn and Kraaykamp, 1996; and

Sullivan, 2001). Van De Werthforst et al., (2001) documented that intergenerational

transmission of preferences and similarities of fields of study are stronger in some

fields than others. For example, in some fields parents refrain their children to enter

into their own educated fields because of heavy workload or limited labor market

opportunities. It shows that parents’ own educational level may significantly shape

their perception of what is an appropriate career for their children (Dustmann, 2004).

In the process of intergenerational transmission of educational aspirations and filed

preferences, it is contended that children choices are either limited or attracted to the

educational fields of their parents. When children take their parents social position as

a point of reference for their own inspirations and educational choices; there is high

probability that children will choose educational fields similar to their parents.

Consequently, it will help to reach and establish the social status of their parents

(Dryler, 1998).

The level of parental education not only determines the student educational attainment

but also strongly predicts the entry into specific career rout for their children.

Variances in parental educational background effects were found between male and

female students; male students’ field selection decision may be more affected by

father’s educational background, while mother’s educational background does affect

the educational decision of female students. For example, high school degree held by

the father increases the probability for the son to attain the intermediate and higher

level education. Whereas mother held high school degree increases the probability for

female to achieve intermediate or higher level education. The parental post schooling

education is not only significantly exerting positive effects on children to attain

graduation and more education but also encourage their children to choose long term

duration fields of study for their future (Goyette, 2008; Dustmann, 2004; and Rochat

and Demeulemeester, 2001).

Parents holding university degree my not only foster the educational success among

students but also encourage and promote their children to enter into more

advantageous fields. This may also increase the odds of students to give preferences

to one field over other (Boudarbat, 2006). For example, father holding a university

degree may encourage their children to enter into scientific orientation fields such as

Medical Sciences, Natural Sciences and Engineering, while entry into literary

orientations subjects such as Law, Social Sciences and Humanities was found among

students having mother with university degree. Although the parental academic

background may affect the field selection decision but this effect may be highly differ

by associated rewards and advantages within the subjects (Rochat and

Demeulemeester, 2001). However, a dramatic shift of educational attainment has been

documented and it is contended that not only more educated parents expect the same

or more qualification from their children but the lees educated parents have high

tendency to expect high qualification form their children too (Goyette, 2008). It is

evidently reflected from the above discussion that parental education to a large extent

determine the students educational choices and students are on the odds to achieve

same or more advanced level of education as their parents.

1.1.3 Parental Occupational Background Characteristics Influences

The literature shows that parental occupation variables strongly predict children

occupational aspirations. The parents’ occupational characteristics are believed to be

influential on both the parents’ personalities and values, which may be in turn

reflecting in their parenting behavior. For example, children will either receive

rewards and appreciations for some behaviors or will be discouraged and refrained

from other behaviors in the home environment. Children are watching their parents

very closely and then imitate what they have learnt. Parental occupational and

professional interests depicting in the home environment in terms of things, literature

and activities are more likely to attract their children towards the same occupations or

professions. Consequently, children are on the odds to make their anticipated entry

into the similar fields already occupied by their parents. It is also assumed that parental

own occupational background may also shape their perception of what will be an

appropriate career for their child (Jodl et al., 2001; Jhonson et al., 2002; and

Dustmann; 2004).

There is considerable support that parental occupational background affects several

child outcomes including their occupational attainment behavior. Parental

occupational status and working conditions are assumed to exert both positive and

negative effects on the children occupational aspirations. For instance, parents who

are occupied in prestigious and high social status occupations may foster positive

effects on child aspirations and will promote and encourage them to enter into their

similar fields. Parents occupied at the bottom of the ladder occupations may either

enter into lower track education or discourage their children to enter into the same

fields. Both parents are differently affecting their children as male child is more

affected by the father occupational background, while female child occupational

aspirations are strongly linked with mother’s occupational background (Jodl et al.,

2001; and Lucas, 2001).

It is tended that parental job characteristics are strongly associated with children

secondary educational choices and to some degree may shape their college major

choices decision (Dustmann, 2004). For instance, Jonsson et al., (2009) study shows

that 10% of the Swedish male students have chosen their father’s occupation. Jodl et

al., (2001) examined the parental occupational background effects on students’

decision on college majors; they found that parental professional or executive

occupational backgrounds determine students’ college major decision. Male students

were found to major in Business, Social Sciences and Humanities, while increases the

probability for female students to major in Sciences, Engineering and Health Sciences.

Another study shows that father holding an elite occupation increases the chances for

male students to major in Engineering and Business related fields and will give more

preferences to choose long duration curricula (Rochat and Demeulemeester, 2001).

The aforementioned discussion lend support to assumption that parental occupational

background characteristics are both provide opportunities and constraints to their

children to choose the same or different occupation for their future.

1.1.4 Peer Group

A substantial amount of research has been carried out to explore friends’ dynamics in

educational expectations and aspirations. Young people become increasingly

interested to think about their future education and career development during their

adolescent years. Sociologists have paid attention to the importance of interpersonal

relationships in the life courses of individuals. A person prefers to constitute

friendship with others who like themselves in many ways and have something

common in them including age, gender, race, educational attainment, social positions

etc. Adolescents see their network of friends as a social capital which seems to be a

source of many other outcomes (Kiuru et al., 2007). But the salient social context lies

within this network is peer group; with whom adolescents associate their identity; with

whom they would like to be a friend. When children reach adolescence, peer relations

begin to play an important role in their lives. It has been suggested that adolescents

acquire a wide range of skills, attitudes and experiences in peer relationships. It is

perceived that adolescents are found to be more responsive to their network of friends

and likely to adopt them in many ways. Members of peer group strongly influences

each other and tend to confirm to the expectations and demands of peers behavior

because of less group conformity leads toward group exclusion. Majority of

adolescents do confirm to peers behaviors either to gain from group social capital in

the wider social network or avoid the risk of ostracize from the group (McPherson et

al., 2001; Crosnoe et al., 2008; and Alkerlof and Kranton, 2002).

During adolescence educational attainment and preparation for working life are the

most important developmental tasks. Adolescents are increasingly interested in these

topics and do think about their future educational goal and life planning. It is assumed

that aside from parents and teachers, adolescents often discuss their future related

decisions with their peers. Adolescents not only receive feedback and support from

their peer but also obtain valuable career related information. For adolescents, school

is the primary extra familial institution where majority of adolescents spend more of

their day time and usually meet and interact with other students and looking to develop

social ties in the shape of friendship. This is evident that school structure affects the

compositions and characteristics of adolescents’ friendship. It is contended that

students choose their friends either on the basis of course they take or similarities and

social priorities. The association with peer group may exert both positive and negative

influences on adolescent behaviors. For instance, it is suggested that academically

competent students attract each other into a greater academic engagement and

achievements through modeling, support and reinforcement. Consequently similarity

of high academic performances and engagement provides ground to strengthen their

relationship and they are more likely to become friends (Crosnoe et al., 2003;

Kubitschek and Hallinan, 1998; and Moddy, 2001).

It is assumed that academically rich friends have a positive impact on students’

academic outcomes. The friends’ knowledge and ability is considered as a source of

social capital that provides resources and opportunities to the students. Such friends

are considered to help the students to keep on track and encourage them to navigate

in a more demanding educational fields which will lead to a successful career

trajectory (Crosnoe et al., 2003). Further evidences have supported this assumption

by describing the students Math course taking behavior; friends course taking

behavior increase the probability for adolescents to choose the same Math courses in

high school. (Leppel et al., 2008). Buchmann and Dalton (2002) study shows that peer

group has an important role to shape the educational aspirations of the students and

peer values of Math performance has significant association with students high

educational aspirations.

Peer group influences are documented separately for male and female students. It is

suggested that peer group may function differently and serves different purposes for

male and female students. A large stream of literature shows that female students are

more affected by group characteristics and found more responsive to group norms.

But male students are also not immune to peer group effects and their attitudes and

actions are strongly affected by peer group characteristics (Leppel et al., 2008; and

South and Haynie; 2004). Describing the peer group influences on students’ decision

of entry into different educational fields, it is suggested that female students having

same sex friends with higher subject grades are more likely to take advance courses

of Math, Physics and English. The presence of opposite sex friends in advance courses

increases the probability for male students to entry into the similar fields (Riegle-

Crumb et al., 2006). To sum up the peer group influences, the discussion indicates

that both students valued their friendship ties in their decision and on the odds to

choose a similar career for their future as their friends.

1.1.5 The Influence of Gender Differences

The early socialization process at home plays a significant role in shaping children

behaviors. Within home environment children learn and internalize the specific

gender role which profoundly affects children’ sense of what others expect from them.

It is suggested that socialization in traditional gender role leads toward gender

differences in choices (Lackland, 2001 and Ridgeway, 1997). This gender based

constructed identity continues to influence male students to choose a career trajectory

that reflects traditionally masculine aspect and reinforces the female students to enter

into a career trajectory that has traditionally feminine characteristics (Francis, 2002).

Croson and Gneezy (2009) study have also confirmed the gender differences in

preferences in three areas i.e. social, risk and competitive. The decisions of career

trajectory selection are made in many times throughout life cycle but this early gender

based constructed identity may lead to differences between male and female entry into

different careers pathways (Ridgeway, 1997).

Describing the gender differences in career rout selection it is argued that not only

gender identity is evidently reflecting in student’s career decision-making behaviors

but both the students also attach different values to after college opportunities

associated with each area of concentration (Turner and Bowen, 1998; and Francis,

2002). Some studies indicate that effects of gender preferences lead to segregation in

many fields; male students are choosing their career in traditional fields which are

mainly masculine domain; female students are assumed to choose their careers in

traditionally feminine domain (Francis, 2002; and Correll, 2001). Consequently, this

segregation of fields in turn leads to either overrepresentation of one gender in

particular fields or underrepresentation in some other fields. For example, it is

considered that female students are either underrepresented in Science, Math and

Engineering fields or overrepresented in Health and caring fields. It shows that female

students are more likely to pursue a career in less technical fields; resultantly female

experienced a wider gap in earnings (Werfhorst et al., 2001).

Moreover, the career decision of male students profoundly affected by anticipating

future earnings variable; male tends to choose more rewarding educational fields for

their future concentration; female students are less likely to consider anticipating

earnings variable in their career pathways selection (Montmarquette at al., 2002,

Davies and Guppy, 1997; Goyette and Mullen, 2006; and Eide and Waehrer, 1998).

Francis (2002) examined the secondary and high secondary students’ career decision

and found strong gender differences in educational fields’ selection. The study shows

that male students inclined to choose Science, Engineering and IT fields for their

career concatenation and female students tend to enter into Humanities and Arts

subjects. Goyette and Mullen (2006) study shows that between Arts and Science

fields’ female students are more likely to enter into Arts fields than male. The study

further shows that there is persistent gender differences in male and female students’

decision of entry into vocational fields’; male students tend to choose Engineering

field; female students are more inclined to choose education for their future

concentration. Correll (2001) study has also shown that male students’ perception of

mathematical competencies leads career path in Math, Engineering and Physical

Sciences fields. On the basis of aforementioned discussion it has been concluded that

widely shared culture belief about gender channelized both students to different career

routs. Male students are more interested to opt for masculine domain fields, while

female students considered feminine suited career for their future.

1.2 Psychological Determinants of Career Decision-making

Psychologists have recognized the importance of personal and environmental factors

influences in career selection process (Porter and Umbach, 2006; Pike, 2006; Rogers

et al., 2008; and Fan et al., 2012). The link between personality traits and career routs

selection are well established in literature; for instance, Larson et al., (2002) study

concludes that Holland’s big five personality’s dimensions were very closely

correlated with six interests dimensions (e.g., Artistic with Openness, Enterprising

with Extraversion, Social with Extraversion, Investigative with Openness, and Social

with Agreeableness) among students. Zhang (2008) finds similar findings in Hong

Kong for a cohort of university students. Other studies argue that career aspirations

act to encourage the young people to choose a career path that is congruent with their

interests, abilities and personality (Kuh et al., 2005; Lent et al., 1994; Salami, 2004;

and Super, 1990). Studies have also showed that students choose environment where

certain behaviors and beliefs are supported and rewarded, which may further help

them in selecting of preferred career of interest which suited their personality (Smart

et al., 2000; Tracey and Robbins, 2006; Pike, 2008; and Buchmann and Dalton, 2002).

Similarly, studies tend to demonstrate the predicative role of self-efficacy in career

development; students’ high self-efficacy has a significant positive impact on

students’ eventual career choices; low self-efficacy of female students is associated

with limited career mobility and narrowed career options (Tang et al., 1999; and

Salami, 2004). Significant others particularly parents, friends, teachers play an

important role in shaping individuals educational attainment and career aspirations

(Buchmann and Dalton, 2002). Moreover, career decisiveness or readiness behaviors

are also linked with high academic grades and better career routs selection (Howard

et al., 2009; Kelly and Lee, 2002; Kleiman et al., 2004; Gianakos, 1999; and Mau,

1995). To conclude the psychological factors influences in students’ career decision-

making, psychological factors influences to a large extent determine students’ choices

at post-secondary level.

1.3 Economics Determinants of Career Decision-making

Economists have long sought to predict career decision-making behaviors of

individuals and explored the underlying factors in the process. Studies show that

anticipated earnings are essential variables in the process of career decision-making.

Entry into different career trajectories are highly dependent on expected future

monetary returns from one’s major. Gender differences exist in this variation and

female students were found less sensitive to this aeffect (Boudarbat, 2008; Thomas

and Zhang, 2005; and Ermisch and Francesconi, 2000).

Using the data from National Longitudinal Survey of Youth in the US, Montmarquette

et al., (2002) found that students’ decision of college majors are significantly

associated with expected earnings. The study shows that female students are

considerably less sensitive to high pecuniary returns. Moreover, findings of study

conducted by Finnie and Frenette (2003) reveal that students stratified the college

majors by discipline and select the anticipated high earnings major for their future

concentration. Research studies also show that students’ decision of college major is

considerably linked with probability of job prospects and anticipated high wages

expectations (Brunello et al., 2004). Male students do consider the expected high

returns in their decision of major, while female students were found less likely to

consider the anticipated higher returns in their decision (Eide and Waehrer, 1998).

On the basis of above discussion, it is evidently reflected that opportunity structure

and associated monetary returns within the career is a linchpin of students’ career

choices at post-secondary level.

1.4 Educational System of Pakistan

Pakistan’s education system has three main components; elementary education,

secondary education and university education. Elementary education comprises of

pre-primary, primary and middle level education. Currently in Elementary level

education more than 31.834 million students are enrolled at different stages in public

and private sector institutions. Secondary level education is divided in high and higher

secondary education. At the high secondary level more than 2.684 million students

are enrolled in both public and private sector institutions. At this level private sector

provides education to 34% students in the country (Pakistan Education Statistics,

2011-12).

The higher secondary/inter colleges level education includes grades 11 and 12.

According to Pakistan Education Statistics (2011-12) in the years 2006-07 there was

only 933 institutions running in the country but over the last seven years significant

increase in the higher secondary level institutions were observed and currently

approximately 4,480 institutions providing education facility in the country; including

1,492 public sector institutions and 2,988 private sectors institutions. In the year 2011-

12 in total 1.246 million students were enrolled in these institutions. The data shows

that .900 million (72%) students were boys and .345 million (28%) were girls students.

Beside that the country is ranked lowest in higher secondary net enrollment rate, a

significant increase has been reported in boys (39.38%) and girls (28.60%) net

enrollment at higher secondary level. The data of Educational Census of Pakistan

(2005) shows that in total 1.0048 million students were enrolled at the higher

secondary level; in Science group .3988 million, General group .4596 million and

.1465 million in Commerce group.

University provides education at higher level to students and prepares them in many

fields to participate in the labor force of the country. Currently there are 79 public

sector universities and 60 private sector universities in the country. Total enrolment

of students in these universities is 1.319 million, whereas only 14% of these students

are enrolled in private sector universities (Pakistan Education Statistics, 2011-12).

The admission criteria vary according to subjects and institutions. The more

demanding subjects and prestigious institutions prefer to more competent students

who have secured highest marks in their last examination. The higher secondary

education is exclusively based on the matriculation performances. Beside the

students’ resources, students who secure high scores at matric level have the

opportunity to enroll in a more demanding and prestigious institutions for higher

secondary education. Students have the choice to apply in a desired field to more than

one institution and to different departments within the same institution for their future

career concentration.

1.5 Significance of the Study

The study investigated the determinants of career decision-making of higher

secondary level students in Karachi. In Pakistan after completion of high secondary

school education students must to choose a field of study for their further education

which will predict that what career rout a student will enter in future. In the country

bifurcation in education starts from secondary education; students have two options

for their further education i.e. Science and Arts groups. After completion of secondary

education students must to make a distinction in the choice of further education; in

Science group pre-medical and pre-engineering; General group including Social

Sciences, Humanities and Arts; and Commerce group. Although, within the university

education multiple fields of study options exist differing in difficulty and length but

the post-secondary education choice is the first step toward the access to university

education.

Researchers have also view the educational decision of students like the consumer

decision-making process. As consumers make a decision after passing number of

stages and reach to a final decision (Hodkinson and Sparkes, 1997). A large stream of

literature is available on the career decision-making process of students; how students

give preference to one career rout over other and what determinants either restrict or

ease opportunities to entry into different career routs (Germeijs and Verschueren,

2006; Briggs, 2006; and Goyette and Mullan, 2006).

In the context of Pakistan, there is almost total absence of attention in both policy and

research literature that how students made their career decision at postsecondary level.

We know very little that how students enter into different fields of study at

postsecondary level and what factors influence the career decision of students. It is

very important to know why certain types of students choose particular fields of study

for their future concentration than other. This study examines the determinants of

career decision-making of higher secondary level students, with emphasis on that does

parental education plays any role in career decision-making of students? To what

extent parental income influences the students’ career decision-making? Does

parental occupational background characteristics exert any effect on career decision-

making of students? To what extent family background influences the career decision-

making of students? What role peer group plays in career decision-making of

students? Is gender differences exist in students’ career decision-making? Do

psychological factors determine students’ choices? To what extent economic factors

influence the career decision-making process of students? The study hypothesized that

parental education, parental income, parental occupational background

characteristics, family background, peer group, gender differences, psychological

factors influences and economic factors influences can be one of those determinants

of career decision-making of students. Moreover, since no such study has been carried

out in Pakistan, therefore, there is a strong need to conduct a study on the issue and

assert the relationship between background variables and career decision-making of

students. The study will contribute to bridge the gap in sociological research.

1.6 Objectives of the Study

The study has both the general and specific objectives, under the study it was

attempted to find out the determinants that participate higher secondary level students

in their career decision-making. Following are the specific and broader objectives of

the study;

1.6.1 General Objective

1.7.1To find out the determinants of career decision-making among higher

secondary level students of Karachi.

1.6.2 Specific Objectives

1.6.2.1 To find out the parental education background effect on career

decision-making.

1.6.2.2 To examine the influence of parental income in career decision-making

1.6.2.3 To examine the role of family background in career decision-making.

1.6.2.4 To find out the parental occupational background characteristics

influences on career decision-making.

1.6.2.5 To examine the role of peer group in career decision-making.

1.6.2.6 To find out relationship between gender differences and career

decision-making.

1.6.2.7 To find out the role of economic factors influences in career decision-

making

1.6.2.8 To examine the role of psychological factors influences in career

decision-making

1.7 Hypothesis of the Study

The current study is focused on the following hypotheses;

1.7.1 Parental education is likely to influence the career decision-making of

students.

1.7.2 Parental income is associated with students’ career decision-making of

students.

1.7.3 There is an association between family background and students’ career

decision of students.

1.7.4 Parental occupational background characteristics are likely to influence

the career decision-making of students.

1.7.5 Peer group is likely to influence the career decision of students.

1.7.6 Gender differences are likely to influence the career decision of students.

1.7.7 Psychological factors influences are likely to be related to students’

career decision-making.

1.7.8 Economic factors influences are associated with students’ career

decision-making

1.8 Variable of the Study

The building blocks for hypothesis is variables. In the current study both the

dependent and independent variables are defined. Dependent variable i.e. career

decision-making has four values (pre-medical, pre-engineering, general group and

commerce).

1.8.1 Independent Variable

Parental Education

Parental Income

Family Background

Parental Occupation

Economic Factors Influences

Psychological Factors Influences

Peer Group

Gender Differences

1.8.2 Dependent Variable

Career decision-making

1.9 Key Concepts

The following concepts are been used in the study. Researcher has operationalized

these concepts accordingly and used in current dissertation in same context.

1.9.1 Career Decision-making

In the current study career decision-making refers to the process in which students

goes through to different career options and give preference to one career option over

other or choose the most appropriate career route for their future at higher secondary

level. In the current study career decision was measured in four domain i.e. per-

medial, pre-engineering, general group and commerce.

1.9.2 Determinants

The potential forces that influences students’ intention to choose one field of study

for their future in the available options. The term determinant is used in thesis for the

social, economic and psychological factors influences in students’ career decision-

making process.

1.9.3 Family Background Influences

The term family background influences refer in the study to the different familial

influences that shape and frame the career rout selection process of students.


Parental education has been used in the study as the highest level of education

completed either by both parents or by father/mother. For the data collection purpose

the researcher has divided educational level in five main categories; elementary level

education, secondary level education, college level education, university level

education and vocational education.

1.9.5 Parental Income

The term parental income was operationalized in the thesis as the father’s and

mother’s monthly income or earnings. Parental income was categorized in five

category and students were asked to encircle the average income of their parent(s).

1.9.6 Parental Occupation

Parental occupation refers to the father and mother participation in the labor force in

a particular occupation. In the current thesis International Standard Classification of

Occupation (2010) were used to capture the parental occupational background. The

scale has 10 major occupational groups, each group is further divided in sub-

categories.

1.9.7 Parental Occupational Background Characteristics

The term parental occupational background characteristics has been used in the study

as the different attributes of parental occupation and its influences on students

intention to give preferences to one career option over other.

1.9.8 Peer Group

Peer group refers to the collection of friends who like themselves in many ways and

have something in common and similar. In the current study peer group refers to the

students close friends at home, in neighborhood, at work place and at school and

college level.

1.9.9 Gender Differences

In the thesis gender refers to the socially constructed identity of male and female

students that differentiates them in their expected roles and responsibilities which

resultantly influences their life choices including career selection process at post-

secondary level.

1.9.10 Psychological Determinants Influences

The term psychological factors influences refer to the different psychological

characteristics influences that are associated with students’ career decision-making.

1.9.11 Economic Factors Influences

The term economic factors influences refers in the thesis to the different economic

influences that precipitate students in their career selection process at higher

secondary level.

CHAPTER 2

THEORITICAL BACKGROUND AND REVIEW OF LITRATURE

This chapter includes the brief description of the contesting theories of career

decision-making and a detail review of the existing literature regarding the family

backgrounds influences, parental education, parental occupational background

characteristics, parental income, peer group influences, gender differences,

psychological and economic factors influences.

2.1 Theoretical Background

Theoretical framework is one of the important pillars of research process that provides

insight to researcher about the phenomena under investigation. According to Creswell

(1994:87-88) theory is a systemic body of knowledge based on a set of assumptions

or statements to explain a phenomenon. Sociological theories are the outcomes of

research work conducted by many researchers over the years. These theories provide

us basis for understanding of contemporary society and prevailing patterns that exist

in society. Maxwell (2005:123) argues that in research process the theoretical

framework serves two major objectives; first one, is to show that how phenomenon

under investigation is fit into what is already known; second is to show that how the

research work undertaken will make contribution or fill the gap in the area under

investigation. In this chapter a brief presentation of contemporary contesting theories

are in order on career decision-making process. There are many theories which do

explain the career decision-making of students, for instance, in psychological theories

the emphasis is on the personal cognitive ability, personality or environment. In

economic theories the prospective labor market participation opportunities and

economic returns to education are main ideas behind explaining the students’ career

decision-making process. In the current dissertation three related theories have been

discussed i.e. Rational Choice Theory, Social Reproduction Theory and Life Course

Theory. All these theories have roots in sociology and extensively been applied in

many research studies to explain the career decision-making from sociological

perspective.

2.2.1 Rational Choice Theory

Rational choice theory views decisions in the social world are purposive and social

actors as being rational and or as having intentionality; that individuals have some

ends or goals toward which their actions are aimed. In explaining the individuals’

action the rational choice theorists give importance to the fact that both the individuals

goals and actions are shaped by the individuals’ preferences and that actors know for

certain that what consequences of their action will be. The underlying assumption is

that individuals choose the best consequences in term of their actions in a situation

with different characteristics under social structure that offer both the constraints and

opportunities (Elster, 1979:68; and Pescosolido, 1992:1100).

According to Coleman (1990) individual evaluate the pros and cons of the expected

outcomes on the basis of relevant information in the light of their preferences. In the

individual actions two important constraints have major role to play in shaping the

individuals decision i.e. the scarcity of resources available to individual and social

institutions. Individuals have different resources and as well differential access to

other resources. For those who have ample of resources, the achievement of desired

goals may be relatively easy. However, for those who have either limited or no access

to such resources the achievement of end may be very difficult or impossible. The

social institutions may also affect the action of individuals and place constraints

throughout life course. Such constraints are manifested through school and their rules,

the policy of employing organization’s and the law of society. These all social

institutions serve to restrict choices available to individuals which directly affect the

expected outcomes of the actions. These social institutions provide both positive and

negative sanctions on individuals’ actions that encourage certain actions, while

discouraging others.

The sociological rational choice theory is the hybrid between sociological and

economic theories. They argued that students are rational decision makers and their

educational decisions are based on the notion to maximize the total expected returns

to education. Two major axioms are borrowed from economic and sociological

theories. From economic the concept of rationality was adopted to explain the

decision-making process and views individuals as rational decision makers who

choose the best means to for a chosen means, while the sociological concept of social

context was adopted to describe the decision-making of individuals and argue that

educational decisions are always embedded in the social context of the decision

makers (Elster, 1979:68). According to Jaeger (2007:454) the new sociological

rational choice theory on education has emerged in 1990s which is based on three

major assumptions that students derive utility from their educational decisions;

students are capable to make informed decision which is totally rational, forward

looking for the expected returns for these decisions; on the basis of available

information students assign subjective probabilities to their decisions and make their

decisions according to these subjective probabilities. The educational decision of

students based on the assumption to maximize the total expected utility to their

education. The theory conceptualized the economic returns of educational decision-

making as the labor market opportunities and earnings return. In addition to economic

utility educational decisions also generate social returns in the form of preserving

existing social network, intergenerational maintenance of family social status and

social recognition from peers and significant others (Hecter, 1994; and Breen and

Goldthrope, 1997).

Some sociologists view that educational returns are heterogeneous in the sense that

different individuals put different weights on educational returns. According to

Morgan (2005:108) economic returns to education is vary by gender and race. The

Jaeger (2007:474) rational choice theoretical model also assumed students as rational

decision makers. The model hypothesized that students educational decisions are

based on an attempt to maximize the total expected economic and social returns from

their decisions. His model found that social and economic returns have independent

and significant effects on students’ secondary level educational decision-making.

Some skeptical views also arises from sociologists on rational choice theory basic

assumption of expected outcomes utility of individual actions. They view that rational

choice theory has lack of realism in explaining the decision-making process of

individuals. The arguments they presented in this context are that individual often act

as impulsively, emotionally and on merely on the basis of habit. They also criticized

that rational choice theory focus on social outcomes rather than individual (Hecter and

Kanazawa, 1997:192). The critics have also pointed out the forward looking

assumption of decision-making and contended that it cognitively too demanding

(Petersen, 1994). According to Macy (1993) individuals are sometimes backward

looking and make their decisions on the basis of their past experiences. Heckathorn

(1996) argues that individuals are sideway looking and the culture milieu also limited

the decision choices for social actors.

2.2.2 Social Reproduction Theory

Social reproduction theory emerged as a major theoretical perspective in 1960s, and

remained one of the dominant theoretical perspective in sociology. Social

reproduction theory basses on the work of European social theorists such as Marxist,

Herbmas and Bourdieu. Social reproduction theory described a set of social

stratification mechanisms which exists and operates in the current modern society

through the educational and other institutions which strongly reproduce the

intergenerational continuation of class positions. The social reproduction theory paid

abundant attention to the structure process and the manner in which the human actions

are reproduces in institutional forms rather than in individual level (Bourdieu and

Passeron 1990:139). The theory holds that how children belongs from different

backgrounds received different kind of education which prepares them for their future

role in social class structure order (Furlong, 2009:14). The theory of reproduction is

based on the concept of ‘capital’. Social reproduction theory is heavily influenced by

the Bourdieu concepts of social and cultural capital. Bourdieu was the only theorist

who correlated the relationship of cultural and social capital with the educational

system. The work of Bourdieu provides a greater conceptual explanatory power to the

educational choices in the current modern world and described that individuals’ class

positions provides differentially access to these resources which may create different

patterns of privilege and inequality.

According to Bourdieu’s (1984:128-129) cultural capital concept, which is widely

known in the sociological literature as cultural reproduction theory, he argues that

explanation for social class inequalities in educational attainment lies in the social

distribution of cultural capital. Explaining the cultural capital Bourdieu views it as the

familiarity with or socialization into dominant culture in a society i.e. ‘highbrow’

codes and tastes. Bourdieu claimed that cultural educational resources are meaningful

for attaining position in the social hierarchies. The theory holds that family social

origin plays major role in the children educational attainment, for instance, children

of privileged parents who are rich and socialized in the dominant culture capital help

their children do well in school. Children who are not familiar with this kind of

socialization will experienced school as hostile place and face difficulties to attaint

education. Bourdieu drew heavily on examples from the educational system at both

compulsory and post-compulsory educational level and assumed that educational

institutions tend to reinforce social inequalities by failing to account the different

cultural capital possess by the students and the students differing level of familiarity

with dominant culture. Consequently, success of working class students in such

educational system may be low because of either less access to dominant culture

capital or familiarity with (Werfhorst et al. 2003:44).

In explaining the process through which prevailing structural inequalities are

correlated through to the individual level, Bourdieu developed the concept of

‘habitus’. According to Bourdieu ‘habitus’ is mental and cognitive structure through

which people deal with social world (1977:81-95). It is a set of internalizes schemes

through which individual perceives, understands and evaluates the social world. The

nature of the ‘habitus’ varies by one’s long term occupied position in the social world.

The habitus enables the individual to make sense out of the social world. For example,

Bourdieu contends that habitus only suggests what people should think and what they

should choose to do. Habitus provides guideline by which people deliberately engage

in the decision-making process. Consequently, through the ‘habitus’ or the actor

subjective expectations of objective probabilities the structure of culture and society

is reproduced. This conceptual framework does explain and holds that the young

people engagement in the educational system depend on the extent to which young

people habitus fits with the educational system and will have the success to internalize

the values of that educational system.

The Hodkinson and Sparkes (1997:34) model of ‘careership’ is also based on the

concept of ‘habitus’ and the opportunity structure what he termed as ‘horizon for

action’. By horizon for action they mean that a situation within which actions are taken

and decisions are made. Both the habitus and the opportunity structure are shaping the

horizon of individual. They view that horizon for action both limits and enables our

view of the world and the choices we made in the social world. Empirical

investigations have proved that the parental cultural capital has relationship with

children educational attainment and field of study choices (Ganzeboom et al.

1990:87).

The first contemporary analysis of social capital was presented by Bourdieu and he

defines the term as the ‘aggregate of actual or potential resources which are linked to

the possession of a durable network or more or less institutionalized relationships of

mutual acquaintance or recognition. According to Bourdieu (1985:249) theoretical

explanation that social relationships provide basis of membership in the group and

opportunity for resources that are available to the members. Bourdieu claimed that

social capital has strong correlation with educational attainment and choices of

students, for instance, students’ belonging from families who are rich in the social

capital in terms of wider social network and have access to information about the

current educational patterns and labor market opportunities do well as compare to

those students who lack such social capitals. The middle class parents consciously

develop a wider social network with more social resources families or communities

that may provide opportunities for their children to benefits from familial wider social

network which in turn increases their children success in educational fields.

Bourdieu (1986:254) views the economic capital as the root of all other form of

capitals. Economic capital is more than financial means, which is a form of strategic

investment in the educational attainment of the children. He describes that more

economic capital parents are able to afford the opportunity cost to extend the

educational career of their children by investing more time and efforts in child

education. The economic capital demonstrates success to outside world and

abundance of economic capital group express their financial success by consuming

luxury and durable life, for instance, possess valuable and expensive goods to show

his success to outside world. According to Bourdieu the field of study is a key to

determine the materialistic preferences. Bourdieu (1998:34) claims that all three forms

of capitals are mutually correlated and converted from one form to other.

2.2.3 Life Course Theory

Life course perspective is emerged as the most influential theoretical perspective in

sociology. The term life cycle, life span and life course are used in the literature

identically and interchangeably. Life course theory tries to see the totality of

individual life in several contexts. Theory has two major dimensions; the micro-level

that focusing on individual level, for instance, the biography of individual and macro-

level focusing at the social institutions level that provides environment to individuals

to fashion their life (Elder, Johnson and Crosone, 2003:4). The Theory aims to explore

the association between ‘structure’ i.e. social forces or institutions and ‘agency’

individual level and their influences on life choices and decisions. The life course

perspective sees the social ties as the form of control and constrains on the choices

and decisions of individuals. The theoretical focus of life perspective is the life course

phases, transitions, trajectories, sequences of social roles, internal and external turning

points that generate changes in the individual life (Elder, 1985:17-18). They argue

that socialization occurs thorough network of such relationships. Elder was one of the

early theorists who developed his model of life course perspective and argues that

historical events are the underling forces to change the social trajectories of families,

education and work that in turn influence both the different phases of development

and behavior. According to Elder structural and cultural constraints and opportunities

shape the individual life choices (Elder, 1998:2). Krecker and O’Rand (1990:241-244)

views that sequential orders of events exist in the life course perspective where one

event follow the other in path like trajectories and the important life events are

resembled as the turning points.

Elder identifies four basic concepts of life course perspective i.e. historical context,

timing, linked lives and agency. He refers the historical context as the historical events

that effect development for people in a birth cohort because individual belongs from

particular birth cohort experiences different important moments in his life course.

According to Elder, social timing enables us to see that how different birth cohort

were influenced differently in their life experiences. Linked lives refers to the

adaptation of people who are important in our lives and the individual success to cope

with situation within available resources. Agency refers to the individual ability to

make choices within the structural and cultural constraints for possible outcomes

(Elder, 1998:3-4).

According to life course perspective individual experiences different transitions in his

life course in the form of changes in the roles and statuses. Individual’s life is full of

such transitions, for instance, starting school, maturation period, leaving school,

getting job, leaving home and retirement. Transition can happen either in predictable

manner or unpredictable manner. Because some events are expected to happen, for

example, transition from lower grade to upper grade education, while other are out of

order or off time events, for instance, birth before marriage. Each transition faced by

the individual changes his roles and statuses because it is conceived as a period of

change and growth and assumed to exert both kind of influences on individual choices

and actions. Some transitions become turning points or key life experiences in life

(Elder, 1985:35). Turning points are those events that change the course of life for

individual and lead towards ever lasting effects. Some of theorists call it ‘epiphanies’

Denzin, (1989), Antikainen, et al., (1996) termed it life changing learning events and

Alheit (1994) viewed it biography discontinuity, all of theorists hold that career

decision is made within a turning points because every individual faces different

turning points in their life courses some of these turning points either get life

trajectories out of track or back on track. According to Elder (1995:6) competent

people have the ability to make choices among available alternatives that can change

or shape their life. The individual choices of education, family, health and work are

constrains by the physical and social structure of choices.

2.2.4 Social Learning Theory

Social learning theory has it’s roots in psychology and was greatly influenced by the

work of Albert Bandura. The theory attempts to explain the socialization and its

effects on the development of the self. The theory maintained that the formation of

one’s identity to be a learned response to social stimuli. Individual’s behaviors are the

product of the uncountable numbers of learning experiences through encounters with

people, institutions and events in a person’s particular environment. According to

Bandura (1977) the individual behaviors are the product of environment and cognitive

process. He further suggested that child had develop gender identity and gender role

through a process called socialization. In this process, the socializing agents such as

parents and peer reinforce both male and female child to adopt their behaviors.

Therefore, male child internalized masculine characteristics while girls child learn

feminine identification. This early socialization process plays an important role to

shape child behaviors including his/her life choices.

The social learning theory of career decision-making was presented by Krumboltz

(1979) and contended that four factors that influence individuals’ career decision-

making: genetic endowment and special abilities, environmental conditions and

events, instrumental and associative learning experiences and task approach skills.

These factors are meant to help explain the origins of career choices and are not

independent of each other because they interact in various ways. According to him,

genetic endowment and special abilities such as gender, race and physical appearance

as the first factor thought to influence career decision-making. The environmental

conditions and events including family traditions, geographical location, cultural,

economic forces, and political influences are described as important in shaping one’s

career choices. These are outside of the individual control and their influences can be

both planned and unplanned. Each individual has some unique circumstances

surrounding instrumental learning experiences. These experiences are characterized

by an individual’s acts producing certain consequences and unique from associative

learning experiences in that they involve personal volition on the part of the learner.

For young people, this type of experiences can have lasting effects and can influence

career decision-making to a significant extent. Task approach skills include individual

work habits, emotional and cognitive responses and problem-solving skills.

As a result of the interaction of these four factors, the social learning theory of career

decision-making suggested that these factors influence belief about self in terms of

self-observation generalizations, task approach skills and actions. The theory

maintained that different combinations of these factors interact over time to produce

different decisions. An educational and occupational preferences, for example, is

considered to be the result of an evaluative self-observation based on the learning of

experiences pertinent to a career task and me be modified by further environment

events and social learning.

2.3 REVIEW OF LITERATURE

Review of literature is a systemic process of identifying all the relevant published

material on the topic under investigation (Gash, 2000:1). Ridley (2008:2) argues that

review of literature serves as a driving force that enables the researcher to identify the

gaps in the existing literature and attempt to fill the gap. In this chapter an attempt has

been made to present the existing literature on the topic of determinants of career

decision-making that reflected the empirical investigations conducted in many parts

of the world.


The family background serves as a major explanatory framework in the understanding

of students’ career trajectories selection process. Sociological explanations for the

association of family background and offspring educational choices refer to the

importance of socialization at home and parental resources i.e. social, cultural and

economic capitals. The literature which does exist shows differences among students

in educational choices belong from different family backgrounds. A comparative

study conducted by Schnabel et al., (2002) among the 7th to 12th grade students in US

and grade 7th to 10th students in Germany shows a strong family background effect in

students’ educational choices in both countries. The study found that family

background effect is more pronounced when career decision is made in early school

age. At the younger age students have less exposure to different career pathways and

remain more dependent on their parents. According to Conley (2001) parental assets

have strong nonlinear effects on offspring educational attainment and transition from

secondary to postsecondary level. A multiyear sample was collected from the national

representative data of Panel Study of Income Dynamics (PSID) in US. The study

demonstrates that parents may use their resources either to invest in offspring

education for human capital formation or transmit the intergenerational of class status.

It is tended that parental assets increase the years of schooling for their children.

According to Mahler and Winkelmann (2004) family structure has strong effect on

children educational attainment and field of study choices at secondary level

education. A large data set of German Socio-economic Panel Study (GSOEP) was

used for the study. They reported that educational attainment of children depends on

the family structure and resources. The single parent families adversely effected the

child educational choices and it is contended that single mother families restricted

students’ field of study choices in Germany. Cavanagh and Fomby (2012)

documented that family structure may play a decisive role in Math course taking

decision of high school students in US. They tended that students with low exposure

to family instability increases their probability to enrol in advance Math courses on

time than students who have high exposure to family instability and disruption.

Frequent changes in family structure is strongly correlated with low academic

performance among students.

Ermisch and Francesconi (2000) analysed the endogeneity of education on earnings

and returns to education. The role of family is examined in human capital formation;

tow theoretical models of educational choices were used i.e. individual based and

family based models. The data was drawn from British Household Panel Study which

based on the national representative sample. They contended that family environment,

educational level of mother, parents resources increased the offspring educational

attainment; parents consider the economic returns from their children education; male

child was on odds to receive more resources from their parents to attain higher

education; female students do consider the home production in their educational

attainment. The number of siblings and non-intact family have negatively associated

with educational attainment.

Similarly Goyette and Mullen (2006) used the data from National Educational

Longitudinal Survey (NELS) and Baccalaureate and Beyond Longitudinal study (B

and B), a national representative sample was drawn from 10th to 12th grades students.

They have explored the effect of students’ background characteristics and

socioeconomic status on college majors’ choices; college majors were divided into

Science and Arts and vocational fields. The multivariate analysis of the data provided

support to the assumption that family background significantly affect the college

majors’ choices; the advantageous backgrounds students have the tendency to choose

Arts and Science than vocational fields.

Goldrick-Rab (2006) argue that in postsecondary education students belong from low

socioeconomic background have less predictable career pathways than privileged

class students. Substantial differences were found in college attendance among

students belong from low and upper socioeconomic backgrounds. The study found

that delay in college enrolment, interrupted college attendance, tendency of college

transfer and two years oppose to four years schooling attendance were found among

low socioeconomic background students. Students who receive more financial

resources from their families are less likely to delay their enrolment and have less

interrupted attendance patterns.

Analysing the contextual aspects of young people career process Mohd et al., (2010)

described that contextual aspects such as family environment may determine students’

career development and planning in vocational and technical fields in Malaysia.

Students from 22 technical institutions were randomly selected to participate in the

study. They found that vocational educational choices of students have association

with student family backgrounds; the immediate relatives particularly parents have

significant influence on students’ career development and planning in vocational and

technical fields. Except from other family members father was the most influential

individual in students’ career choices process.

Karlson (2011) compared the sequential logit model (SLM), multinomial transition

model (MTM) and multinomial transition model with unobserved heterogeneity

(MTMU) on the students’ transition from secondary to postsecondary level. The data

was drawn from the Danish Longitudinal Survey of Youth (DLSY) containing

complete information of the respondent family backgrounds and individual ability.

The study focused on the effects of parental social class, parental education and

individual ability on available track choices of education. Except the other two models

the multinomial transition model with unobserved heterogeneity (MTMU) was the

most appropriate to explain and predict the students’ choices in diversified educational

system of Denmark. The MTMU model exhibits that social class effects are large for

academic track choices than for vocational transition but this transition are more

pronounced in the postsecondary education.

Empirical evidence was provided by Stocke (2007) to the impact of social class on

educational decisions of students. He argued that in German educational system

students’ decision largely affected by the students’ background characteristics. Breen-

Goldthorpe educational attainment model was used to assert relationships between

class inequalities and educational choices among students. In German educational

system three options available to the students’ i.e. lower secondary, intermediate

secondary, and upper secondary level. Class heterogeneity was evidently depicted

from the analysis. The study found that parents’ class positions were strongly

associated with the students’ educational success and attainment. For instance,

students from the upper service class were on the odd to choose and complete the

upper secondary track education than the working, manual and routine class students.

Parents were found very concerned about the status maintenance (SM) motive and

equally motivated to invest more in child education for achieving similar family social

status.

Another study conducted by Vryonides and Gouvias (2012) showed that parental

aspirations were influential on offspring educational and occupation prospects. Data

collected from 700 parents of primary school students in Greece shows patterns of

parents’ aspirations and expectations from their children. On the basis of the parents

job they were classified on different social classes. The findings show that parental

social class has statistically significant effects on children anticipated educational and

occupational trajectories. The more the parents have social and cultural capital the

higher their educational aspirations from their children and have expectations for

prestigious job in the future. Social class has been found a defining element in

explaining the parents’ aspirations and expectations. The high parental social class

was closely associated with parental readiness to mobilize their capital to facilitate

their children to achieve better employment opportunities. High social class parents

were more satisfied from their children educational performance than the lower class

children. Realistic offspring educational aspirations were found among parents belong

from high social class.

Similar line study conducted by Bodovski (2010) which lends support to the

assumption that social class, racial background and parenting practices predicated the

parental attitudes and behaviours which differently affect the overall educational

attainment of children. The study mainly address two key questions: to find

relationships between parental socioeconomic status and parental educational

aspirations and to what extent the parental aspirations are linked with educational

achievements of White and African American students. Data was collected from US

elementary level students’ parents and teachers, a detail information about students

were collected. The study revealed that patterns of racial differences were exist in

parental practices; comparatively White students have received more social and

cultural capital at home than their counterparts. Parents’ high socioeconomic

backgrounds increase the parental educational expectations from their children. The

study further explained that high socioeconomic background and high educational

aspirations were positively associated with educational achievements of students.

Shah et al., (2010) conducted a qualitative study on the educational achievements of

middle class working British Pakistani families and indicated that ethnic capital plays

central role in students’ educational attainment and career trajectories selection

process. They argued that parents see higher education as a means to achieve high

social mobility therefore, they mobilize their economic and social capitals to support

and encourage their children to navigate in more prestigious fields. British Pakistani

families put high weight on attainment of higher education and they have high career

aspirations for their children.

Howard et al., (2009) made in important contribution in this regard and argued that

family involvement and support have significant linked with students’ distress,

educational outcomes and career decidedness. The data was collected from 588

middle schools in Italy, the study found that family support is positively associated

with academic grade and career decidedness among students. Gender dichotomy and

geographical differences in effects were evidently depicted from the study. In

Malaysian students Palos and Drobot (2010) study also find that children who

received psychological support from their parents in terms of either receiving

encouragement and support for their decision or parents showed their interest in child

activities are more personally and professionally successful than children who

received less psychological support from their parents. Differences were found

between parental involvements, study shows the intensive involvement of mother in

child career development than father. Parental restrictiveness and control were

negatively associated with children’s’ openness and career guidance.

Salami (2004) investigated the seven personal-social and psychological variables; sex,

sex role stereotype, age, socioeconomic status, self-efficacy, family involvement and

career aspirations to predict the secondary schools students career choices in Nigeria.

Sample of 260 students were collected from co-educational middle secondary schools

in Nigeria. Except from other variables, he found that family involvement may

determine the career pathways of students’. It is documented that parents have

statistically significant effect on their children to pursue their career in a more

prestigious, financial rewarding and contemporary demanding fields. High family

involvement is linked with students’ high confidence and aspirations level that

increases their career orientation in a particular field.

Parental belief may be one of the strong determinants of children enrolment in Science

related subjects (Tenenbaum and Leaper, 2003). Parental gender stereotyping is

associated with parenting practices, subsequently they treated male and female

children differently which effects the male and female children self-efficacy and

interest in science related subjects. Parental high gendered belief was linked with girls

less enrolment in Science and Math subjects which shows the gender dichotomy in

choice of career selection among female students. The family background review

shows that family not only plays an important role in early socialization process but

also provides a platform for a wider exposure and channelized children to available

opportunities in the contemporary world.

2.3.2 Parental Education Influences

The literature which does exist focuses on the similarity of parental educational level

and children educational attainment and choices. Werfhorst et al., (2001) described

the influences of parental characteristics on field of study choices among Dutch

students. They used data from the Dutch Family Surveys and focused on three

dimensions of parental resources i.e. intergenerational transmission of field of study,

cultural and economic capital and parental socioeconomic background. The study

shows that independent of other key explanations the field of study choices are

transmitted from one generation to the next and children are on the odds to enter into

the same fields of study of their parents. In some fields’ intergenerational preferences

are stronger than other fields. For instance, father holding an agriculture related

educational background increases the chances of their children almost five times high

to choose the same fields for their future. The intergenerational similarity of field of

choices were high in the field of General education, Agriculture, Economics,

Education and Law fields; low ratio of similarities were found in Culture and caring

fields.

Consistence results were shown by the study conducted by Dustmann (2004) and

concluded that parental backgrounds are better predicted the educational choices of

their children. Analysed a large data set of German Socioeconomic Panel Household

Survey; where households are surveyed in successive years. The study underline the

assumption of parental educational backgrounds effects on preferences in secondary

educational track choices. The central points of his study were to test students’

transition from secondary to post-secondary education; parental educational

characteristics effects on secondary school choices; changes in secondary educational

choices over time; association between educational achievement and wages and

parental backgrounds effects on earnings of students. He argued that secondary

educational choices are significantly associated with later educational choices and

tends different effects for male and female students. Apparently independent from

other explanations the parents schooling and post schooling education are the strong

determinants of children secondary school track choices. The study also demonstrates

that parental backgrounds predict the individual differences in the attainment of high

school education, male and female children are differently influenced on their

educational choices. Educational achievements are closely associated with anticipated

wages of male students, while this effect was insignificant for female students.

De Graaf et al., (2000) attempted to empirically examine the influences of parental

cultural resources including cognitive and linguistics skills effects on offspring

educational attainment and choices. Based on the Netherlands Family Survey (1992)

data they indicated that parental education has increased the probability of children

educational attainment and success; parents have transmitted their linguistic and

cognitive skills to their children which consequently benefited them in educational

attainment. Similar findings revealed from Huang (2013) study conducted on the

intergenerational transmission of education between two cohort of 1984 and 19994.

A national representative sample of 13 and 20 years age children was collected from

the US panel survey. The study underlines the assumption that intergenerational

transmission of education persists between the two cohort and documented that over

the years the pattern of intergenerational transmission has been changed; parental

education particularly mothers’ college level education increases the probability of

their child college entry than children whose mother could not attain college level

education.

Ermisch and Francesconi (2001) provided theoretical explanation of family

backgrounds characteristics effects including family structure, parents’ education and

income on children educational attainment in Britain. Data was derived from the

British Household Panel Study (1991-1997), the study indicated that educated parents

put more weight on offspring educational attainment and the level of parental

education increases the probability for their children to attain similar or more

education than their parents. For instance, mother than father, holding A-level or more

education increases the chances for the offspring to attain A-level or above education.

Whereas father’s O-level or above qualification increases an average probability for

the adults to gain similar or more education than their father. The educational level of

mother was significantly associated with children educational attainment.

Davis et al., (2002) provided a theoretical implication of Relative Risk Aversion

(RRA) theory by analysing the career choices of young people at different stages in

the education system of Denmark. They argue that aside from the ability, family

background plays unobserved role in this transition process. The empirical analysis

has shown that parents’ education have nonlinear effect on after 9th grade choices and

children with more educated parents have more probability to continue their education

for a longer time but this effect weakened after lower to upper class transition.

Children have the propensity to minimize the risk and maximize the probability of

reach to the educational level of their parents to maintain the social class of their

parents.

Sen and Clemente (2010) estimated the correlation of intergenerational transmission

of education among the three cohort 1986, 1994 and 2001 from the data of General

Social Survey of Canada. They found a positive correlation between parent’s years of

schooling and child’s educational attainment. Father’s secondary and postsecondary

education is positively correlated with the child’s similar or upper level educational

attainments. Used the Taiwanese household registration data set Tsou et al., (2012)

provide a causal explanation to the biological and adoptive parents’ years of schooling

on child’s education. They found that effects of both biological and adoptive parents’

years of schooling has statistically significant effects on child’s educational

attainment. According to Daouli et al., (2010) the influence of parental education is

weakened overtime in Greece. Examined the data of Greek Household Budget Survey

and focused on the 16-17 years old daughters. They contended that mother educational

background has statistically significant effects on daughter educational attainment and

poor maternal educational background are associated with poor daughter educational

outcomes.

In other study conducted by Goyette (2008) revealed that over the years the influence

of parents educational background have been decreased and misaligned with students

educational plan. Analysed the data from the National Longitudinal Educational Study

(NLES) of 1980, 1990 and 2000, a sample of 10th grade students’ were drawn from

the data set. The study attempted to establish relationship between parental

background characteristics on students overall occupational and educational plan. The

study shows a shift in students’ occupational ambitions and educational plan over the

years and the social background particularly the parents’ educational background

effects weakened over the years. Due to the emerging of new labour market

opportunities and changes in educational institutions students occupational ambitions

were changed. It is depicted from the study that students were more inclined towards

professional fields which consequently affect their overall educational plan and

choices.

According to Martin (2012) co-residential parents’ may play an important role in the

process of transmission of resources to children for human capital development. Used

the data from US National Educational Longitudinal Study the study documented that

intergenerational transmission of educational and occupational capital varies by

family structure. It is contended that highly educated single mother families were less

likely to transmit their educational capital to their children than biological parents.

The study found that highly educated biological parents were more likely to transmit

their resources to their children. The years of schooling of biological parents increases

the likelihood of their children to attend postsecondary education and perform better

than those students who have lived with single mother parents families.

Plug and Vijverberg (2003) used the mobility model of human capital to determine

that how family ability and income are genetically transmitted to children. The data

derived from the panel data of Wisconsin Longitudinal Survey, it was hypothesized

that differences exist in biological and adopted children educational success and

parental ability may predict the educational attainment for their children. High

educated parents’ children were more likely to attend upper level education than their

counterparts. The study found that parental education increases the chances of

educational attainment of biological children more than adopted children.

Tieben and Wolbers (2009) used the Breen and Jonsson Dutch educational transition

model and linked the conditional and unconditional effects of socioeconomic

backgrounds on the overall transitions of students to postsecondary education choices.

Four consecutive waves of Family Survey Dutch Population (FSDP) 1992, 1998, 2000

and 2003 were studied including secondary level respondents who have not obtained

the secondary level education during the time of interview. The study shows that aside

from the previous educational track record the socioeconomic backgrounds have

significant effects on the educational transitions. The study underlines the assumption

that parental educational background has a robust effects on students’ educational

transition and does explain the inequality in educational choices among students. It

was also reported that parental occupation has lesser effect on the students’

educational transition.

A similar study conducted by Van Lenger et al., (2008) in Netherland shows that after

controlling of other variables the effects of parental education is significant on Math

and Science course taking decision among students at upper secondary level. A large

Netherland national representative data set of secondary students’ educational profile

was used to analyse the role of ascribed characteristics on the students’ choices of

Math and Science subjects’ selection in upper secondary level. The results of

multilevel analysis revealed that the effects of parental education should not be

trivialized and children belong from highly educated parents are on the odds to choose

Math and Science fields than students who have less educated parents.

Karlsen (2001) concluded that in Norway patterns of occupational preferences were

persistent in students’ occupational choices. Randomly data was collected from upper

secondary level of 902 students from 19 schools. Two perspectives were analysed i.e.

structural reproduction and individual freedom. Tangible evidences were presented

that socioeconomic background differentiated students in their occupational

preferences. Low socioeconomic students put less weigh on self-realization and they

avoided to prefer high prestigious occupation in the future. The study also

demonstrated that parental education may better predict the students anticipated

occupational preferences, for instance, father’s higher educational background

increases the probability for female students to choose humanity in their upper

secondary level, low parental education increases the probability for female students

to enter into caring related subjects. Students’ chances of choosing vocational fields

for their future decreases as the father’s education level increases.

Explaining the intergenerational transmission of human capital Black et al., (2003)

documented that the years of parental education increases the chances for offspring to

attain similar or more education in Norway. The study found causal relationship

between parental years of education on both boys and girls children. The study also

hypothesized that compulsory educational reforms have positive effects on parental

education which consequently increases the chances of education for children.

Ayalon and Yogev (2005) found that disadvantaged groups varies in their field of

study choices in the diversified education system of Israel. They examined the socio-

demographic characteristics of 24 colleges and 6 universities students and contended

that due to the expansion of higher education patterns of inequality exist in the

opportunity available to the students in the seven major fields at college and university

level. The findings reveal that on the one hand college increases the probability of less

advantaged group to enrol in less lucrative and lower prestigious field of study, for

instance, in the field of education. On the other hand college also increases the

opportunity for privileged students to enrol in lucrative and prestigious fields.

Consequently, less advantaged group receives less economic return, while advantaged

students receive more from their education. Among the socio-demographic

characteristics parental education exerts significant and vary effects across all fields

of study. The higher parental education increases the probability of students’

enrolment of college versus university. On the basis of the above review, it is

concluded that parental years of schooling play a vital role in students anticipated

career choices. Students are on the odds to attain similar or more education as their

parents. However, unlike mother, father’s years of schooling are strongly linked with

students’ further education and career progression.


Parents’ occupational background have long been studied and remained one of the

dominant areas of life courses in students’ lives. Extensive inquiries have been made

by various researchers from many fields to explore parental occupational background

characteristics influences dimensions in students’ career decision-making process.

According to Leppel et al., (2001) parental occupation determines the students’

educational selection choices. The data was drawn from the Beginning Postsecondary

Students (BPS) survey conducted by National Centre for Education Statistics (NCES).

The multinomial logit analysis of the data shows that occupational background of

father has statistically significant effect on both male and female students to choose

Sciences and Engineering as a college major. Female students were more influenced

to enter into male dominated majors if their father has high occupational status.

Whereas, mother occupational background was found to exert smaller effects on

students’ educational selection choices.

Oren et al., (2013) investigated the intergenerational transmission of occupation

congruence between parents and child and it is found that parents are the primary

influential individuals on child’s occupational selection process. A sample of 260

undergraduate students were collected from Ariel University and their planned

occupational preferences were investigated by using the Theory of Planned

Behaviour. The regression analysis of the study showed that perceptions of social

pressure to choose the same profession of parents for the career success may better

predicted the intergenerational transmission of occupation than personal attitudes.

A similar study conducted by Laftman (2008) in Sweden and she hypothesized that at

upper secondary level students’ decision to choose either Natural Science or

Technology program (NT) are largely depended on the parental skills. A national

representative large data set of secondary school students and their parents were used

to ascertain the relationship between students’ educational choices and parental skills.

It is revealed from the analysis that differences in pattern of choices exist among

students belong from different family backgrounds. Sex segregation effect was found

among students, for instance, the Natural Science and Technology skills of step

parents were negatively associated with aspirations of girls’ students in the same

fields, while the single mother families have found to constrain the boys’ students

educational choices to enter into Math and Science fields.

Werfhorst et al., (2003) argue that in Britain students decision of subject choices at

secondary and postsecondary level may be explained through the family background

resources i.e. social class, culture and economic. Students made their decisions

corresponding to their family background resources. A sample of 17,414 students

were drawn from the National Child Development Study in Britain. It was found that

other than ability, parental social class is positively associated with students’ career

choices. Students belonging from professional backgrounds are more inclined to

choose more prestigious field for their future. For example, manual and unskilled

backgrounds students are less likely to choose Medicine and Law subjects. Contrary

to the previous studies this study does not find any over representation of manual class

background in field of Engineering.

Korupp et al., (2002) investigated the impact of parental backgrounds characteristics

on the offspring initial labour market entry when they completed the high school

education. Two man questions were inquired in the study and empirical evidences

were presented to prove the association through testing the classical model of status

attainment of Balu and Duncan. Data drawn from Households in the Netherland

Survey 1995 (HIN 95) and Netherland Family Survey 1992-1993 (FAM 93) both the

survey collected detail career related information about male and female participants.

The study lends support to the assumption of intergenerational transmission of

occupational characteristics between parents to children; dichotomy of sex typing

influences was depicted from the findings and it is tended that impact of father’s job

characteristics are robust than mother; mother’s occupational characteristics were

found to be influential over girls first job status, while father’s job characteristics exert

statistically strong effects on both boys and girls first entry into labour market.

Loberman, and Tziner (2012) found that parents’ child relationship may affect the

offspring future occupational preferences. Data was drawn from 146 12th grade

students and 134 university level students in Israel. Two dichotomous variables were

used to explore the parental job influences on the child i.e. similarity in career choices

and parental job characteristics. They hypothesized that parents supportive

relationship with child may aspire their children to seek future occupation in the same

field as of their parents. The father’s job characteristics effect was emerged for high

school students’ perceived professional characteristics. High school students were less

likely influenced by career quality of their mother and the chances of career similarity

was comparatively very narrow. While no significant effect was found for university

level students preferred career options.

Adeleke and Okobge (2014) supported the assumption that parental professional

background variables exert statistically significant effects on students’ career

preferences. Data was collected from six hundred senior secondary school students

and their parents were selected belonging from teaching profession through multistage

sample techniques. The study found that parental professional backgrounds affected

students’ career preferences and they are more inclined to pursue their career similar

to their parents’ professional background. They also contended that other variables,

for instance, job security, financial incentives, working environment etc. of parental

professional background are largely influenced the students preferences, however,

parental gender exhibits no influences on students career.

According to Van de Werfhorst and Luijkx (2010) parental occupational sex typing

plays a major role to shape the field of study choices among offspring. The patterns

of similarities exist between parents’ occupation and student field of study choices. A

large national representative surveys data set of Netherland was used including

Households in the Netherland (HIN), Family Surveys data of Dutch Population and

the Supplementary Use of Service Research data. The findings showed that across all

social classes’ patterns of sex typing similarities in occupational preferences exist

among students. For example, mother’s occupational status was stronger for daughter

and father’s job status was influential on both son and daughter first job status.

Children of services class background are more likely to choose field of study similar

to their parents’ occupation which may help them to achieve and reach similar class

positions as of their parents.

Jackson et al., (2008) presented empirical evidences to the detail role of field of study

in social mobility in four European countries i.e. France, Germany, UK and

Netherland. A national representative data set was used for each country and four

educational level were distinguished for the study purpose. The study found that in all

countries occupations are intergenerationaly reproduced through field of study

choices but reproduction are weakened in some fields than other. For instance, in

France reproduction of occupations are weakened in Humanities, Social Sciences,

Health and caring fields, while very strong in Business, Law and Economic fields. In

Netherland a partial effects were persistent in Humanities fields, while in UK and

Germany a similar patterns of French reproduction of occupational exist at the upper

level of educational fields.

Jonsson et al., (2009) presented the implications of microclass mobility model in

Germany, US, Sweden and Japan and argued that parental occupation plays an

important role in intergenerational transmission of social, cultural and economic

resources to their children. A national representative sample for each of four countries

were collected including a detail information of parental occupation and demographic

characteristics. They divided the intergenerational reproduction in two categories i.e.

categorical form, in which parents transmitted their big class position to the children;

gradual form, in which the socioeconomic status positions of the parents are

transmitted to children. The study lends support to the persistent of microclass

reproduction pattern across four countries and tended that parents transmitted their

job specific characteristics to children and provide them an opportunities to develop

job specific attitudes, skills and facilitate them to acquire more job related trainings

through a large social network exist outside the home environment. They argued that

children of professional class are more likely to become professional as the

nonprofessional students.

Schroder et al., (2011) presented contextual explanation to adolescents’ career

intentions belong from business family backgrounds. Three dimensions of career

intention of adolescents were analysed i.e. to develop career in the family business,

start their own business or working with others as an employee. Interviews were

conducted with both parents and adolescents of 106 families in Germany. The

intergenerational transmission of occupational values transmitted from parents to

child were displayed form the analysis. It is demonstrated that parental views have

statistically positive relationship with parental career intentions. The more the parents

oriented and prepared their children for the family business succession, the more the

child will intended to join their business in the future. The study demonstrated gender

dichotomy between boys and girls intentions and tended that female girls were less

likely to enter into family business because they perceived that father’s occupation or

business are more rewarding for boys only. Girls were more inclined toward either for

employment or start their own business.

Gardner and Cortina (2006) also correlated the parental work experiences perceptions

with adolescents’ positive future occupational orientation. A sample of 415 students

of 9th to 12th grade was collected from public high school in US. The findings indicated

a high degree of correlation between parental job experiences and positive

adolescents’ future occupational orientation. The more the rewarding and self-

direction parents job characteristics the high the adolescents hopes and optimistic

view about their future. It is also tended that female seems to view the future

occupational orientation more in relation with their parents job characteristics. To sum

up the aforementioned review, it is concluded that students take their parental

occupational status as a point of reference for their preferred career routs. Parents’

occupational background characteristics provides either opportunities or refrain

students to enter into same occupation as their parents. Father’s occupational status is

more influential than mother, and students had the tendency to choose similar

occupation as their father. Resultantly, intergenerational of occupation are reported in

many studies.

2.3.4 Peer Group Influences

The importance of friends in human life courses have long been studied by researchers

and view friendship as a means of social resources. The dynamics of friendships

influences have been studied in childhood, adulthood and later stages of life and it is

found that friends’ behaviours and attitudes are remain influential throughout life

courses. The importance of friends is considerably stronger during adolescence

because in adulthood adolescents are found to be more responsive to their friends’

behaviours and attitudes. A wealth of previous literature suggested that friends are of

potential source of exerting both positive and negative influences over young people.

Gaviria and Raphael, (2001) documented that the risky behaviour of close friends

strongly determine the adolescents’ engagement in risky behaviours and this effect is

more pronounced at school level. Ali and Dwyer (2011) examined national

representative sample of 7th to 12th grade students in US and concluded that peer social

network increases the probability of adolescents to engage in risky behaviour

including sexual behaviour.

The experimental study of Eisenkopf (2010) explored that peers’ effects exist in

motivation and learning and peers improve the academic performance of their partner.

Riegle-Crumb et al., (2006) found that friends are potential source of advanced course

taking in high school across gender and adolescents Math and Science advance course

taking decisions are largely influenced by their friends. The data was drawn from

National Longitudinal Study of Adolescent Health and a national representative

sample was collected through stratified random sampling method of 7th-12th grade

students from 132 middle and high schools in US. The study revealed that friends’

characteristics exert a significant effect on student advances course taking decision.

The gender pattern of friendships have significant effects on female students’ decision

of advance course taking. For instance, high academic performing same sex friends

increases the probability for female students to take advance courses of Physics, pre-

calculus and English at 11th and 12th grade.

Similar study conducted by Crosnoe et al., (2003) revealed that friendships

composition plays an important role in structuring human life courses. A large

nationally representative sample was collected and approximately 9,223 students of

7th-12th grade students of 144 US high schools participated in the study. The study

suggests that academic oriented friends are a source of social capital; students who

have more of such resources were more protected from academic problems, for

instance, there is a less probability to disengage and lose their educational process;

high probability to remain on track and to navigate in the academic process. In less

advantaged schools the influences of academic oriented friends are more than

advantageous schools.

In other study conducted by Crosnoe et al., (2008) contended that during secondary

and post-secondary education peer group posits a strong effects on the Math course

taking decision of students. Close ties of friendships with academically oriented peers

may be potential source of anticipated trajectories selection in Math subjects. Gender

difference emerges from the study; the academic achievements of peers have strong

association with female Math course taking decision; the course mate academic

achievements are closely linked with male students’ Math course decision.

The Britain educational choices data was analysed by Thomas and Webber (2009) and

they concluded that after compulsory education at the age of 16 students’ educational

choices at a large extent shaped by their peers. Exploring the potential career

opportunities in the mind of students in their post-compulsory education the study

examined the role of family background, school and peer group effects. The results

provided evidence to peer group effects and contended that immediate peers are of

crucial importance in male students’ educational choices decision. Female students

were found less influential from their peers’ ability, performance and less likely to

follow the decision of their peers. Similar results depicted from the Thomas and

Webber (2001) study, from the nominal logit regression analysis the study revealed

that peer group plays statistically significant role in students’ post-compulsory

education decision. Gender dichotomy depicted from the results; male students give

more preferences to the decision of their friends and are more susceptible to peer

group effects.

The peer relationships is widely considered as a potential source of support for

development personal perceptions and attitudes. Stake and Nickens (2005) contended

that peer relationships positively affect students’ perceptions of their possible career

in Science related fields. Data was collected from 76 high schools junior and senior

students with equal representation of male and female students. For identification of

peer effects the Science peer relationships scale was administered. They concluded

that across gender peer groups remained as a main agent of socializer and largely

shape the adolescents expectations and perceptions to view him/herself as scientist in

the future. Students are more likely to participate in Science related activities if they

have network of friends in the Science.

A consistent results were depicted from the Kiuru et al., (2007) study conducted on

peer groups influences on 9th grade students’ educational expectations. Similarity of

educational expectations and academic achievements were found among peer groups

members. Peer groups effects were not correlated with group size, for instance, dyadic

group and larger group have similar effects on adolescents. Similarity of group

characteristics were found in girls peer groups, while boys were different in their

group characteristics. For both boys and girls peer relations are a source of future

information, provide support in educational decision and act as a role model for each

other. The study also shows that group norms are highly valued and only those who

share similar future expectations are allowed to enter into group.

According to Flashman (2012) academic achievements do explain the friendship

composition among adolescents. Used the data of National Longitudinal Study of

Adolescent Health, a saturated sample of 3700 students of 7th-12th grade were drawn

from 144 school in US. The study revealed that friendships network ties were

extended to similar academic achievements students’, for instance, high academic

achiever students have the tendency of making friendship with high academic

achieving students and lower academic achieving students have the tendency of

making friendships with other lower achiever students. The study also found that

dynamics of friendships are changing overtime and similarities between friends were

maximized. These friendships ties may predict the school to college trajectories for

the adolescents.

The social context of adolescents exerts influences on the decision of Math course

taking among 7th-12th grade high school students in U.S (Frank et al., 2008). The data

base of US Adolescent Longitudinal Add Health was used, a sample of 20,745

students were collected from 80 high schools through stratified random method. The

study showed that the social milieu of adolescents is a strong predictor of Math course

taking decision. A tendency of Math course taking was found among students who

have close friends in the same course. Female students were found more responsive

to their social milieu than boys and on the odds to follow their group members. Male

students are less responsive to their social context and more independent in their

decision of selecting advance Math courses.

Exploring the racial composition of friendships at school level Ueno (2009)

documented that racial composition of friendships increases the school attachment

among U.S high school students. Differences in racial friendships effects were found

among Black, Hispanic, Asian and White students. For Black and Asian cross race

peer groups’ friendships tend to positively associated with high academic orientation

and better placement in advance course tracks. Contrary, due to the top position

friendships popular hierarchy White students have same race friends’ pattern and their

stronger school attachment associated with more same race friends. School level racial

composition of friendship of Hispanic students were not associated with any

friendship compositions. Stearns et al., (2009) analysed that how interracial

friendships form in secondary and college level among U.S students. They found that

friendships composition changed during the transition from secondary to college for

each racial groups. The friends’ composition remain same racial for White and Black

students before and during college transition. For Asians and Latinos students cross

race friendships composition were found before and after college transition.

The interpersonal relationships may play a significant role in educational aspirations

among students of pre and postsecondary education level. Buchmann and Dalton

(2002) examined the data collected from 12 countries and found that interpersonal

influences particularly peers and parents are the shaper of students’ educational

aspirations. The effects of interpersonal relationships were stronger in countries with

undifferentiated education system. Peers attitudes and behaviours were closely linked

with students’ high education ambitions. Zimmer and Toma (2000) also revealed the

peer effects on educational achievement among high schools students. A large data

set of five countries was used and comparison was made between public and private

schools across countries. The study lends support to assumption that peers effects do

matter in schools setting but the effect is vary across country and school. They

contended that peers play statistically significant role in educational achievement of

low ability students than high ability students.

Zimmerman (2003) pointed that the peers ability affect the students overall academic

achievements. Used the data from the British Child Development Survey data the peer

effects were documented for different backgrounds students. They tended that

roommate level peers effects exit among students and the peer school aptitude test

(SAT) score is both positively and negatively associated with students overall grade

performance. Sharing room with a low SAT score peer has worse effects on students’

academic achievements. The peer group review shows that students’ network of

friends particular their peers are of potential source to shape their life choices

including educational choices. Both students viewed their network of friends as a

social capital and valued peer group dimension in their decision. However, female

students are more sensitive to peer group influences than male students.

2.3.5 Influence of Gender Differences

A considerable research studies have affirmed the gender differences and preferences

in career pathways selection among male and female students. The sex role

reinforcement has been found a dominant predictor of girls and boys career choices

selection. Correll (2001) used the US data of National Educational Longitudinal Study

to examine the gender mathematical competency perception and its effects on

students’ career selection in Math, Engineering and Physical Sciences. Used the multi-

stage probability sampling technique, the study found gender differences in Math

competency between male and female students; cultural widely shared belief strongly

biased the students’ perceptions of ability in a particular task or field of study; personal

perception of task competency is considered necessary for enrolling in particular

career. It was also found that male students perceive themselves more mathematical

competent than female students and on odds to continue their career leading to

Science, Math and Engineering fields.

Correl (2004) provided experimental explanation to the constraints and preferences of

girls and boys career choices. It is hypothesized that biased culturally shared belief

played a mediating role in affecting students’ self-assessment of task competency

which consequently, differently influenced their career decisions. Male students

considered themselves mathematically superior and have high career aspirations

which lead them to peruse career in Science, Math and Engineering fields. The biased

self-assessment of mathematical competency constrained the female students’ choices

to enrol in Math and Engineering fields which further explain the gender gap in

enrolment in advance math courses.

Francis (2002) in a qualitative study examined the 14-16 years old students future

work aspirations in the secondary schools of London. The study found that gender

dichotomy is evidently reflected in students’ field selection process. Female students

have the tendency to prefer creative and caring fields such as Arts, Humanities,

Nursing and Medicines. Male students are inclined to choose technical, scientific,

Engineering or Business oriented fields for their future. According to Roksa (2005)

lower earnings are associated with majoring in female dominated fields. Used the data

of National Longitudinal Survey of Youth the study found that in US students who

have opted for female dominated fields have lower labour market opportunities and

comparatively experienced less earnings and lower occupational location in the world

of work than those students who enter into male dominated fields.

Charles and Bradley (2009) examined the sex segregation in field of study selection

in forty four countries. The data was drawn from International Math and Science

Survey and forty four developed, developing countries and transitional societies were

included in the study. The study was limited to find out the sex segregation in the four

fields i.e. Engineering, Mathematics and natural Sciences, Humanities and Social

Sciences, and Health/other. The multivariate analysis of the data shows cross-national

differences in field of study selection among students and found strong gendered

patterns in educational decision in all countries. Sex segregation by fields of study

was found in more affluent countries; for instance, Finland, South Africa, and

Switzerland have the highest level of sex segregation and Tanzania, Bulgaria and

Colombia have the lowest level of sex segregation by field of study. The study

revealed that across all countries women were underrepresented in Engineering fields

and were overrepresented in Humanities and Social Sciences fields. Female students

were overrepresented in Health/other and caring fields but a tendency were also found

among female students to enrol in the fields of math and natural sciences.

Similar findings revealed from the study of Van Langen et al., (2006), which shows

differences of male and female participations in STEM courses across 42 countries.

The study shows a lower number of female enrolling in tertiary education in STEM

courses which increases the underrepresentation of women in Math and Science

fields. A 30 years review of literature conducted by Clark Blickenstaff (2005)

concluded that the phenomena of female participation in Science, Technology,

Engineering and Math (STEM) fields are multifactorial and multidimensional that

required multifaceted solutions.

A cross national study conducted by van Langen and Dekkers (2005) in Sweden, UK,

Netherland and US. The study found cross national differences among students in

STEM courses participations. The Math and Science subjects choices at upper

secondary level plays an important role for choosing STEM subjects at tertiary

education level. Due to lack of interest for these subjects a general declining trend was

found among female students participation in STEM courses in all countries.

Consequently, underrepresentation of women in labour market have been reported in

these countries. According to Uerz et al., (2004) study a gender dichotomy depicted

from the students’ secondary school career choices. Data was drawn from Dutch

National Longitudinal Study of secondary school careers, the study included 20,000

first year students of 381 schools across country. The study showed a strong gender

differences in career selection process because it is contended that male and female

students have different areas of interest, for instance, boys choose Science subject

more than girls and perceive their probability of success in these male dominated

fields.

Thompson (2003) studied the single sex schooling effect on female students’ major

choices at secondary level in US. Data was drawn from the High School and Beyond

(HS & B), using two stage sampling method selected female students from 1,122

schools who were enrolled in community or junior colleges. The study found that

single sex schooling pushes female students to enrol in more integrated or traditionally

male dominated fields and refrain them to enrol in traditionally female dominated

fields i.e. Health Sciences, Education, and Library Sciences. Attended Catholic or

religious based schools have constrained the female choice to more female dominated

fields. Simpson (2001) also analysis the data of High School and Beyond (HS & B)

to find out differences in academic major choices among students belong from

different racial backgrounds. He found that beside the racial backgrounds, gender

identity is the strong determinant of academic major. It is contended that female

students give less preference to technical fields than male students and are more

inclined to pursue their career in health related fields, business, public services and

liberal arts fields.

Study conducted by Francis et al., (2003) on the subject choices and future

occupational aspirations of female students from single sex-schools in England

revealed that gendered trends persists among students in subject choice preferences.

Students were asked to identify their top five favourite subjects in questionnaire. The

nature of subjects was perceived as an important determinant among students’

preferences. Majority of students identified Art, Math, English, History and Science

the most favourite subjects. Of the Science subjects Chemistry was least favourite and

Biology was the most popular subject among students. Math subject was ranked

lowest in the list and lower number of students have identified it as favourite subject.

Findings of the study reflected the traditional gendered patterned in students choices

and female students are more inclined to choose feminine jobs for the future. For

instance, female students are more inclined to choose creative and caring jobs than

technical and business jobs.

Tinklin et al., (2005) examined the attitudes of 200 secondary level students in

Scotland about their views on general gender role and their personal future aspirations.

On gender basis students were divided into average to high group and average to lower

group. The study showed that all students believe that school level qualification is

very important and essential for getting good job in the future. All the students believe

in equal participation of both the gender in the world of work and view that both the

gender could do any job they want. The study further explores gender differences in

personal future aspirations, for instance, female students are more interested in having

good job and consider the important feature of their job is to help others. Contrary,

male students have different aspirations and consider the important feature of their job

is promotion opportunities and long term security. Consequently, due to differences

in personal aspirations both the students are looking for choosing gender typical

subjects at the upper secondary level.

Similar study has been conducted by Taiwo and Menyasto (2005) in Botswana to

know the secondary level students perceptions to pursue career in Physical Sciences

fields. Population of the study was 36 public secondary schools, used the convenient

sample techniques data were collected from 409 students of 14 schools were surveyed.

The study revealed that there is a robust gender differences between male and female

students perceptions about Physics. Male students hold positive career perception than

girls and perceive Physics as masculine fields and inclined to pursue their career in

the subject, while female students have negative perception about Physics related

careers and perceive it as hard subject for themselves. On the basis of above review,

it is concluded that gender reinforcement to a large extent determine students preferred

career choices and students had the tendency to valued their gender identity in their

decision. Therefore, a gendered pattern of choices are reflected from students’

choices.

2.3.6 Psychological Factors Influences

A large stream of research has been carried out to explore the importance of different

psychological influences in students’ career selection process. As Pike (2006)

presented an empirical evidences to Holland’s theory of vocational choices by

interpreting the students’ expectations about college, their personality types and their

intended college major. Participants of the study was 543 college freshman in US. The

study found that personality types and academic major are linked with students’

college expectations. Students with investigative, artistic and enterprising personality

type had higher expectations being involved in science and math. However, the study

found a lower female expectations than male students for Mathematics and Science

disciplines. The Allen and Robbins (2008) study also supported the Hollond’s theory

of vocational preferences and explored association between academic performances

and person environment fit. The study found that students are more flourish in

academic environment that fit their personality types.

Porter and Umbach (2006) used the Hollond’s theory of career to explore and

understand the students’ college major choices. Three consecutive cohort of degree

seeking students from 1993, 1994 and 1995 were selected from Liberal Arts College.

Data on students college major was taken from institutional database and college

major was classified into four categories i.e. Arts and Humanities, interdisciplinary,

Social Sciences and Life and natural Sciences. They used six set of independent

variables to understand the students college major choices: demographics, parental

influences, academic preparations, anticipated career views, political views and

personality goals. The study documented gendered pattern, racial and ethnic

differences in college major. For instance, female and Black students were on the odds

to choose interdisciplinary and Social Sciences over Science major. The study also

found that academic preparation, belief about the major, political views and self-

efficacy all consistently affect the students’ choices. Moreover, Hollond’s four

personality scale revealed as the predictor of college major. Students with high scored

on investigative scale are more likely to choose Science major, while students scored

high on artistic, social and enterprising scale are more likely to opt for non-science

majors.

Fan et al., (2012) conducted cross culture study of American and Hong Kong students

and compared the pattern of relationships among personality traits, vocational interest

and career explorations. Data was collected from 369 American and 392 Hong Kong

university students. The study found cultural differences in the pattern of relationships

and the personality traits were mediated to career interests and career explorations.

Hong Kong students scored higher than American students in the personality

dimension.

Rogers (2008) investigated the career decision-making process of high school

students in Australia by exploring the importance of personality type in adolescent

career planning and explorations. Data were collected from 414 high school grade

10th, 11th and 12th students. Hierarchical multiple regression analysis was conducted

to test the relationships between the variables. The study extended the social cognitive

career theory and revealed that personality and social support linked with career

readiness and exploration.

Salami (2004) provided casual explanation to students’ career orientation to seven

different personal, social-psychological variables. A sample of 260 senior secondary

level students were collected from Ibadan, Oyo State. Six scales i.e. sex role

stereotyping inventory, socio-economic status scale, self-efficacy scale, family

involvement inventory, career aspirations and career orientation scales were used to

collect data from the students. Analysed data through multiple regression and path

analysis. The study documented that career aspirations, socio-economic status, family

involvement and sex role stereotyping had direct causal influences on students’ career

orientations.

Osoro et al., (2000) investigated the factors that reportedly affected career decision-

making process of high school students in Kenya. A sample of 280 students were

drawn from three urban and urban schools from Nairobi and Naynza province. Beside

the all other factors the study found that unlike urban students, rural students visited

the career counselling department in their respective school and got help from there.

However, urban students reported that they had more access to career related

information. It has been demonstrated that in both rural and urban schools teacher

played an important role to motivate students to take initiative to career related

information.

Gushue et al., (2006) study have found relationship between career decision-making

self-efficacy, vocational identity and career search activities in a sample of 72

American African high school students. Findings of multi regression analysis shows

that career decision-making self-efficacy was associated with vocational identity and

students career exploration activities. Students who had greater self confidence in

making career related decisions were better sense of their abilities, interests and goals

and more on the odds to engage in career exploration related activities.

Bright et al., (2005) investigated the influence of contextual factors and serendipitous

events on career decision-making of 651 university students. The study found

statistically significant effects of contextual factors on students’ career decision-

making. For instance, the self-reported factors were media, internet, teachers, and

parents. These self-reported factors yield significant effects on students’ choices.

Moreover, the study also documented the influence of unplanned and chance events

on students’ choices at university level. On the basis of above mentioned review, one

can conclude that students considered the psychological factors influences in their

career choices and make their decision congruent with their personality, interest,

abilities, aspirations and expectations.


Economists lay emphasis on labour market opportunities structure and returns from

education. Analysed the US Current Population Survey (CPS) Freeman and Hirsch

(2008) found link between changes in 27 knowledge areas over 26 years and changes

in labour market job contents. They argue that students decision on college major are

well made before degree completed, based on the market importance and valuation of

knowledge content of the job at the time of decision. Women’s degree of

responsiveness to knowledge content was statistically stronger than male but week

monetary returns responses were documented for female students than male.

Staniec (2004) examines the determinants of college major choice and the factors that

affecting the students’ entry into Science, Engineering and Math disciplines are

significant by race and sex. Uses data from the National Educational Longitudinal

Study of 1998. The study surveyed students from their 8th grade to grade 12th and

analysed the students’ major choices at post-secondary level. Majors were grouped

into four categories i.e. Science and Engineering, Math, Humanities and Fine Arts and

Social Science. College major choice was documented among White, Asian, Hispanic

and Black students. Significant racial differences were found in enrolment in majors,

for instance, Asian students have high probability to enrol in SEM fields, than Social

Sciences. Asian students put high value on major returns, while the greater labour

market reward have attracted Asian students to SEM field. Study also found that

controlling other factors the major returns have no effects on female students majoring

in SEM fields.

Analysed the National Longitudinal Study of Class 1972-1974, Arcidiacono (2004)

estimated the monetary returns to particular college major among students. The

majors were grouped into four categories i.e. Natural Science, Business, Social

Science and Humanities and Education. It was depicted from the data that individual

choice of college major is conditional on the anticipated future expectations and one’s

ambitions that what they would do in the future. After controlling the Math ability,

statistically significant monetary premium exist in choosing natural science and

business as college majors.

The earnings differences were estimated among the Canadian Bachelor students by

Finnie and Frenette (2003). The National Graduate Survey database of 1982, 1986

and 1990 was used for the estimating variability of earnings differences by field of

study. Majors were grouped into earnings pattern and majors have different earnings

profile were kept separately. A large earnings pattern persist among students choices

in all three cohorts. Male students were more sensitive to earnings effects than female

students and were on the odds to prefer more lucrative fields.

Brunello et al., (2004) studied the wage expectations and expected employment

probabilities among European Business and Economic students. They collected data

on a short questionnaire from 10 European countries and surveyed 26 Business and

Economic faculties. After controlling the personal and house hold characteristics, they

found that students perceived ability was strongly associated with students’ high

expected wage and better job in the future. Private university students have lower

earnings expectations than students who enrolled in universities with a formal

procedure. It was also revealed from the analysis that female college students have

lower earnings expectations and worse job prospect.

Thomas and Zhang (2005) demonstrated that beside the higher quality factor,

students’ growth in the earnings varies by major field of study. Analysis was

conducted on national representative sample, drawn from the Baccalaureate and

Beyound study 1993-1997 and Integrated Postsecondary data Education Data System

1992-1993. The study documented discrepancies among students graduated from low

quality public college. High quality public institutions students enjoy substantially

high earnings. Students graduated in Science, Math, Business and Social Sciences

enjoy higher returns than graduated in Education and History.

A similar line study conducted by Montmarquette et al., (2002) to investigate the

choices of college majors among students enrolled at college level. Uses the database

of National Longitudinal Survey of Youth 1979, mixed multinomial logit and probit

models were used to estimate the effects of college major on students’ earnings. The

study found that the choice of college major concentration depends on the anticipated

earnings associated with major. The findings revealed that Science and Business offer

the highest earnings for both gender, while Education has the lowest monitoring

returns. Female students were reportedly lower earnings expectations, while high

payoff could not explain their subject choices selection process.

Boudarbat (2008) examined the community college students’ choices of subjects’

preference to one over other in Canada. Collected data from the two cohort of

Canadian National Graduate Survey (1990 & 1995) and sampled 12,781 individuals

completed their program at Canadian Community College. The study demonstrate that

after graduation monetary returns do explain the field of study preferences choices.

Individuals who had work experience before starting the community college put more

weight on earnings dimension in their decision. Gender differences were evidently

depicted from the study and it is contended that unlikely male, female students were

less sensitive to high payoff in their field of study choices. Science, Business and

Commerce are relatively high earnings fields than Social Science and Education. In

summary it can be concluded that students lay emphasis on economic factors

influences in their decision and had the tendency to choose those fields for their

futures which are job oriented, had high pecuniary returns and associated economic

advantages in future. Unlike female students, male students put high value on mentor

returns in their decision.

2.4 Conceptual Framework

In social research the development of conceptual framework is common practice. It is

usually based on the related theories presented and review of existing literature on the

phenomenon under investigation. The figure 2.1 shows the theoretical framework for

the current study which indicate a tentative relationship between variables. In the

current study career decision making was used as dependent variable, while family

background, parental education, parental occupational background characteristics,

parental income, peer group influences, influence of gender differences,

psychological and economic factors influences as independent variables. The primary

focus of the study was on career decision-making refers to students intention to pursue

their career in Pre-medical, Pre-engineering, General Group and Commerce at higher

secondary level.

CHAPTER 3

RESREACH METHODOLOGY

This chapter presents the detail of methodology used in this thesis. The chapter has

been organized under six major headings i.e. methodology, research design, type of

study, universe, sample size, method of sampling, method of data collection, analysis

of data, pre-testing, coding, tabulation and statistical methods of data analysis. A brief

description of each topic has been given as under.

3.1 Research Methodology

The present study is explicitly based on the quantitative methodological approach and

employed the quantitative methods for data collection and analysis to present

empirical evidences to support the hypotheses constructed for the study. Research

methodology is arguably view as medium of instructions for conducting research. As

Katleen and Lapan, (2004:5) argue that methodology encompasses our entire

approach to research. According to Sarantokas (1993:33) methodology means the

science of methods, which contains the standards and principals employed to guide

the choice, structure, process and use methods, as directed by the underlying

paradigm. In addition to it, methodology in research means as a medium of

instructions for conducted a scientific inquiry (Nachmias and Nachmias, 1992:15-17).

The widely used methodologies in scientific research are; quantitative methodology,

qualitative methodology and mixed approach methods. As Creswell (2003:18)

contended that the quantitative research involves; the collection of data; quantification

of information; and subjected to different statistical tests in order to support or refute

“alternate knowledge claim”.

3.2 Research Design

In the present study survey technique was adopted for data collection and the study

samples were neither manipulated in any manner nor subjected to any treatment.

Research design determines the priority being given to different dimensions in the

research process and covers all the aspect of research avoiding biasness and

preventing distortion. A research design provides a structure that guides the research

process for the execution of research methods that involves the process of data

collection, data analysis and making inference. Research design is the conceptual

framework within which a researcher answers to specific research questions or testing

hypothesis within time and resources available to them. (Bhattacherjee, 2012:35). It

is generally perceived that a good research design is the one which clearly defines

purpose and logical order in research questions and proposed methods or approaches

which can generate reliable and valid data. The researcher has the choice to select the

most suitable and appropriate research design for the study. In the contemporary

Social Science research the vogue research designs are; exploratory, descriptive,

correlational, causal-comparative and experimental design. A brief description of

research design used in the study is as under;

3.2.1 Exploratory Research Design

In order to achieve the set objectives of the study the exploratory research design was

used in the study. In exploratory research design the focus of entire research process

is on gaining insights and ideas. This type of research design is also known as

formulative research study. The objective of this design is to formulate a problem for

precise investigation and discovery of new idea or in-depth insight. The exploratory

research design is more flexible to provide opportunity to cover all the aspects of the

problem and formulate a working hypotheses (Kothari, 2004:35).

3.3 Type of Study

Each study has its own nature and specific objectives. The nature of present study is

an exploratory research and the study is different in the sense that it does not proposed

to predict the career decision-making behavior of students but rather attempting to

explore the determinants that reportedly influence the career decision-making of

higher secondary level students. Generally exploratory research is conducted when

there is not enough information available about the phenomena under investigation

and the researcher aims to gain insights about or familiarize with phenomena or

concept under investigation. The study attempts to employ comparatively open,

flexible and inductive approach in the research process (Neuman, 2006:33-35).

Exploratory study facilitates the researcher to define the research problem and to

construct study hypothesis accurately. Exploratory research study employs very

flexible research approach, in order to cover all aspects of phenomena under

investigation the researcher uses the more suitable and appropriate research

techniques for generating much needed information. A research study has its own

purpose and goal to achieve which is reflected in the findings and conclusion drawn

from the data. The specific nature and quality of a study makes it distinguished and

unique in terms of its approach towards the topic or issue under investigation. The

social research has been organized into three groups based on what a researcher is

trying to achieve; explore a new topic or issue; describe a social phenomenon; or

explain why something occurs. All the three major types of research studies i.e.

exploratory, descriptive and explanatory research have some unique characteristics

that distinguished one form the other. A research study may have multiple purposes

but one purpose is usually dominant (Neuman, 2006:33).

3.4 Population

The population of the present study was made of all the students enrolled in both

public and private colleges at higher secondary level located in Karachi city.

According to the Board of Intermediate Education (B.I.E.) Karachi, in the year 2014

there are 160 public and 153 private sector affiliated colleges/higher secondary

schools. Therefore, all the higher secondary level students constitute the population

for the study. After the 18th amendment the academic institutions are the responsibility

of provincial government and federal government provides assistance in terms of

curriculum development, accreditation and financial support for research work.

According to Pakistan Education Statistics (2011-12) 1.246 million students have

been enrolled at higher secondary level education.

3.5 Sampling Method

As the population of the study was too big and for the researcher within available

resources and time it was not possible to collect data from all the registered institutions

in the city. Therefore, on the first stage convenient sampling technique was used to

select eight (8) easily accessible colleges from public (4) and private sector (4)

institutions located in Karachi city.

On the second stage the probability sampling method was used and stratified random

sampling technique was employed to draw a representative sample from the study

population. The population elements were separated into non-overlapping groups

(strata). Generally, stratified random sampling method is employed when there is a

need to represent all the groups of target population in research study or when

researcher has interest in a certain strata. Stratified random sampling method is very

economical and offer high degree of accuracy and provides results that can be

generalized to the entire population. The study population was divided into four strata

i.e. pre-medical, pre-engineering, general group and commerce. From each strata

students were randomly selected with equal representation of both gender.

3.6 Sample Size

In order to achieve the objectives of the study, an appropriate sample size was

collected from the study population. All the important considerations were made to

draw a sample size that was precise, accessible and representative of the entire

population being studied. Choosing a right sample size is a matter of great concern in

social research in general and in quantitative research in particular. In order to draw a

representative sample size from the population several methods are employed and

many considerations are valued. For instance, objective of the study, population type,

methodology employed, and type of instruments uses, time and resources availability

are all crucial for drawing an appropriate sample size from target population. Because,

a representative and accurate sample size has in important consequences with

accuracy and validity of study findings. Neither a large and nor a very small sample

size is a true representative of population under investigation and in both cases will

not produce an accurate, precise and valid results (Sarantokar, 1993:143-144).

Approximately, from each strata i.e. pre-medical, pre-engineering, general group and

commerce, 16 students were randomly selected from boys’ and girls’ colleges, equal

number of students were selected for 11th and 12th grade i.e. 8 students from grade 11th

and 12th. This resulted in a selected sample size of 512 students, comprised of 256

male and 256 female students with an equal representation of government and private

colleges.

3.7 Method of Data Collection

In the current study a structured questionnaire was used to collect the required data

from the higher secondary level students of Karachi city. The questionnaire was

specifically developed and designed for the study that focuses on the overall study

objectives. Questionnaire was discussed with experts and research supervisor on

regular basis. In order to explore accurate and required information, several

considerations have been made and after a pilot test changes have been made

regarding the exclusion and inclusion of certain questions. In the final questionnaire

31 closed ended questions have been included. The questionnaire was divided into

two parts. Part first includes personal and demographic information and part two

composes of matrix questions that included statements to capture students’ responses.

Data collection process was pre-planned and data collection schedule was shared with

concerned authorities (college principals and Administrators) a day before. The data

collection process was completed after necessary permission had been sought and

obtained from relevant authorities to conduct the study. The researcher received a

warm welcome from all the visited colleges for data collection purpose.

The questionnaire was self-administered to students during class time. Before students

filled in the questionnaire, an orientation session was conducted by explaining the

purpose, objectives of the study and the meaning of different concepts used in

questionnaire. Student were suggested to read carefully the consent form that he/she

agreed to participate in the study. Students’ personal privacy and confidentiality was

highly maintained and no personal identification marks or name were used during the

data collection. Overall, the study has a high response rate and completed 510

questionnaires were filled in by the students. In general students showed keen interest

in the topic and were willing to participate and report their opinion in a meaningful

way.

Furthermore, particular attentions were paid to the quality and the logical consistency

of the information collected. A careful data cleaning procedure was carried out, for

instance, 99.6% of the questionnaires have no missing information or observations

and had logical consistency in the responses. Questionnaires which have missing

information or inconsistencies in the answers concerned with the main variables were

dropped form the final analysis.

3.8 Pre-Testing

A pilot study was conducted under the study, which is a small scale replica of main

study and considered as a prerequisite in research process. The required information

may not be revealed, unless the researcher has not sure about the effectiveness,

reliability, validity and suitability of all data collection methods and instruments

employed in the study. Pilot study enable the researcher to removes ambiguities,

errors and inadequacies in the data collection methods and instruments. In order to

check the effectiveness of data collection methods and instruments 25 questionnaires

were per-tested. After the self-administration of the pilot test questionnaires to

students, modifications and additions were made regarding the exclusion and

inclusion of some question(s).

3.9 Measurement

The main idea of measurement in social research is that there is a thing being

measured. In both qualitative and quantitative research measurement of a concept or

variable are very essential and integral part in research process. Because, in

measurement researcher assigns category or number to variable in question.

Measurement is common practice in social research and a good measurement must be

precise, reliable and valid (Bailey, 2008:62). In the current study variables in question

were measured on Likert scale ranging from strongly disagree “1” to strongly agree

“5” which indicates the degree to which students disagree or agree to the item.

3.9.1 Demographic Profile

The demographic information of the students was documented on the designed

format. Type of college was labeled as “1” for government college and “2” for private

college; student class was labeled “1” for first year and “2” for second year. Students’

gender was measured in two categories “1” for male and “2” for female. The age of

students was measured on ratio level in five categories ranging from 15-16, 17-18,

19-20, 21-22 and 23 and above years. Family type was measured in four categories,

“1” for joint family, “2” for nuclear family, “3” for single parent family and “4” for

others.


Parental educational background was measured on ordinal level in seven categories

and assigned values to each category such as “1” for no education, “2” for elementary

education, “3” for secondary level, “4” for college level education, “5” for university

level education, “6” for vocational education.

3.9.3 Parental Occupational

Parental occupation was measured on upgraded version of International Standard

Classification of Occupation (ISCO, 2010) scale. A widely used scale for measuring

a person occupational/professional status or position. In the ISCO-2010 scale 10

major occupational groups were distinguished, each major group was further divided

into several sub-groups. In this study parental occupation was measured in sub-groups

and for analysis purpose the response were merged into major group. In the scale

group-1 represents “legislators, senior officials and managers”, group-2 includes

“professional”, group-3 consists “technicians and associates professionals”, group-4

represents “clerks”, group-5 for “service workers and shop and market sales workers”,

group-6 involves “skilled agricultural and fishery workers”, group-7 shows “craft and

related trade worker”, group-8 consists “plant and machine operators and assemblers”,

group-9 includes of “elementary occupations”, and group-0 represents “armed

forces”. A separate category of group-10 was included for retired and no occupation

or housewife in case of mother. Students were guided to choose the option that

represents their father’s or mother’s occupational status or position.

3.9.4 Parental Income

Parents’ income was measured on ratio scale according to the monthly income or

earnings of parent(s). Parental income was group in six categories where, “1”

represents “1” less than or 10,000, “2” for 11,000 to 20,000, “3” for 21,000 to 30,000,

“4” for 31,000 to 40,000, “5” 41,000 and above and “6” for no income.


Family background influences were measured on a matrix question including 11

statements, each statement represents the different family background influences on

students’ career decision-making. On five points Likert scale ranging from 1 “strongly

disagree” to 5 “strongly agree” students responses were captured. Statements 1 to 4

explored the psychological and emotional support which a student received from their

families. Statements 5 and 8 related to the family social and economic capital

influences and statements 9 to 11 purely agentic influences on students’ career

decision-making process.


Parental occupational background characteristics influences were measured on a

matrix question representing 13 statements. Students responses were captured on 5-

five points Likert scale ranging from 1 “strongly disagree” to 5 “strongly agree”.

Statement one related to students’ intention to pursue their career similar in their

parental occupation. Statement two related to the prestigious dimension of parental

occupational and statements 3 to 6 explored economic advantages associated within

parental occupation. Statements 7 to 13 captured the different kind of structural

constraints and opportunities attributes of parental occupation.

3.9.7 Peer Group Influence

Peer group influences were measured on a matrix question included 10 statements.

On five points Likert scale each item was assessed ranging from “1” strongly disagree

to “5” strongly agree indicating the degree to which they agreed to the items.

Statements 1 and 2 measured the students’ disposition and ties with friends.

Statements 3 to 10 measured the different kind of support students received from their

peer network.


On a matrix question the influence of gender differences were assessed. Each item

was assessed on 5 point Likert scale ranging from “1” strongly disagree to “5” strongly

agree. Statement 1 and 8 represent measured purely agentic choices in career decision-

making. Item two to seven revealed the different form of constraints that limit a

student educational choices due to his/her gender only.

3.9.9 Psychological Factors Influence

The different psychological factors influences were assessed on 8 statements matrix

question. Students responses were captured on 5-points Likert scale ranging for “1”

Strongly disagree to “5” strongly agree. Statement 1 and 4 revealed students interests,

abilities, skills and competencies and the influences of serendipitous events on

students’ decision. Statements 5 and 6 captured the opportunities structure influences

on students’ choices at post-secondary level.


The economic factors influences were assessed on seven statements matrix question.

On Likert scale ranging from strongly disagree “1” to strongly agree “5”. Statements

1 and 2 revealed the influences of opportunities within the career, statements 3

explored the influence of financial returns associated within the career, and statements

4 and 5 documented the students’ ambitions and opportunity for a better life associated

with the career and statements 6 and 7 captured the prestigious dimension of the career

selected.

3.10 Coding and Tabulation

Due care has been taken for checking each questionnaire for possible missing

information or incompleteness. All questionnaires were individually checked for this

purpose and questionnaires include incomplete or missing information were rejected

and not included in the study. For data analysis it is well recommended that statements

and answers must be converted to computer in the form of numbers. This entire

process is called coding. In the current study all variables were coded accordingly and

fed in computer to the spread sheet of SPSS version-20 for further process and

analysis.

3.11 Statistical Methods of Data Analysis

The collected data were subjected to both descriptive and inferential statistical

analysis. Because of robustness of the data collected, data analysis for the study was

carried out with the aid of statistical package SPSS (Statistical Program for Social

Sciences) version-20.

3.11.1 Descriptive Analysis

On the initial stage descriptive statistical analyses were carried out including measure

of central tendency (mean and median) and measure of variability about the average

(range and standard deviation). In order to draw a rough picture about the data

distribution, findings of descriptive analysis were tabulated, followed by graphical

presentation that revealed meaningful information about the data.

3.11.2. Bivariate Analysis

In the dissertation Bivariate analyses were carried out for establishing relationships

between variables in question and to show the significance of association between

variables. Contrary to univariate and multivariate analysis where in former case the

properties of single variable is described through a set of statistical techniques called

frequency distribution. Whereas, in latter case more than two variables are in question

and set of statistical methods are used such as multiple regression, multiple

discriminant analysis and multivariate analysis of variance.

3.11.3 Chi-Square

Chi-square test, symbolically written as χ2 (pronounced as Ki-square), is the most

common and useful statistical test of significance in social sciences research. It is

based on the null hypothesis: that there is no relationship between two variables. The

test is usually employed for either showing the existence or to verify significance of

association between independent and dependent variables (Babbie, 2004). In the

present study Chi-square test was applied to verify and establish significance of

association between variables in question. The Chi-squire test of independence was

conducted for variables in question. Chi-square test for association is also known as

Pearson’s Chi-Square test for association and used to determine the strength of

association between variables, whereas Chi-square test for independence explains that

whether two attributes are associated or not.

Formula for Chi-square calculation

χ2 =

In order to establish or verify the relationships between independent and dependent

variables Chi-square test was employed and the values were compared with the table

values, if the calculated value of χ2 is less than the tabulated value than the null

hypothesis stands which means that there is no relationships between variables. If the

calculated value of χ2 is greater than the tabulated value than the null hypothesis is

rejected which indicates association between variables.

3.11.4 Degree of Freedom

To compute the Chi-square value from the contingency table, the degree of freedom

was calculated DF= (R-1) (C-1). Where “DF” stands for degree of freedom and “R”

means the number of rows and “C “means the number of columns. The number of

degree of freedom must be known before the table is used. After calculating the value

of DF, the value of particular level of significance was noted and compared with the

calculated value of Chi-square for 0.05 level of significance.

3.12 P-Value

P-value is the probability value for a statistical test of a hypothesis, assuming that the

null hypothesis is true. It is a measure that determine that how unusual or rare our

obtained statistics is, compared with what is stated in our null hypothesis. The smaller

the P-value, the more evidence in favor of rejecting the null hypothesis against the

research hypothesis. P-value is reported as “P <0.05”.

3.13 Measurement of Correlation Coefficient

In the current study Cramer’s V was used for the measurement of correlation

coefficient between two variables. The closer V is to +1 indicates a positive perfect

relationship and the closer V is to -1 indicates strong negative relationship. The value

0 shows no relationship between the two variables. The values of correlation

coefficient closer to +1 shows stronger liner relationship and increase in the value of

one variable will change the value of compared variable in the same direction.

Inversely linear relationship is found if the value of correlation coefficient is closer to

-1.

Formula for Cramer’s V correlation coefficient;

In order to investigate the nature and degree of relationship between dependent

variable (career decision-making) and each independent variables Cramer’s V

correlation coefficient was calculated for each independent variables.

3.14 Interpretation of Results

After collection and analyzing the data by conducting several sophisticated statistical

tests the researcher has to draw inference from the data. The interpretation of results

were done very carefully and in an impartial manner otherwise, a misleading or

inaccurate conclusion will be drawn and the purpose of entire research process will

be vitiated. Interpretation is an art and a basic element in research process because the

usefulness and utility of any research findings depend on in proper interpretation. In

this process the researcher attempts to present evidences for revealing underlining

relationships between variables in questions; linking up his research findings with

those of other studies conducted in the same area; serves as a guide for other

researchers by creating new avenues for future research in the same area. Finally,

implications of research findings are explained and recommendations made on the

basis of study findings.

CHAPTER 4

ANALYSIS AND INTERPRETATION OF DATA

Analysis and Interpretation of Results

In order to obtain the accurate results and accomplish the entire research process in a

scientific way, the researcher has followed the methodology defined in the previous

chapter to reach a conclusion that will help us in to explore the determinants that

precipitate students in career decision-making at higher secondary level. The

quantitative findings of the study are presented and described in this chapter, the

chapter is divided into two main sections; section one relates to the descriptive

statistics; section two presents bivariate analysis indicating the relationships between

dependent and independent variables in question.

4.1 Descriptive Analysis

In the current study descriptive analysis has been conducted for all the variables in

question including the personal and demographic information, parental educational,

parental occupation, parental income, family background influences, parental

occupational background characteristics influences, psychological influences,

economic factors influences, peer group influences and gender differences in career

decision-making. Descriptive analysis is the process of summarizing and organizing

of data collected in understandable way. It shows overall picture of a research data by

providing information about what is and what the data shows. In the present study

descriptive analysis includes the measures of central tendency and graphical

presentation of the data. For both male and female students separate variable-wise

descriptive analysis was undertaken.

SIMPLE TABLES

Table 4.1

Frequency and percentage distribution of students with respect to college type

Type of College Frequency Percent Cumulative Percent

Govt. College 256 50.0 50.0

Private College 256 50.0 100.0

Total 512 100.0

Graph 4.1

The table and figure in pie-chart show equal representation of government and private

colleges (50% each). Equal number of students were participated in the study,

therefore, both the government and private colleges were equally represented in the

study.

Govt.

College, 50%

Private

College, 50%

Govt. College Private College

Table 4.2

Frequency and percentage distribution of students’ according to class

Students’ Class Frequency Percent Cumulative Percent

First year 256 50.0 50.0

Second year 256 50.0 100.0

Total 512 100.0

Graph 4.2

The table and figure in pie-chart show students’ class in which they were currently

enrolled. Both classes were equally represented in the data (50% first year and 50%

second year).

1st Year

50%

2nd Year

50%

Students' Class

1st Year 2nd Year

Table 4.3

Frequency and percentage distribution of students according to field of study

Field of Study Frequency Percent Cumulative Percent

Pre-medical 128 25.0 25.0

Pre-engineering 128 25.0 50.0

General 128 25.0 75.0

Commerce 128 25.0 100.0

Total 512 100.0

Graph 4.3

The table and figure in pie-chart show frequency and percentage distribution of each

strata represented in the study. The final sample size consists of 25% pre-medical,

25% pre-engineering, 25% Commerce group and 25% General group students.

Pre-medical

25%

Pre-engineering

25%

Commerce

25%

General Group

25%

Field of Study

Pre-medical Pre-engineering Commerce General Group

Table 4.4

Frequency and percentage distribution of students according to gender

Gender Frequency Percent Cumulative Percent

Male 256 50.0 50.0

Female 256 50.0 100.0

Total 512 100.0

Graph 4.4

The table and figure in pie chart show frequency and percentage distribution by

gender. Both gender were equally represented in the final sample size i.e. 50% male

and 50% female students.

Male

50%

Female

50%

Students' Gender

Male

Female

Table 4.5

Frequency and percentage distribution of students according to age

Students’ Age Frequency Percent Cumulative Percent

Male

16 23 9.0 9.0

17 75 29.3 38.3

18 81 31.6 69.9

19 45 17.6 87.5

20 23 9.0 96.5

21 and above 9 3.5 100.0

Total 256 100.0

Female

16 23 9.0 9.0

17 102 39.8 48.8

18 72 28.1 77.0

19 43 16.8 93.8

20 10 3.9 97.7

21 and above 6 2.3 100

Total 256 100.0

Male: Mean = 17.99, Standard Deviation = 1.24 Female: Mean = 17.75, Standard Deviation = 1.35

Diagram 4.5

Data in the table and bar chart show age distribution of students. The data shows that

majority of male students 31.6% had 18 years of age, 29.3% had 17 years of age and

17.6% had 19 years of age. The reported minimum and maximum age of male students

was 16 and 21 respectively with mean of 17.99 and with 1.24 standard deviation.

Female data indicates that majority of students 39.8% had 17 years of age, 28.1% had

18 years of age and 16.8% had 19 years of age. The average age of female students

were 17.75 years with Standard deviation of 1.135, whereas minimum age of female

students was 16 and maximum age was 21 years reported.

9

29.831.6

17.6

9

3.5

9

39.8

28.1

16.8

3.92.3

0

10

20

30

40

50

up to 16 17 18 19 20 21 & aboveStudents' age

MaleFemale

Table 4.6

Frequency and percentage distribution of students with respect to family type

Students’ Age Frequency Percent Cumulative Percent

Male

Joint Family 103 40.2 40.2

Nuclear Family 148 57.8 98.0

Single Parent

Family 5 2.0 100.0

Total 256 100.0

Female

Joint Family 116 45.3 45.3

Nuclear Family 137 53.5 98.8

Single Parent

Family 3 1.2 100.0

Total 256 100.0

Graph 4.6

Data in the table and bar chart show that majority of male students 57.8% belonged

to nuclear family, 40.2% belonged to joint family and only 2.0 percent students living

within single parent family. The female students’ data revealed that majority of female

students 53.5% residing in nuclear family, 45.3% belonged to joint family and only

1.2% belonged to single parent family.

40.2

57.8

2

45.3

53.5

1.2

0

10

20

30

40

50

60

70

Joint Family Nuclear Family Single Parent Family

Students' family type

Male

Female

Table 4.7

Frequency and percentage distribution of male students according to parental

education

Parental Education Frequency Percent Cumulative Percent

Father’s

Education

No Education/Skip 1 .4 .4

Elementary Education 39 15.2 15.6

Secondary Education 108 42.2 57.8

College Education 28 10.9 68.7

University Education 80 31.3 100.0

Total 256 100.0

Mother’s

Education

No Education/Skip 31 12.1 12.1





Total 256 100.0

Graph 4.7

The table and bar chart show parental level of education of male students. The data

shows that majority of male students 42.2% reported that their father had secondary

level education, 31.3% had university level education, 15.2% had elementary level

education and 10.9% had degree college level education, whereas only .4% student’s

father had no educational background. Data also revealed that most of male students

28.9% had elementary level education, 28.9% reported that their mother had

secondary level education, 13.7% had college level of education and 16.4% had

university level education, while 12.1% students’ mothers had either no education or

skipped this question.

0.4

15.2

42.2

10.9

31.3

12.1

28.9 28.9

13.716.4

0

10

20

30

40

50

Skip/No

Education

Elementary Edu Secondary Edu College Edu University Edu

Male students' parental educcation

Father's Edu

Mother's Edu

Table 4.8

Frequency and percentage distribution of male students’ according to father’s

occupation

Father’s Occupation Frequency Percent Cumulative Percent

Armed Forces 6 2.3 2.3

Legislator, Senior Officials & Managers 1 0.4 2.7

Retired, and No Occupation 6 2.3 5.1

Professionals 50 19.5 24.6

Technicians & Associate Professionals 61 23.8 48.4

Clerical Support Workers 12 4.7 53.1

Service Workers and Sales Workers 83 32.4 85.5

Skilled Agriculture, Forestry and Fishery 1 0.4 85.9

Craft and Related Trades Workers 12 4.7 90.6

Plant Machine Operators and Assemblers 11 4.3 94.9

Elementary (unskilled) occupations 12 4.7 99.6

Skip 1 0.4 100

Total 256 100.0

Graph 4.8

The table and bar chart show that 32.4% male students’ fathers belonged to services

and sales workers occupation, 23.8% belonged to technicians and associate

professional background, 19.5% students have reported that their father belonged to

professionals background, each 4.7% students reported that their father belonged to

clerical, support workers, craft and related trade workers, 4.3% reported plant and

machine operators or elementary occupation and only 2.3% students’ reported that

father belonged to armed forces.

2.30.4

2.3

19.5

23.8

4.7

32.4

0.4

4.7 4.3 4.7

0.4

0

5

10

15

20

25

30

35

Armed

Forces

Legislator,

Senior

Officials &

Managers

Retired, and

No

Occupation

Professionals Technicians

& Associate

Professionals

Clerical

Support

Workers

Service

Workers and

Sales

Workers

Skilled

Agriculture,

Forestry and

Fishery

Craft and

Related

Trades

Workers

Plant

Machine

Operators

and

Assemblers

Elementary

(unskilled)

occupations

Skip

Male students' father's occupation

Table 4.9

Frequency and percentage distribution of male students with respect to

mother’s occupation

Mother’s Occupation Frequency Percent Cumulative Percent

Retired, Housewife or No Occupation 224 87.5 87.5


Technicians and Associate Professionals 2 0.8 97.7

Craft and Related Trade Workers 1 0.4 98.1

Elementary and Unskilled Workers 1 0.4 98.5

Skip 4 1.6 100.0

Total 256 100.0

Diagram 4.9

Data in the table and bar chart show the male students’ distribution according to

mother’s occupation. Most of students 87.5% mothers were either retired, housewife

or had no occupation, 9.4% belonged to professionals group and 0.8% technicians and

associate professionals, 0.4% were engaged in craft and related trade workers and

elementary trade occupation category. Whereas, 1.6% students were skipped this

questions.

87.5

9.4

0.8 0.4 0.4 1.6

0

10

20

30

40

50

60

70

80

90

100

Retired,

Housewife or No

Occupation

Professionals Technicians and

Associate

Professionals

Craft and Related

Trade Workers

Elementary and

Unskilled

Workers

Skip

Male students' mother's occupation

Table 4.10

Frequency and percentage distribution of male students according to parental

income

Parental Income Frequency Percent Cumulative Percent

Father’s

Income

Up to 10000 30 11.7 11.7

11000-20000 56 21.5 33.2

21000-30000 50 19.9 52.1

31000-40000 44 17.2 70.3

41000 and above 71 27.7 98.0

No income/skip 5 2.0 100.0

Total 256 100.0

Mother’s

Income

Up to 10000 2 0.8 0.8

11000-20000 8 3.1 3.9

21000-30000 7 2.7 6.6

31000-40000 4 1.6 8.2

41000 and above 6 2.3 10.5


Total 256 100.0

Graph 4.10

Table and bar chart show parental income of male students. As 11.7% of male students

reported that their father’s had monthly income of up to 10000, 21.5% had 11000-

20000, 19.9% had 21000-30000, 17.2% had 31000-40000 and 27.7% had 41000 and

above monthly income. It was depicted from mother’s income data that 0.8% of

students had mother’s income of up to 10000, 3.1% students had mother’s of 11000-

20000, 2.7% students had 21000-30000, 1.6% students had 31000-40000, 2.3%

students had father’s income of 41000 and above, while 89.5% students mother’s had

no income.

11.7

21.5 19.9 17.2

27.7

20.8 3.1 2.7 1.6 2.3

89.5

0

20

40

60

80

100

Up to 10000 11000-20000 21000-30000 31000-40000 41000 & above No income

Male students' parental income

Father's

Income

Mother's

Income

Table 4.11

Frequency and percentage distribution of female students according to

parental education

Parental Education Frequency Percent Cumulative Percent

Father’s

Education

No Education/Skip 1 .4 .4





Total 256 100.0

Mother’s

Education

No Education/Skip 12 4.7 4.7





Total 256 100.0

Graph 4.11

The table and bar chart show students’ parental level of education. The data shows

that majority of male students 42.2% reported that their father’s had secondary level

of education, 31.3% had university level education, 15.2% had elementary level

education, 10.9% had college level education, while .4% students’ father’s had no

educational background. Most of students reported that their mother’s 41.0% had

secondary level of education, 29.3% had elementary level education, 16.0% had

college level education, 9.0% had university level education, whereas 4.7% students

either had mother’s with no educational background or skipped this question.

0.4

15.2

42.2

10.9

31.3

4.7

29.3

41

16

9

0

5

10

15

20

25

30

35

40

45

Skip/No

Education

Elementary Edu Secondary Edu College Edu University Edu

Female students' parental education

Father's Edu

Mother's Edu

Table 4.12

Frequency and percentage distribution of female students according to father’s

occupation

Father’s Occupation Frequency Percent Cumulative Percent


Legislator, Senior Officials & Managers 2 0.8 7.4

Retired, Housewife and No Occupation 4 1.6 9.0


Technicians & Associate Professionals 52 20.3 57.8


Service Workers and Sales Workers 63 24.6 83.2

Skilled Agriculture, Forestry and Fishery 10 3.9 87.1

Craft and Related Trades Workers 11 4.3 91.4

Plant Machine Operators and Assemblers 13 5.1 96.5

Elementary (unskilled) occupations 7 2.7 99.2

Skip 2 0.8 100.0

Total 256 100.0

Graph 4.12

The table and bar chart indicate the female students’ distribution according to fathers’

occupation. Majority of students 28.5% have reported that their father engaged in

professional occupation, 24.6% students’ fathers were engaged in service and sales

worker occupation, 20.3% reported that their father occupied in technicians and

associate professionals, 6.6% students’ fathers engaged to armed forces and 4.3%

students’ fathers were related to craft and related trade work.

6.6

0.81.6

28.5

20.3

0.8

24.6

3.9 4.35.1

2.7

0.8

0

5

10

15

20

25

30

Armed Forces Legislator,

Senior Officials

& Managers

Retired, and No

Occupation

Professionals Technicians &

Associate

Professionals

Clerical Support

Workers

Service Workers

and Sales

Workers

Skilled

Agriculture,

Forestry and

Fishery

Craft and

Related Trades

Workers

Plant Machine

Operators and

Assemblers

Elementary

(unskilled)

occupations

Skip

Female students' father's occupation

Table 4.13

Frequency and percentage distribution of students’ according to mother’s

Occupation

Mother’s Occupation Frequency Percent Cumulative Percent

Retired, Housewife or No Occupation 206 80.5 80.5


Technicians and Associate Professionals 2 0.8 98.0


Service and Sales Workers 1 0.4 98.8

Craft and Related Trade Workers 3 0.4 100.0

Skip 2 0.8 81.2

Total 256 100.0

Graph 4.13

Female students data revealed that 80.5% students reported that their mothers were

either retired, housewife or had no occupation, 16.0% students mother’s belonged to

professional occupation, 1.2% related to craft and related trade workers and 0.8%

related to technicians and associate professional background and .4% related to

clerical support workers, service and sales workers and craft related trade workers

respectively.

80.5

16

0.8 0.4 0.4 0.4 0.8

0

10

20

30

40

50

60

70

80

90

Retired,

Housewife or

No Occupation

Professionals Technicians

and Associate

Professionals

Clerical

Support

Workers

Service and

Sales Workers

Craft and

Related Trade

Workers

Skip

Female students' mother's occupation

Table 4.14

Frequency and percentage distribution of female students’ according to

parental income

Parental Income Frequency Percent Cumulative Percent

Father’s

Income

Up to 10000 25 9.8 9.8

11000-20000 33 12.9 22.7

21000-30000 53 20.7 43.4

31000-40000 98 38.3 81.7

41000 and above 44 17.2 98.9

No income/skip 3 1.2 100

Total 256 100.0

Mother’s

Income

Up to 10000 11 4.3 4.3

11000-20000 12 4.7 9.0

21000-30000 19 7.4 16.4

31000-40000 2 0.8 17.2

41000 and above 3 1.2 18.4


Total 256 100.0

Graph 4.14

Data in the table and bar chart show parental income of female students. It was

reported that 9.8% students had father’s income of up to 10000, 12.9% had 11000-

20000, 20.7% had 21000-30000, 38.3% had 31000-40000, 17.2% had 41000 and

above while only 1.2% students had either father with no income or skipped this

question. Mother’s income data revealed that 4.3% students had mother’s with inocme

of up to 10000, 4.7% had monthly income of 11000-20000, 7.4% had 21000-30000,

only 0.8% had monthly income of 31000-40000 and 1.2% students had 41000 and

above monthly mother’s income. Whereas a large number of students 81.6% had

mother’s with no income.

4.3 4.7 7.40.8 1.2

81.6

9.812.9

20.7

38.3

17.2

1.2

0

10

20

30

40

50

60

70

80

90

Up to 10000 11000-20000 21000-30000 31000-40000 41000 &above

No income

Father's Income

Mother's Income

Table 4.15

Frequency and percentage distribution of students’ knowledge about career

decision-making

Students responses Frequency Percent Cumulative Percent

Male Yes 218 85.2 85.2

No 38 14.8 100.0

Total 256 100.0

Female Yes 221 86.3 86.3

No 35 13.7 100.0

Total 256 100.0

Graph 4.15

Data in the table and bar chart show that 85.2% of male students had knowledge about

the term career decision-making, while 14.8% of students had no understanding about

the term. Female students’ data indicated that majority of female students 86.3% had

prior knowledge about the term, while 13.7% students had reported that they have no

understanding of the term career decision-making.

85.2

14.8

86.3

13.7

0

10

20

30

40

50

60

70

80

90

100

Yes No

Students' knowledge about career decison-making

Male

Female

Table 4.16

Frequency and percentage distribution of male students’ perception about


Students Responses Frequency Percent Cumulative Percent

Kind of inspiration 11 4.3 4.3

Choice of profession/occupation 71 27.7 32.0

Source of achieving authority 7 2.7 34.7

Achievement of desired goal 55 21.5 56.2

Availability of more job options in future 32 12.5 68.7

Way for achieving social status 4 1.6 70.3

Source of economic empowerment 15 5.9 76.2

Enhancing intellectual ability/skills 23 9.0 85.2

Do not know 38 14.8 100.0

Total 256 100.0

Graph 4.16

Data in the table and bar chart show that 27.7% of male students perceived career

decision-making as choice of profession, 21.5% thought that it was achievement of

desired goals, for 12.5% students it was a availability of more job options, 9.0%

students perceived as the enhancement of intellectual skills and abilities, 5.9%

students perceived it as source of economic empowerment, 4.3% thought that it as a

kind of inspirations and 2.7% students perceived that it as a source of achieving

authority, whereas 14.8% had no idea about the career decision-making.

4.3

27.7

2.7

21.5

12.5

1.6

5.9

9

14.8

0

5

10

15

20

25

30

Kind of inspiration Choice of

profession/occupation

Source of achieving

authority

Achievement of desired

goal

Availability of more job

options in future

Way for achieving social

status

Source of economic

empowerment

Enhancing intellectual

ability/skills

Do not know

Male students' perception about career decision-making

Table 4.17

Frequency and percentage distribution of female students’ perception about



Kind of inspiration 11 4.3 4.3

Choice of profession/occupation 42 16.4 20.7

Source of achieving authority 14 5.5 26.2

Achievement of desired goal 51 19.9 46.1

Availability of more job options in future 27 10.5 56.6

Way for achieving social status 26 10.2 66.8

Source of economic empowerment 8 3.1 69.9

Enhancing intellectual ability/skills 42 16.4 86.3

Do not know 35 13.7 100.0

Total 256 100.0

Graph 4.17

The data in the table and bar chart presentation show that for 19.9% female students

career decision-making was the achievement of desired goals, 16.4% students thought

that it as the enhancement of intellectual abilities/skills, for 16.4% students it was the

choice of profession, 10.5% students perceived it as the availability of more job

options in the future, 10.2% students though that it as mean for achieving social status,

5.5% of students reported that it was a source of achieving authority and 4.3% students

perceived it as a kind of inspirations, whereas 13.7% of students don’t know about the

term.

4.3

16.4

5.5

19.9

10.5 10.2

3.1

16.4

13.7

0

5

10

15

20

25

Kind of inspiration Choice of

profession/occupation

Source of achieving

authority

Achievement of desired

goal

Availability of more job

options in future

Way for achieving social

status

Source of economic

empowerment

Enhancing intellectual

ability/skills

Do not know

Female students' perception about career decision-making

Table 4.18

Frequency and percentage distribution of students’ responses on the important

role of career decision-making in one’s life


Male Yes 244 95.3 95.3

No 12 4.7 100.0

Total 256 100

Female Yes 255 99.6 99.6

No 1 0.4 100.0

Total 256 100

Graph 4.18

The data in the table and bar chart presentation show that majority of male students

95.3% agreed that career decision-making had an important role in their lives, while

only 4.7% students put less weight on the importance of career decision in their lives.

Majority of female students 99.6% agreed and perceived that career decision-making

had an important role to play in their life, while only 0.4% students denied the

importance of career decision-making in their lives.

95.3

4.7

99.6

0.40

20

40

60

80

100

120

Yes No

Role of career decision-making in one's life

Male

Female

Table 4.19

Frequency and percentage distribution of students’ responses on the level of

importance of career decision-making


Male

Not at all important 13 5.1 5.1

Low important 1 0.4 5.5

Slightly important 18 7.0 12.5

Neutral 13 5.1 17.6

Moderately important 21 8.2 25.8

Very important 115 44.9 70.7

Extremely important 75 29.3 100.0

Total 256 100

Female

Not at all important 1 0.4 0.4

Low important 9 3.5 3.9

Slightly important 6 2.3 6.2

Neutral 14 5.5 11.7

Moderately important 29 11.3 23.0

Very important 126 49.2 72.3

Extremely important 71 27.2 100.0

Total 256 100.0

Graph 4.19

The data in the table and bar chart show that 44.9% of male students perceived career

decision-making very important, 29.3% students extremely important, 8.2% students

moderately important, 7.0% students’ slight important, while 5.1% students remained

neutral in their opinion. Female students data revealed that 49.2% of female students

perceived that career decision-making very important, for 27.7% students it was

extremely important, for 11.3% students it was moderately important, for 3.5%

students it was low important, while 5.5% students remained neutral in their opinion.

5.1

0.4

75.1

8.2

44.9

29.3

0.43.5 2.3

5.5

11.3

49.2

27.2

0

10

20

30

40

50

60

Not at all

important

Low

important

Slightly

important

Neutral Moderately

important

Very

important

Extremely

important

Importance of career decision-making

Male

Female

Table 4.20

Frequency and percentage distribution of students’ responses on what stage of

life they have made career decision

Students responses

Frequency Percent

Cumulative

Percent

Male

When I was in primary level 42 16.4 16.4

When I was enrolled in secondary level 133 52.0 68.4

When I was entered in higher secondary

level 81 31.6 100.0

Total 256 100

Female

When I was in primary level 43 16.8 16.8

When I was enrolled in secondary level 112 43.8 60.5

When I was entered in higher secondary

level 101 39.5 100.0

Total 256 100.0

Graph 4.20

Data in the table and bar chart show that majority of male students 52.0% made their

educational career decision when they were at secondary level education, 31.6%

students made their career decision at higher secondary level and 16.4% students

made their career decision when they were in primary level education. Female data

revealed that majority of students 43.8% had made their decision when they were

enrolled in secondary level, 39.5% students made their decision at higher secondary

level and only 16.8% students was made their decision at primary level education.

16.4

52

31.6

16.8

43.8

39.5

0

10

20

30

40

50

60

When I was in primary

level

When I was enrolled in

secondary level

When I was entered in

higher secondary level

Stage of career decision-making

Male

Female

Table 4.21

Frequency and percentage distribution of students’ according to their first

career of choice


Male Yes 185 72.3 72.3

No 71 27.7 100.0

Total 256 100

Female Yes 191 74.6 74.6

No 65 25.4 100.0

Total 256 100

Graph 4.21

The data in the table and bar chart show that 72.3% of male students had reported that

it was their first choice of career, whereas for 27.7% students it was not their first

choice of career and they were interested in other than the present career. The female

data depicted that 74.6% of female students were of the opinion that it was their first

choice of career, while 25.4% students had reported that it was not their first choice

of career.

72.3

27.7

74.6

25.4

0

10

20

30

40

50

60

70

80

Yes No

Students' responses on first choice of career

Male

Female

Table 4.22

Frequency and percentage distribution of students’ responses on any other

choice of career


Male Yes 61 85.9 85.9

No 10 14.1 100.0

Total 71 100

Female Yes 48 80.0 80.0

No 12 20.0 100.0

Total 60 100

Graph 4.22

Data in the table and bar chart show the frequency and percentage distribution of

students who had reported in the previous question that it was not their first choice of

career. 85.9% of male students had reported that it was not their first choice of career

because of they had other choices of career in their mind, while 14.1% of male

students had no any other choices of career in their mind. Majority of female students

80.0% had reported that it was not their first choice of career because they were

interested in some other careers, whereas 20.0% students had no any other choices of

career in the mind.

85.9

14.1

80

20

0

10

20

30

40

50

60

70

80

90

100

Yes No

Students' responses on other choice of career

Male

Female

Table 4.23

Frequency and percentage distribution of students’ according to what was their

first choice of career


Male



Commerce 12 17.9 82.1

General Group 2 3.0 85.1

Vocational Education 8 11.9 97.0


Total 67 100

Female



Commerce 3 6.2 95.8

General Group 2 4.2 100.0

Total 48 100

Graph 4.23

Frequency and percentage distribution were calculated for those students who had

other choices of career in their mind. It was found that majority of male students

40.3% were interested in pre-engineering, 23.9% in pre-medical, 17.9% in commerce,

12.2% in vocational education, while 2.0% students were interested to join Armed

forces. Female students’ data indicated that majority of female students 54.2% were

interested in pre-medical, 35.4% want to pursue their career in pre-engineering, 6.2%

were interested in commerce and only 4.2% female students were looking for general

group as prospective field for their future.

23.9

40.3

17.9

3

11.9

3

54.2

35.4

6.24.2

0

10

20

30

40

50

60

Pre-medical Pre-engineering Commerce General Group Vocational

Education

Armed Forces

Students' responses on their first choice of career

Male

Female

Table 4.24

Frequency and percentage distribution of students’ satisfaction from their

decision


Male Yes 240 93.8 93.8

No 16 6.2 100

Total 256 100

Female Yes 254 99.2 99.2

No 2 0.8 100.0

Total 256 100

Graph 4.24

Data in the table and bar chart show students satisfaction from their career decision-

making. It was found that majority of male students 93.8% were satisfied from their

current choice of career, while 6.2% of male students were not satisfied from their

current career choice. Female students’ data indicated that majority of female students

99.0% were highly satisfied from their current career decision, while only 1.0%

students had reported that they were dissatisfied from their current career decision.

93.8

6.2

99.2

0.8

0

20

40

60

80

100

120

Yes No

Students' satisfiction from their career

Male

Female

Table 4.25

Frequency and percentage distribution of students’ level of satisfaction from

their career decision


Male

Not at all satisfied 17 6.6 6.6

Slightly satisfied 17 6.6 13.3

Moderately satisfied 53 20.7 34.0

Very satisfied 105 41.0 75.0

Extremely satisfied 64 25.0 100.0

Total 256 100

Female

Not at all satisfied 3 1.2 1.2

Slightly satisfied 11 4.3 5.5

Moderately satisfied 47 18.4 23.8

Very satisfied 97 37.9 61.7

Extremely satisfied 98 38.3 100.0

Total 256 100

Graph 4.25

Data in the table and bar chart presentation show students level of satisfaction from

their current decision. Male students’ data indicated that 41.0% of male students were

very satisfied from their career decision, 25.0% were extremely satisfied, 20.7% were

moderately satisfied, 6.6% were not at all satisfied and 6.6% students reported that

they were slightly satisfied from their career decision. The female data revealed that

38.3% of female students were extremely satisfied, 37.9% of students were very

satisfied, 18.4% were moderately satisfied, while 4.3% students were slightly satisfied

and only 1.2% students were not at all satisfied from their current career decision.

6.6 6.6

20.7

41

25

1.2

4.3

18.4

37.9 38.3

0

5

10

15

20

25

30

35

40

45

Not at all

satisfied

Slightly satisfied Moderately

satisfied

Very satisfied Extremely

satisfied

Students' level of satisfiction from their career

Male

Female

Table 4.26

Frequency and percentage distribution of male students’ responses with respect

to the role of family background in career decision-making


Yes 231 90.23 90.23

No 25 9.87 100.0

Total 256 100.0

Graph 4.26

Data in the table and bar chart show that majority of male students 90.23% believed

that family background played an important role in career decision-making process,

while 9.87% students thought that family background had no role in career decision-

making process.

90.23

9.87

0

10

20

30

40

50

60

70

80

90

100

Yes No

Role of family background in male students' career

decision

Table 4.27

Frequency and percentage distribution of male students’ responses with

respect to family background influences

S. No. Statements Disagree Neutral Agree

i. My family member persuaded me to choose

this career

86

(37.2)

20

(8.7)

125

(54.1)

ii. One or more of my family members are in

the same field

82

(35.5)

27

(11.7)

122

(52.8)

iii. I have discussed my career choices with

family members

42

(18.2)

23

(10.0)

166

(71.9)

iv. My family members have

encouraged/advised me to choose this career

48

(20.8)

30

(13.0)

153

(66.2)

v. My home environment influenced my career

decision

69

(29.9)

37

(16.0)

125

(54.1)

vi. My own financial/economic condition have

influenced my career decision

61

(26.4)

40

(17.3)

130

(56.3)

vii. My family expected me to study in this

career

57

(24.7)

24

(10.4)

150

(64.9)

viii. I have received career related information

from my family

47

(20.3)

34

(14.7)

150

(64.9)

ix. I am engaged in the career what my family

have chosen for me

69

(29.9)

40

(17.3)

122

(52.8)

x. My family has already chosen a career 97

(42.0)

50

(21.6)

84

(36.4)

xi. Career chosen by my family is not what I

want

124

(53.6)

31

(13.4)

76

(32.9)

Values in table indicate frequencies while values in parenthesis represents percentages

Family Background Influences on Male Students’ Career Decision-making

Different family background influences were assessed on 11 item scale, students

responses were captured on five point Likert scale ranging from “strongly disagree”

to “strongly agree”. Students were asked to indicate their level of agreement with each

item in the scale by addressing the family influences such as psychological and

emotional support students received at home; family social and economic capital

influences; and students agentic responses on family effects. For the analysis purpose

the response categories were reduced to three categories: disagree, neutral and agree.

Out of 256 male students sample, 25 male students were excluded from the analysis

because of they disregard the family background influences in their career decision-

making process. Findings from descriptive analysis are summarized as under;

The data in the Table 4.1.27 shows that family pursuance was strongly pronounced in

male students’ career choices. Most of students 54.1% were persuaded by their family

in their career selection process, whereas 52.8% of male students identified that they

had family member(s) in the career chosen. Moreover, 71.9% of male students agreed

they had discussed and negotiated their career choices with their family members.

Majority of male students 66.2% endorsed the family encouragement and involvement

in their career choice process. 54.1% of male students identified the home

environment influences in their career decision-making. It is generally believed that

family economic capital either constrain or provide opportunities to students for

further educational attainment. The current study found that 56.3% male students

reported the family economic conditions as the influential element of their decision-

making process. Family expectations also played a decisive role in the students’

choices as 64.9% of male students made their decision according to family

expectations.

Male students at the time of their decision-making received most of the career related

information from their family members for instance, 64.9% of male students identified

family as a source of information about their future career choices. Moreover, 52.8%

of male students were engaged in the career what their family had chosen from them.

Family openness was reflected from the findings as 42.0% of students endorsed that

their family had not already chosen a career for them. A large percentage of male

students 53.6% made their decision with conformity of family choices.

Table 4.28

Frequency and percentage distribution of female students’ with respect to the

role of family background in career decision-making


Yes 249 97.26 97.26

No 7 2.74 100

Total 256 100.0

Graph 4.28

The data in the table and bar chart show the female students responses on the role of

family background in career decision-making. 97.26% of female students perceived

that family background played an important role in career decision-making, while

2.74% denied the role of family background in career decision-making.

97.26

2.74

0

20

40

60

80

100

120

Yes No

Role of family background in female students' career

decision

Table 4.29

Frequency and percentage distribution of female students’ responses with

respect to family background influences


i. My family member persuaded me to choose

this career

84

(33.7)

58

(23.3)

107

(43.0)

ii. One or more of my family members are in

the same field

70

(28.1)

44

(17.7)

135

(54.2)

iii. I have discussed my career choices with

family members

48

(19.3)

33

(13.3)

168

(67.5)

iv. My family members have

encouraged/advised me to choose this career

61

(24.5)

23

(9.2)

165

(66.3)

v. My home environment influenced my career

decision

67

(26.9)

47

(18.9)

135

(54.2)

vi. My own financial/economic condition have


71

(28.5)

56

(22.5)

122

(49.0)

vii. My family expected me to study in this

career

68

(27.3)

28

(11.2)

153

(61.4)

viii. I have received career related information

from my family

49

(19.7)

49

(19.7)

151

(60.6)

ix. I am engaged in the career what my family

have chosen for me

67

(26.9)

47

(18.9)

135

(54.2)

x. My family has already chosen a career 99

(39.8)

72

(28.9)

78

(31.3)

xi. Career chosen by my family is not what I

want

174

(69.9)

33

(13.3)

42

(16.9)

Values in table indicate frequencies while values in parenthesis present frequencies

Family Background Influences on Female Students’ Career Decision-making

The family background influences 11 item scale was employed to female students to

capture the different family background influences in their career decision-making

process. Out of 256 female students’ sample, only 7 female students denied the family

background influences in their career decision-making process. These students were

excluded from the final analysis.

The findings of descriptive analysis in the Table 4.29 indicates that 43.0% of female

students were persuaded by their family members to enrol in their current career.

Majority of female students 54.2% were inclined toward those fields where they had

already family members in the career. Moreover, family discussion and negotiation

were profoundly affected female students choices 67.5%, whereas most of female

students had received support and encouragement 66.3% at home. Home environment

influences were also depicted from female students’ 54.2% responses and identified

it as the influential element in their career decision-making process. The family

economic conditions had weak influences on female students’ career decision making

at higher secondary level (49.0%).

Female students (61.4%) put high weight on family expectations in their decision and

made their career decision according to family expectations. Moreover, 60.6% of

female students identified family as a source of access to career related information.

Majority of female students 54.2% reported that they were engaged in the career what

their family had chosen for them. The findings also indicate that most of students

31.3% disagree with “my family has already chosen a career” dimension in their

career, whereas 53.6% of female students endorsed the congruence between their and

family choices.

In summary the descriptive analysis indicates that family background exerted

different influences on male and female students. It is noteworthy, that male not

female students received most of family resources such as more access to career

related information and considered more family economic conditions influences,

while female students made their decision according to family norms and values. The

findings suggested the possible gender biases in treating male and female students’ in

the family.

Table 4.30


to the role of parental occupational background characteristics


Yes 199 77.73 77.73

No 58 22.27 100.0

Total 256 100.0

Graph 4.30

The data in the table and bar chart show that majority of male students agreed 77.73%

that parental occupational background characteristics played an important role in

career decision-making process, while, 22.27% of students denied the role of parental

occupational background characteristics in career decision-making process.

77.73

22.27

0

10

20

30

40

50

60

70

80

90

Yes No

Role of parental occupational background

characteristics in male students' career decision

Table 4.31


to father’s occupational background characteristics influences


i. I am intended to work in my father’s

occupation

89

(44.9)

28

(10.9)

81

(40.9)

ii. My father’s occupation gives the feeling of

being respected

52

(26.3)

22

(11.1)

124

(62.6)

iii. My father’s occupation gives him

interesting and challenging things to do

52

(26.3)

29

(14.6)

117

(59.6)

iv. My father’s occupation gives him feeling

of security in future

54

(27.3)

28

(14.1)

116

(58.6)

v. My father’s occupation provides with an

income that satisfies him

49

(24.7)

29

(14.6)

120

(60.6)

vi. My father’s occupation gives the

opportunity to make as much money as

their friends/relatives

56

(28.3)

40

(20.2)

102

(51.5)

vii. My father’s occupation gives him

opportunity to the kind of work that suited

his abilities

36

(14.1)

41

(20.7)

121

(61.1)

viii. My father’s occupation gives more

advancement opportunities

51

(25.8)

47

(23.7)

100

(50.5)

ix. My father’s occupation provides him a

pleasant working conditions

49

(24.7)

28

(14.1)

121

(61.1)

x. My father’s occupation gives him the

opportunity to get full credit of work done

45

(22.7)

38

(19.2)

115

(58.1)

xi. My father’s occupation gives him

opportunity to work independently of other

43

(21.7)

33

(16.7)

122

(61.6)

xii. My father’s occupation keeps him busy all

the time

48

(24.4)

47

(23.7)

103

(52.0)

xiii. My father’s occupation gives him

opportunity to be of service to people

38

(19.2)

40

(20.2)

120

(60.6)

Values in table indicate frequencies while values in parenthesis represent percentages

Father’s Occupational Background Characteristics Influences on Male

Students’ Career Decision-making

The parental occupational background characteristics scale was administered to male

students to assess the father’s occupational background characteristics influences in

their career decision-making process. For both the parents the scale was separately

used to measure their influences on students’ career decision-making process. On 13

item scale different occupational background characteristics were captured such as

students intention to pursue their career in similar occupation as of the parent; social

prestigious of parental occupation; pecuniary benefits associated with parental

occupation; the different kind of structural constrains and opportunities associated

within the parental occupation. Students’ responses were documented on five point

Likert scale with endpoints of “Strongly disagree” to “Strongly agree”. For analysis

purpose the response categories were further reduced to “disagree”, “neutral” and

“agree”. Students were asked to indicate their agreement with each item in the scale.

Out of 256 male students sample, 58 students were excluded from the analysis because

of they denied the father’s occupational influences in their career decision. The

findings are summarized as under;

The Table 4.31 indicates a less resemblance in male students 40.9% choices to pursue

their career in similar occupation as of their father. It shows that male students had

the intention to start their career other than their father’s occupation. The respected

dimension of the father’s occupational had influences the male students’ career

choices as 62.6% of students reported it as influential element in their career choice

process, whereas 59.6% of male students agreed with the challenging and interesting

dimension of their father’s occupation. Moreover, 58.6% of male students do consider

the future security aspect of their father’s occupation in the career decision. The

earnings dimension of father’s occupation were evidently reflected as one of the

influential determinant of male students choices, as 60.6% of male students reported

that their father’s occupation provides a satisfied earnings opportunity and

comparatively earned as much as their relatives and friends (51.5%). Majority of male

students 61.1% reported that their father occupation suited the abilities and skills he

had.

The data further demonstrated that advancement opportunities attributes of father’s

occupation were influential on male students’ choices 50.5%. The pleasant working

conditions characteristics of father’s occupation had remained influential elements of

students’ career choices process 61.1%. Most of students 58.1% reported that “getting

full credit of work done” dimension had influenced their career decision.

Independence of working opportunities dimension was regarded by 61.6% of male

students in their decision, whereas 52.0% of male students agreed with “busy all the

time” aspect in their career decision. Moreover, 60.6% of male students perceived that

their father’s occupation had the characteristics to be of service to people.

Table 4.32


to mother’s occupational background characteristics influences


i. I am intended to work in my mother’s

occupation

14

(51.9)

1

(3.7)

12

(44.4)

ii. My mother’s occupation gives the feeling

of being respected

7

(25.9)

1

(3.7)

19

(70.4)

iii. My mother’s occupation gives him


7

(25.9)

2

(7.4)

18

(66.7)

iv. My mother’s occupation gives him feeling


8

(29.6)

3

(11.6)

16

(59.3)

v. My mother’s occupation provides with an


5

(18.5)

6

(22.2)

16

(59.3)

vi. My mother’s occupation gives the



11

(40.7)

5

(18.5)

11

(40.7)

vii. My mother’s occupation gives him the


his abilities

8

(29.6)

2

(7.4)

17

(63.0)

viii. My mother’s occupation gives more


7

(25.9)

3

(11.1)

17

(63.0)

ix. My mother’s occupation provides him a


7

(25.9)

4

(14.8)

16

(59.3)

x. My mother’s occupation gives him the


9

(33.5)

2

(7.4)

16

(59.3)

xi. My mother’s occupation gives him


8

(29.6)

6

(22.2)

13

(48.1)

xii. My mother’s occupation keeps him busy

all the time

8

(29.6)

8

(29.6)

11

(40.8)

xiii. My mother’s occupation gives him


9

(33.3)

2

(7.4)

16

(59.3)


Mother’s Occupational Background Characteristics Influences on Male

Students’ Career Decision-making

The occupational background characteristics scale was employed to male students to

assess the mother’s occupational background characteristics influences in their career

decision-making process. Students were suggested to indicate their level of agreement

with each item in the scale. Out of 256 male students’ sample, 27 male students had

working mothers’ only. The remaining male students were excluded from the final

statistical analysis.

The Table 4.32 indicates that mother’s occupational background characteristics

influences on male students’ career decision-making process. For instance, 51.9% of

male students had disagreed to pursue their career similar to their mother’s

occupation. The respectable dimension of mother’s occupation to some extent

influenced the career decision of male students’ 70.4%. Whereas, 66.7% of male

students perceived the interesting and challenging characteristic as influential aspect

of their decision. Moreover, 59.3% of male students do consider the future security

aspect, while similar percentage of students had reported satisfied earnings dimension

of their mother’s occupation. Similar responses were documented for “make as much

as money as their friends and relatives” influences, as 40.7% of male students agreed,

while an equal percentage of male students denied its influences in their decision.

Most of male students 63.0% reported a match between mother’s occupation and the

abilities and skill she possess. 63.0% male students were influenced by the associated

advancement opportunities within mother’s occupation, whereas 59.3% of male

students liked the pleasant working conditions aspect of their mother’s occupation.

Majority of male students liked and were influenced by the getting full credit of work

done aspect of their mother’s occupation. 48.1% of male students liked the

independent working characteristics of their mother’s occupation. Most of students

reported that their mother’s occupation kept her busy all the time, while 59.3% of

male students were influenced by their mother’s occupation because it provides her

the opportunity to serve the people.

Table 4.33


respect to the role of parental occupational background characteristics


Yes 214 83.99 83.99

No 42 16.01 100.0

Total 256 100.0

Graph 4.33

Data in the table and bar chart indicate that 83.99% of students perceived that parental

occupation played an important role in career decision-making process, while 16.01%

students thought that parental occupation had no role in career decision-making

process.

83.9

16.01

0

10

20

30

40

50

60

70

80

90

Yes No

Role of parental occupational characteristics in female

students' career decision-making

Table 4.34


respect to father’s occupational background characteristics influences


i. I am intended to work in my father

profession

107

(50.0)

52

(24.7)

55

(25.7)

ii. My father’s profession gives the feeling of

being respected

49

(22.9)

42

(19.6)

123

(57.6)

iii. My father’s profession gives him


59

(27.6)

35

(16.4)

120

(56.1)

iv. My father’s profession gives him feeling of

security in future

59

(27.6)

35

(16.4)

120

(56.1)

v. My father’s profession provides with an


38

(17.8)

44

(20.6)

132

(61.7)

vi. My father’s profession gives the



51

(23.8)

60

(28.0)

103

(48.1)

vii. My father’s profession gives him


his abilities

41

(19.2)

46

(21.5)

127

(59.3)

viii. My father’s profession gives more


48

(22.4)

42

(19.6)

124

(57.9)

ix. My father’s profession provides him a


52

(24.3)

26

(12.1)

136

(63.6)

x. My father’s profession gives him the


54

(25.2)

51

(23.8)

109

(50.9)

xi. My father’s profession gives him


48

(22.4)

41

(19.2)

125

(58.4)

xii. My father’s profession keeps him busy all

the time

48

(22.4)

44

(20.6)

122

(57.0)

xiii. My father’s profession gives him


36

(16.8)

55

(25.7)

123

(57.5)


Father’s Occupational Background Influences on Female Students’ Career

Decision-making

The occupational background characteristics scale was administered to female

students to assess the father’s occupational background characteristics influenced in

their career decision-making process. Students were asked to indicate their agreement

with each item in the scale. Out of 256 female students’ sample, 42 students had

denied the important role of father’s occupational influences in their career decision-

making process. These students were excluded from the analysis.

The Table 4.34 shows the different father’s occupational background characteristics

influences on female students’ career decision-making process. The findings revealed

that female students’ 25.7% had less tendency to join similar occupation as their

father. The respected dimension of father’s occupation was agreed by 57.6% female

students’, whereas 56.1% of female students had perceived the interesting and

challenging aspect of their mother’s occupation as influential in their career decision-

making. 56.1% of female students’ were influenced by future security aspect of their

father’s occupation. Moreover, high earnings satisfaction was identified as the major

determinant to explain female students’ career decision-making process for instance,

61.7% of female students reported satisfied earnings of father’s occupation as

influential, whereas 48.1% female students perceived that their father’s occupation

gave them the opportunity to earn as much as their relatives and friends earned.

Majority of female students 59.3% were believed that their father’s occupation is well

suited to the skills and abilities he possess. As compared to male students’, female

students liked their father’s occupation because it provides more advancement

opportunities. Most of female students 57.9% do consider the pleasant working

conditions aspect of their father’s occupation in their career decision-making process.

The father’s occupation attribute of getting full credit of whatever work he done had

influenced 50.9% of female students in their decision. 58.4% of female students liked

their father’s occupation because it provides independently working opportunities.

Moreover, 57.0% male students agreed and perceived their father’s occupation keeps

him busy all the time, while 57.5% female were liked their father’s occupation

because it provides an opportunity to serve the people.

Table 4.35


respect to mother’s occupational background characteristics influences


i. I am intended to work in my mother’s

profession

17

(40.5)

16

(38.1)

9

(21.4)

ii. My mother’s profession gives the feeling

of being respected

4

(9.5)

9

(21.4)

29

(69.0)

iii. My mother’s profession gives him


9

(21.4)

6

(14.3)

27

(64.3)

iv. My mother’s profession gives him feeling


7

(16.7)

8

(19.0)

27

(64.3)

v. My mother’s profession provides with an


7

(16.7)

7

(16.7)

28

(66.7)

vi. My mother’s profession gives the



13

(31.0)

8

(19.0)

21

(50.0)

vii. My mother’s profession gives him the


his abilities

7

(16.7)

9

(21.4)

26

(61.9)

viii. My mother’s profession gives more


3

(7.1)

4

(9.5)

35

(83.3)

ix. My mother’s profession provides him a


6

(14.3)

12

(28.6)

24

(57.1)

x. My mother’s profession gives him the


4

(9.5)

8

(19.0)

30

(71.4)

xi. My mother’s profession gives him


6

(14.3)

10

(23.8)

26

(61.9)

xii. My mother’s profession keeps him busy all

the time

4

(9.5)

6

(14.3)

32

(76.2)

xiii. My mother’s profession gives him


11

(26.3)

13

(31.0)

18

(42.9)


Mother’s Occupational Background Characteristics Influences on Female

Students’ Career Decision-making.

The occupational background characteristics scale was administered to female

students to assess mother’s occupational background characteristics influences in their

career decision-making process. Students were asked to indicate their agreement with

each item in the scale. Out of 256 female students’ sample, only 42 female students’

were exposed to statistical analysis because they had working mother’s only.

The Table 4.35 shows the different mother’s occupational background characteristics

influences. The data indicates that 40.5% of female students had no intention to purse

similar career as their mother. 69.0% of female students liked the respectable attribute

of their mother’s occupation. Whereas, 64.3% of female students were influenced by

the interesting and challenging dimension of their mother’s occupation. Majority of

male students 64.3% endorsed that they had considered the future security aspect of

their mother’s occupation while making their career decision. Earnings satisfaction

was emerged from the data and 66.7% of male students identified as influential

determinant of their career decision, whereas 50.0% female students perceived that

their mother’s occupation gives her the opportunity to earn as much as their relatives

and friends earned.

Moreover, 61.9% of female students reported a match between mother’s occupation

and the skills and abilities she had. The advancement opportunities associated with

mother’s occupation emerged as the strong determinant to explain the female students

83.3% career decision-making process. For 57.1% female students the pleasant

working conditions aspect of their mother’s occupation was influential element of

their decision, whereas 74.4% of female students liked their mother’s occupation

because of receiving full credit of whatever work she done. 61.9% of female students

were influenced by the independently working opportunities characteristics of

mother’s occupation. 76.2% of female students perceived that their mother’s

occupation kept her busy all the time, while 42.9% of female students liked their

mother’s occupation because it gives her the opportunity to serve the people.

Table 4.36

Frequency and percentage distribution of male students’ responses regarding



Yes 227 88.67 88.67

No 29 11.33 100.0

Total 256 100.0

Graph 4.36

The data in the table and bar chart presentation show that majority of students 88.67%

had agreed that peer group played an influential role in their career decision-making

process, whereas 11.33% students had disagreed and they disregard the role of peer

group in career decision-making process.

88.67

11.3

0

10

20

30

40

50

60

70

80

90

100

Yes No

Role of peer group in male students' career decision-

making

Table 4.37


to peer group influences


i. I have friend(s) in the career 68

(30.0)

14

(6.2)

145

(63.9)

ii. I have friend(s) that I can depend on

him/her for help

59

(26.0)

21

(9.3)

147

(64.8)

iii. I have discussed and consulted with

him/her about own choice of career

43

(18.9)

29

(12.8)

155

(68.3)

iv. My friend(s) have helped me in choosing

this career

51

(22.5)

27

(11.9)

149

(65.6)

v. I have selected the career what my

friend(s) have suggested

62

(27.3)

37

(16.3)

128

(56.4)

vi. All of my friends have agreed to select the

same career in higher secondary level

60

(26.4)

34

(15.0)

134

(58.6)

vii. Successful story of my friend(s) have


55

(24.2)

48

(21.1)

124

(54.6)

viii. I would have chosen another career if did

not discussed with my friend

69

(30.4)

32

(14.7)

126

(55.5)

ix. My friend(s) have influenced own career

decision

74

(32.6)

33

(14.5)

120

(52.9)

x. I am not engaged in the career what my

friend(s) have chosen for me

113

(49.8)

35

(15.4)

79

(34.8)


Peer Group Influences on Male Students’ Career Decision-making

Peer group influences were assessed on 10 item scale and students responses were

captured on five point Likert scale 1 “strongly disagree” to 5 “strongly agree”. For the

analysis purpose the response categories were further reduced to three categories i.e.

“disagree” “neutral” and “agree”. Students were asked to indicate their agreement

with each item in the scale. The scale items include such as “I have a friend in the

career”, I have friend(s) that I can depend on him/her for help”, “My friend(s) have

helped me in choosing this career”, “ I have selected the career what my friend(s) have

suggested” etc. Of the 256 male students’ sample, 29 students had denied the peer

group influences in their career decision-making process. These students were not

included in the final analysis. The findings are summarized as under;

In Table 4.37 presents the peer group effects on male students’ career decision

making. It is understandable fact that students’ imitate their peers in many ways.

Findings in the table show that had friend(s) in the career increases probability for

male students’63.9% to choose similar career as of their friends. Similarity in career

choices are the realization of proximity of peer group relationship. Of 64.8% male

students reported that they depended on their friends for any kind of help. Majority of

students 68.3% had have consulted their career choice with their friends, whereas

65.6% students reported that their friends had help out them in their career choice

process. Majority of students 56.4% had selected the career what their friends had

suggested. The findings also show that most of students 58.6% followed their group

decision in their career decision. Peer group were emerged as the shaper of male

students aspirations for instance, storytelling had shaped the students 54.6%

perceptions about a particular career option.

The findings also revealed that group ties played an important role to restrict male

students 55.5% to some fields than other. 52.9% of students realized that their network

of friends was a major determinant to explain their career decision. Moreover, 49.8%

students stated that they are engaged in the career what their friends had chosen for

them. In summary the findings presented an overall picture of peer group influences

in students’ decision-making process. It is argued that network of friends is a source

of social, cultural and educational capital and played a vital role to shape the students

behaviours and attitudes which resultantly change the students’ life choices including

their educational choices.

Table 4.38

Frequency and Percentage distribution of female students’ responses regarding



Yes 245 95.71 95.71

No 11 4.29 100.0

Total 256 100.0

Graph 4.38

Data in the table and bar chart show that majority of female students 95.71% believed

that peer group had an important role in determining their career choices. Only 4.29%

students denied the role of peer group in career decision-making process.

95.7

4.3

0

10

20

30

40

50

60

70

80

90

100

Yes No

Role of peer group in female students' career

decision

Table 4.39


respect to peer group influences


i. I have friend(s) in the career 78

(31.2)

15

(6.1)

152

(62.0)

ii. I have friend(s) that I can depend on

him/her for help

57

(23.3)

32

(13.1)

156

(63.7)

iii. I have discussed and consulted with

him/her about own choice of career

61

(24.9)

30

(12.2)

154

(62.9)

iv. My friend(s) have helped me in choosing

this career

55

(22.4)

29

(11.8)

161

(65.7)

v. I have selected the career what my

friend(s) have suggested

67

(27.3)

27

(11.0)

151

(61.6)

vi. All of my friends have agreed to select the

same career in higher secondary level

54

(22.0)

42

(17.1)

149

(60.8)

vii. Successful story of my friend(s) have


47

(19.2)

28

(11.4)

170

(69.4)

viii. I would have chosen another career if did

not discussed with my friend

55

(22.4)

29

(11.8)

161

(65.7)

ix. My friend(s) have influenced own career

decision

52

(21.7)

27

(11.0)

166

(67.8)

x. I am not engaged in the career what my

friend(s) have chosen for me

107

(43.7)

41

(16.7)

97

(39.6)


Peer Group Influences on Female Students’ Career Decision-making

The peer group influences scale was administered to female students to explore the

peer group influences in their career decision-making process. Out of 256 female

students’ sample, 11 students disregarded the peer group influences in their career

decision. These students were excluded from the analysis. The findings are

summarized as under;

The Table 4.39 shows that friends in the career were emerged as the strong

determinant to explain female students 62.0% career choices. Across gender, both

male and female students had the tendency to enrol in the similar career of their

friends. Relatively female students 63.7% were more dependent on their peers. The

data also demonstrated that female students 62.9% had more discussion and

consultation with their friends about their career choices process. Unlike male

students, peer group were more helpful for female students 65.7% to choose the most

appropriate career for their future. Group conformity was more pronounced among

female students as 61.6% selected the peers suggested career, whereas 60.8%

followed the collective decision in their career decision-making process. It indicates

that the fear of to be ostracize from the group serves as a motivating factor among the

female students to follow the group decision.

Female students’ perceptions about career were much shaped by their peers’

successful storytelling. It was emerged as the main predictor of students’ career

decision making process for instance, 69.4% female students reported it as the strong

determinant to explain their career choice process. It was depicted from the data that

majority of female students 65.7% agreed that they would have chosen another career

if did not discussed with their friends. Moreover, 67.8% of female students had

confirmed the peer influences in their decision, whereas 43.7% were engaged in the

career what their friends had chosen for them.

In summary, the descriptive findings of the study suggested a strong peer group effects

on students career decision-making at higher secondary level and both male and

female students were differently effected in the decision-making process. Contrary to

male students, female students were more sensitive to peer group influences and on

the odds to imitate their peer group in the decisions. For both students peer group

clinches serve as a source of social and educational capital.

Table 4.40


to gender differences role in career decision-making


Yes 197 76.95 76.95

No 59 23.04 100.0

Total 256 100.0

Graph 4.40

Data in the table and bar chart presentation show that majority of students 76.95%

perceived that gender had played an important role in influencing one’s career choice,

while 23.04% of students believed that gender was not influencing factor in their

career decision-making process.

76.9

23.1

0

10

20

30

40

50

60

70

80

90

Yes No

Role of gender in male students' career decision

Table 4.41


to gender differences influences


i. Differences in interest areas by gender has

influenced own choice of career

81

(41.1)

21

(10.7)

95

(48.2)

ii. Differences in socio-cultural expectations

by gender has influenced own choice of

career

75

(38.1)

26

(13.2)

96

(48.7)

iii. Differences in requirements of certain

occupation have influenced own choice of

career

65

(33.0)

41

(20.8)

91

(46.2)

iv. Working condition in a certain career

suited one gender only

90

(45.7)

30

(15.2)

77

(39.1)

v. Influenced by the specific gender role

attached with own choice of career

91

(46.2)

23

(11.7)

83

(42.1)

vi. My gender is limited me to other career

options

87

(45.1)

23

(11.9)

83

(43.0)

vii. The gender stereotyping have influenced

own career choice

93

(47.2)

24

(12.2)

80

(40.6)

viii. I am engaged in the career which suited my

gender

43

(21.8)

29

(11.3)

125

(48.5)


Gender Differences Influences in Male Students’ Career Decision-making

A person gender plays a decisive role to determine one’s career for his/her future. This

gender based differences in career decision-making was assessed on 8 item scale. The

scale included items such as “Differences in interest area by gender”, “Differences in

socio-cultural expectations influences”, “Differences in requirements of certain

occupation influences”, “Working conditions influences”, “Specific gender role

attachment influences” Gender stereotyping influences” etc. Students’ responses were

captured on five point Likert scale with endpoint of “strongly disagree” to “strongly

agree”. Students were asked to indicate their level of agreement with each item in the

scale. Out of 256 male students’ sample, only 59 students were excluded from the

final analysis because of they perceived gender differences dimension not an

important aspect of their career decision. The findings are summarized as under;

The Table 4.41 shows that male students valued the differences in interest areas by

gender dimension in their decision. They had opted only for those fields where they

had personal interest 48.2%. The social-cultural expectations shaped the individual

perceptions and play a pivotal role to mould their life choices. Therefore, majority of

male students 48.7% considered it in the career choices. The occupational

requirements to some extent constrain students’ choices as shown in the data that

46.2% of male students put value on this dimension in their career decision-making

process. As it is generally believed that working conditions in certain occupations

suited one gender only. Therefore, findings shows that 39.1% of male students do

considered the working conditions dimension in their decision. The findings also

demonstrate that specific gender role attachment may not influenced the male

students’ 42.1% career decision process. Male students made their decision

independent of this effects. Majority of male students had reported that their gender

had a very weak effects 43.0% on their choices, whereas 40.6% of male students had

denied the gender stereotyping effects in the career decision-making process. Majority

of male students 48.5% reported that they had chosen the career that suited their

gender only.

Table 4.42


respect to gender differences role


Yes 219 84.76 84.79

No 39 15.24 100

Total 256 100

Graph 4.42

The data in the table and bar chart show that majority of female students 84.76%

thought that gender differences has an important role in shaping their career decision-

making, while 15.24% of students believed that gender differences has no role in one’s

career decision-making process.

84.76

15.24

0

10

20

30

40

50

60

70

80

90

Yes No

Role of gender influences in female students' career

decision-making

Table 4.43


respect to gender differences influences


i. Differences in interest areas by gender has


64

(29.5)

37

(17.1)

116

(53.5)

ii. Differences in socio-cultural expectations

by gender has influenced own choice of

career

46

(21.2)

24

(11.1)

147

(67.7)

iii. Differences in requirements of certain

occupation have influenced own choice of

career

42

(19.4)

43

(19.8)

132

(60.8)

iv. Working condition in a certain career

suited one gender only

56

(25.8)

35

(16.1)

126

(58.1)

v. Influenced by the specific gender role

attached with own choice of career

57

(26.3)

44

(20.3)

116

(53.5)

vi. My gender is limited me to other career

options

57

(26.3)

44

(20.3)

116

(53.5)

vii. The gender stereotyping have influenced

own career choice

69

(31.8)

45

(20.7)

103

(47.5)

viii. I am engaged in the career which suited my

gender

37

(17.1)

40

(18.4)

140

(64.5)


Gender Differences Influences in Female Students’ Career Decision-making

The gender differences influences scale was employed to female students to assess

the different gender differences influences in their career decision-making process.

Out of 256 female students sample, 39 students were excluded from the analysis

because of they denied the gender differences dimension as an important aspect in

their career choice process. These students were not the part of final analysis. Detail

of the findings are summarized as under;

The Table 4.43 shows the different gender based influences that either restrict or ease

opportunities to the students to choose one career over other. Comparatively female

students 53.5% were more likely influenced by the differences in interest areas by

gender dimension in their career decision. Female students’ career choices were

bounded by socio-cultural expectations (67.7%). It indicates that female students do

consider their traditional role while making their career decision. Unlike male

students, differences in requirements of certain occupation were emerged as a major

determinant to explain female students’ 60.8% career decision-making process. The

findings also demonstrated that female students 58.1% were enrolled in those fields

where working conditions suited their gender only.

The feminine role associated within the career to a large extent explain female

students choices for instance, 53.5% of female students opted in those fields which

have associated with specific gender role in the career. Majority of female students

53.5% reported that they their gender had limited their career options, while 47.5% of

students reported that they had influenced by the gender stereotyping in their decision.

Moreover, most of female students 64.5% were engaged in the career which suited

their gender only. In summary gender differences were apparently reflected from the

findings and both male and female students were differently influenced in their career

choice process. The social-cultural norms reinforce differences between male and

female students. Contrary to male students, female students considered their feminine

role in their career decision-making process and had the tendency to choose those

fields for their future which suited their gender only.

Table 4.44




Yes 224 87.5 87.5

No 32 12.5 100.0

Total 256 100.0

Graph 4.44

Data in the table and bar chart presentation show that majority of male students 87.5%

endorsed that psychological factors had played an important role to determine their

career decision-making at higher secondary level. Whereas 12.5% of students denied

the importance of psychological factors in career decision-making process.

87.5

12.5

0

10

20

30

40

50

60

70

80

90

100

Yes No

Role of psychological fatcors in male students' career

decision

Table 4.45


psychological influences in career decision-making


i. I have free choice to make my career

decision

46

(20.5)

83

(37.1)

95

(42.4)

ii. I have personal interest in the career 61

(27.2)

68

(30.4)

95

(42.4)

iii. My own skills, competencies and abilities 40

(17.9)

75

(33.5)

109

(48.7)

iv. It was a chance, luck or circumstances only 65

(29.0)

83

(37.1)

76

(33.9)

v. Easy access to this particular career 62

(27.7)

69

(30.8)

93

(41.5)

vi. Lack of access to or information of other

career option

69

(30.8)

58

(25.9)

97

(43.3)

vii. Teacher(s) motivation to choose this

particular career

80

(35.5)

41

(18.1)

105

(46.5)

viii. The school I have attended have influenced

my career decision

79

(35.0)

46

(20.4)

101

(44.7)


Psychological Factors Influences on Male Students’ Career Decision-making

Different psychological factors influences were assessed on eight item scale, students

responses were measured on five point Likert scale with endpoints of “strongly

disagree” to “strongly agree”. For analysis purpose the responses categories were

further reduced to three points i.e. disagree, neutral and agree. The scale was

administered to those students who perceived the importance of psychological factors

influences in their career decision-making. Therefore, the scale was employed to 225

male students, whereas the remaining 32 students were excluded from the analysis.

The scale included statements such as had free choice in career decision; personal

interest in the career; had their own skills, competencies and abilities; due to chance,

luck or circumstances; easy access to this particular career; lack of access to or

information of other career options; teacher motivations influences; and school

attendance influences in career decision-making process. The findings of the Table

4.45 are summarized as under;

The findings of descriptive analysis show that majority of male students 42.4%

reported that they had free choice of making their career decision. It shows that most

of the students were independent in their decision and they had the freedom to choose

their desired field of study for their future. 42.4% students were motivated by their

personal interest and had chosen the field of study what they liked the most. It is

evidently depicted from the data that students own skills, competencies and abilities

to a large extent had determined their prospective career trajectories (48.7%). Findings

of item two and three in the scale show that majority of students made their career

decision on the basis of their cognitive ability and they put high value on their personal

interest, skills, competencies and abilities. The influence of serendipitous events

(33.9%) such as chance, luck or circumstances had week effects to influence students’

career decision-making process. 41.5% students endorsed the “easy access to this

particular career” influences in their career selection process, whereas 43.3% students

opposed that they had lack of access to or information about other career options. It

indicates that majority of students had access to career related information and they

had made a well-informed career decision for their future. The findings further

revealed that most of students were motivated by their teacher(s), while 44.7%

students choose their current career because of institutional influences in their career

decision-making process.

Table 4.46

Frequency and percentage distribution of female students’ responses regarding



Yes 235 91.79 91.79

No 21 8.20 100

Total 256 100.0

Graph 4.46

Data in the table and bar chart presentation indicate that majority of female students

91.79% were perceived that psychological factors had played an important role to

shape their career decision, while 8.20% of female students disregard the importance

of psychological factors in career decision-making.

91.79

8.20

0

10

20

30

40

50

60

70

80

90

100

Yes No

Role of psychological factors influences in female

students' career decision

Table 4.47


psychological factors influences


i. I have free choice to make my career

decision

88

(34.4)

82

(34.9)

65

(27.7)

ii. I have personal interest in the career 55

(23.4)

50

(21.3)

130

(55.3)

iii. My own skills, competencies and abilities 39

(16.6)

47

(20.0)

149

(63.4)

iv. It was a chance, luck or circumstances only 65

(27.7)

58

(24.7)

112

(47.7)

v. Easy access to this particular career 48

(20.4)

48

(20.4)

139

(59.1)

vi. Lack of access to or career related

information

56

(23.8)

39

(16.6)

140

(59.6)

vii. Teacher(s) motivation to choose this

particular career

50

(21.3)

30

(12.8)

155

(66.0)

viii. The school I have attended have influenced

my career decision

51

(21.7)

48

(20.4)

136

(57.9)


Psychological Factors Influences on Female Students’ Career Decision-making

The psychological factors influences were measured on eight item scale; students

were asked to indicate their level of agreement with each item (e.g. “I have free choice

to make career decision”, “I have personal interest in the career”, “My own skills,

competencies and abilities”, “It was a chance luck or circumstances only”, “easy

access to this particular career”, Lack of access to or career related information” and

“It was teacher(s) motivation to choose this particular career”) on five point Likert

scale the students responses were captured with endpoints of “strongly disagree” to

“strongly agree”. On the basis of mean score of similar response categories, new

response categories (disagree, neutral and agree) were created for analysis purpose.

Out of 256 female students’ sample, 21 students disregard the psychological factors

influences in their career decision-making process. These students were excluded

from descriptive analysis.

The findings of the Table 4.47 indicate that contrary to male students, female students

27.7% had less freedom in their career decision-making process. This observed

disparities in decision-making style is due to the fact that female students kept many

considerations, while making their decision. Personal interest dimension was more

pronounced in female students’ decision 55.3% than male students. Majority of

female students had chosen their career because of their personal preferences.

Moreover, high percentage of students 63.4% perceived themselves either competent

or had the skills and abilities needed in the career. It indicates that female students had

high self-efficacy than their counterparts. As compare to male students, serendipitous

events had greater influences on female students’ 47.7% career selection process

whereas, 59.1% of students had reported that they had easy access to choose this

particular career for their future. Majority of female students 59.6% believed that they

had difficulties in making career decision. Teacher(s) emerged as an important

individual to shape the female students’ career choices; majority of female students

66.0% got inspirations from their teachers. Institutional effects was also to some

degree 57.9% do explain and determine the female students’ career decision-making

process.

Table 4.48


the role of economic factors in career decision-making


Yes 248 96.87 96.87

No 8 3.12 100.0

Total 256 100.0

Graph 4.48

Data in the table and graph presentation indicate that majority of male students

96.87% were perceived the economic factors influences had played a decisive role to

shape their career decision, while 3.12% of male students denied the importance of

economic factors in career decision-making.

96.87

3.12

0

20

40

60

80

100

120

Yes No

Role of economic factors influences in male students'

career decision

Table 4.49


to economic factors influences in career decision-making


i. More labour market participation

opportunities

76

(30.6)

38

(15.3)

134

(54.0)

ii. More financial rewards associated with

career

78

(30.5)

35

(14.1)

135

(54.4)

iii. It will enable me to run my own business 59

(23.8)

38

(15.3)

151

(60.9)

iv. I want to be a successful person in the

future

35

(14.1)

18

(7.3)

195

(78.6)

v. Quality of life associated with this career 53

(21.4)

31

(12.5)

164

(66.1)

vi. Achieving high social status in society 55

(22.2)

20

(8.1)

173

(69.8)

vii. Society considers it prestigious 60

(24.2)

39

(15.7)

149

(60.1)


Economic Factors Influences in Male Students’ Career Decision-making

The economic factors influences were assessed on seven item scale and students’

responses were captured on five point Likert scale ranging from “strongly disagree”

to “strongly agree”. Students were suggested to show their level of agreement on each

item in the scale. The scale was employed to those students who perceived the

economic factors influences in their career decision-making process. Therefore, 8

male students in the sample were excluded from the analysis because they had not

considered the economic factors influences in their decision. The findings of

descriptive analysis are summarized as under;

Findings from the Table 4.49 presented that opportunity structure to a large extent

determine the students anticipated future career options. For instance, 54.0% of

students do consider the prospective labour market opportunities in their career

selection process. Of the 54.4% male students in the sample were more concerned

about the earnings aspect of their career choices. Relatively, they had chosen lucrative

fields and want to be well-off in the future. Moreover, the findings also demonstrated

that high percentage of students (60.9%) were expected to run their own business in

the future. It indicates that students expected to end up in those fields that instil those

qualities that enable them to start their own business in the future. Majority of students

78.6% were determined to be a successful person in the future. It seemed that students

had associated high expectations while they had chosen field of study for their future.

The associated quality of life dimension had attracted many students 66.1% to some

particular fields than others. It indicates that students opted in those fields that had the

desired potential quality of life in the future. Majority of students 69.8% had regarded

the “achieving high social status” dimension in their career. It is generally believed

that some occupations are more respected than other and people avoiding to choose

such occupations that are positioned at the lower rung of the ladder. It is evidently

reflected from the findings that most of students 60.1% valued this dimension in their

career decision at higher secondary level.

Table 4.50


the role of economic factors influences


Yes 245 95.71 95.71

No 11 4.29 100.0

Total 256 100.0

Graph 4.50

Data in the table and bar chart presentation indicate that majority of female students

96.71% were believed that economic factors had played an important role to shape

their career decision, while 4.29% of female students denied the importance of

economic factors in their career decision-making.

95.71

4.29

0

20

40

60

80

100

120

Yes No

Role of economic factors influences in female students'

career decision

Table 4.51


respect to economic factors influences


i. More labour market participation

opportunities

57

(23.3)

42

(17.1)

146

(59.6)

ii. More financial rewards associated with

career

67

(27.3)

61

(24.9)

117

(47.8)

iii. It will enable me to run my own business 62

(25.7)

44

(18.0)

139

(56.7)

iv. I want to be a successful person in the

future

35

(14.3)

25

(10.2)

185

(75.5)

v. Quality of life associated with this career 42

(17.1)

45

(18.4)

158

(64.4)

vii. Achieving high social status in society 29

(11.8)

31

(12.7)

185

(75.2)

viii. Society considers it prestigious 32

(13.1)

64

(26.1)

149

(60.8)


Economic Factors Influences on Female Students’ Career Decision-making

The economic factors influences on female students’ career decision-making were

assessed on 7 item scale and students’ responses were captured on five point Likert

scale with endpoints of “strongly disagree” to “strongly agree”. Students were asked

to indicate their level of agreement with each item. Of the 256 female students’

sample, 11 students had denied the economic factors influences in their career

decision-making process. These students were not included in the final analysis. The

findings from descriptive analysis are summarized as under;

In Table 4.51 the findings are presented which shows overall economic factors

influences on female students career decision-making process. Unlike male students,

opportunity structure emerged as more influential on female students’ choices. As

59.6% of female students had reported it as one of the determinants of their current

career choices. It indicates that female students are more curious about labour market

participation opportunities and expected to participate in a greater degree in the future.

The findings report that female students 47.8% had lower earnings expectations than

male students. The lower earnings estimation of female students are always remain a

concern in a traditional society. Like in any traditional society, the day-to-day social

life are regulated by sanctions and cultural norms that reinforce differences between

males and females resulting variation in their perceptions.

The findings also revealed that majority of female students 56.7% were interested to

run their own business in the future. Moreover, a high percentage of female students

75.5% were highly ambitious about their future and expected to be a successful person

in the future. The associated quality of life within the career 64.4% were found as a

major determinant to explain the career decision-making process of female students.

Female students 75.2% do prefer those fields of study that provide high social status

in society. Whereas, table data also shows that societal prestigious of a career 60.8%

to a large extent explained the career decision-making process of female students.

4.3 Bivariate Analysis

In order to ascertain relationship between dependent variable i.e. career decision

making and independent variables i.e. parental education, parental income, parental

occupational background characteristics, family background influences, peer group

influences, gender differences, psychological influences and economic factors

influences the bivariate analysis was conducted to explore that whether association of

relationships exist between variables or not.

4.4 Reliability

The researcher has test the internal reliability of each items used in the current study

through Cronbach α alpha. Calculating Cronbach α is a common practice in social

sciences research and employs when researcher intended to estimate the internal

consistency of reliability of a test or scale. It helps the researcher to estimate reliability

of a construct that will ensure that items are correlated and inter-relatedness. The value

of Cronbach α from 7.00 to 1.00 indicates that items have high correlation and

consistent with each other, whereas lesser value indicates low correlation among the

items. The Table 4.4 shows the calculated values of Cronbach α for the items used in

present study.

Table 4.52 Summary of Reliability Estimate

Measurement Scale for Variable

Item

Mean

Standard

Deviation

Cronbach

α

Father’s Education 6 2.65 1.237 -

Mother’s Education 6 1.88 1.095 -

Father’s Income 6 3.35 1.176 -

Mother’s Income 6 2.70 1.239 -

Family Background Influences 11 2.17 - .863

Fathers’ Occupational Characteristics 13 2.43 - .914

Mothers’ Occupation Characteristics 13 2.37 - .893

Peer Group Influences 10 2.55 - .848

Gender Differences 8 2.17 - .793

Psychological Influences 7 2.20 - .878

Economic factors Influences 5 2.48 - .832

(-) value in table indicates that SD or Cronbach α test is not applicable

CONTINGENCY TABLE 4.1

Ho: There is no relationship between parental education and students’ career decision-

making.

H1: Parental education is likely to be related to students’ career decision-making.

Table 4.1.1

Association between parental education and male students’ career decision-

making

Parental Education Career Decision-making Total

Pre

Medical

Pre-

Engineering

General

Group

Commerce

Elementary Education 19

(22.5)

7

(22.5)

32

(22.5)

32

(22.5) 90

Secondary Education 18

(20.5)

21

(20.5)

22

(20.5)

21

(20.5) 82

College Education 19

(12.3)

20

(12.3)

5

(12.3)

5

(12.3) 49

University Education 8

(8.8)

16

(8.8)

5

(8.8)

6

(8.8) 35

Total 64 64 64 64 256

Values in Table indicate fo while values in parenthesis indicate fe

χ2 = 45.430, df = 9, p< .000, V= .243

Chi-Square test indicates significant result at 5% level

Diagram 4.1.1

0

5

10

15

20

25

30

35

Pre-medical Pre-engineering General Group Commerce

Pa

ren

tal

Ed

uca

tio

n I

nfl

uen

ces

Career Decision-making

Elementary Edu

Secondary Edu

College Edu

University Edu

Bivariate analysis was conducted for establishing association of relationships between

parental education and students’ career decision-making. Parental education was

categorised in four groups’ i.e. elementary education, secondary education, college

education and university education. Students were suggested to score the highest level

of education completed by their father and mother. For analysis purpose a new

category of variable was created, based on the mean score of father’s and mother’s

level of education. Question was phrased ‘‘please skip this item’’ if student had no

parent(s) or parents had no educational background.

Out of 256 male students sample, one student was not included in the analysis because

of either had no parents or had no parental education. Chi-square test was employed

to examine whether parental level of education determine the career decision-making

of students or not. The strength and direction of relationship between variables were

further validated by employing the Cramer’s V statistical test.

The Table 4.1.1 indicates the χ2 analysis and suggested that there is a significant

association of relationship between parental level of education and male student’s

career decision-making (χ2 = 45.430, df = 9, p< .000). The calculated value of χ2 is

greater than the table value with 12 degree of freedom at 5% level of significance and

the corresponding p-value is approximately zero, which shows that both the variables

are strongly dependent and there is a significant association of relationships between

variables in question. Strength and direction of relationship between variables were

further confirmed by applying Cramer’s V test (V= .243), which indicates positive

moderate relationship between variables. It has been concluded from the analysis that

parental level of education plays an important role to influence the male students’

career decision-making process. The results of Chi-square analysis supported the

research hypothesis H1 that parental education is likely to be related to students’ career

decision-making at higher secondary level.

Table 4.1.2

Association between parental education and female students’ career decision-

making

Parental Education Career Decision-making Total

Pre

Medical

Pre-

Engineering

General

Group

Commerce

Elementary Education 15

(18.8)

10

(18.8)

25

(18.8)

25

(18.8) 78

Secondary Education 30

(21.8)

19

(21.8)

21

(21.8)

17

(21.8) 87

College Education 14

(17.8)

28

(17.8)

12

(17.8)

17

(17.8) 71

University Education 5

(5.8)

7

(5.8)

6

(5.8)

5

(5.8) 23

Total 64 64 64 64 256


χ2 = 22.624, df = 9, p < .007, V= .172


Diagram 4.1.2

The association of relationship between parental level of education and female

students’ career decision-making. Out of 256 female students’ sample, 2 students were

excluded from analysis, either they had parents with no educational background or

had no parent(s).

The Chi-square test was employed to examine the association of relationships between

parental level of education and female student’s career decision-making. Table 4.1.2

15

10

25 25

30

1921

17

14

28

12

17

57

65

0

5

10

15

20

25

30

35

Pre-medical Pre-engineering General group Commerce

Pare

nta

l ed

uca

tion

al In

flu

ence

s


Elementary Edu

Secondary Edu

College Edu

University Edu

indicates Chi-square results that shows that parental level of education has significant

association of relationship with female students career decision-making (χ2 = 22.624,

df = 9, p < .007, V= .172). The calculated value of χ2 is greater than the table value

with 9 degree of freedom at 5% level of significance and the corresponding p-value is

greater than .05, which shows that both the variables are strongly dependent and there

is significant association of relationships between the variables in question.

From the analysis of Table 4.1.1 (χ2 = 45.430, df = 9, p< .000) and 4.1.2 (χ2 = 22.624,

df = 9, p < .007)., it has been concluded that parental level of education do affect the

male students’ choices at higher secondary level and had an important role in

determining students’ career decision-making. The association of relationship was

robust for male students than female students. It shows that male students do consider

the parental level of education in their career decision more than female students. In

comparison of father’s and mother’s level of educational influences it was found that

the influence of father’s level of education was stronger (male students χ2 = 59.701,

df = 9, p < .000, V= .279 and female students χ2 = 30.927, df = 9, p < .000, V= .201)

than mother’s level of education (male students χ2 = 26.182, df = 9, p < .002, V= .197

and female students χ2 = 8.807, df = 9, p < .455, V= .110). It is pertinent to deduce

from the analysis that majority of students take their father’s level of education as a

point of reference for further education. The findings supported the research

hypothesis (H1) that parental education is likely to be related to students’ career

decision-making at higher secondary level. Therefore, the (Ho) is rejected and (HA) is

accepted.

CONTINGENCY TABLES 4.2

Ho: There is no relationship between parental income and students’ career decision-

making.

H1: Parental income is likely to be related to students’ career decision- making.

Table 4.2.1

Association between parental income and male students’ career decision-

making

Parental Income Career Decision-making Total

Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Up to 10000 5

(7.9)

5

(7.6)

16

(7.9)

5

(7.6) 31

11000-20000 5

(14.2)

5

(13.8)

18

(14.2)

28

(13.8) 56

21000-30000 14

(15.2)

17

(14.8)

19

(15.2)

10

(14.8) 60

31000-40000 14

(10.4)

17

(10.1)

5

(10.4)

5

(10.1) 41

41000 and above 26

(16.3)

18

(15.7)

6

(16.3)

14

(15.7) 64

Total 64 62 64 62 252


χ2 = 66.616, df = 12, p < .000, V= .297


Diagram 4.2.1

5 5

16

55 5

18

28

14

17

19

10

14

17

65

26

18

6

14

0

5

10

15

20

25

30


Pa

ren

tal

Inco

me

Infl

uen

ces


Up to 10000

11000-20000

21000-30000

31000-40000

41 and above

Bivariate analysis was conducted for establishing association between parental

income and students’ career decision-making. Parental income was categorised in five

groups ranging from up to 10000, 11000-20000, 21000-30000, 31000-40000 and

41000 and above. Students were suggested to score their father’s and mother’s

monthly income or earnings. Question was phrased ‘‘please skip this item’’ if student

belong from single parent families, parents had no earning or had no parents.

Table 4.2.1 shows association of relationships between parental income and male

students’ career decision-making. Out of 256 male students’ sample, 4 students were

excluded from the final analysis because of either they had no parents or residing

within single parent families.

The Chi-square results suggested that parental income has statistically significant

association of relationship with male student’s career decision-making (χ2 = 66.616,

df = 12, p < .000). The calculated value of χ2 is greater than the table value with 12

degree of freedom at 5% level of significance, the corresponding p-value is

approximately zero, which shows that both the variables are strongly dependent and

there is a significant association of relationship between variables in question.

Cramer’s V test was carried out to test the strength and direction of relationship. The

value of Cramer’s V (V= .297) suggested a moderate positive relationship between

variables. It has been concluded from the analysis that parental income plays an

important role to influences the career decision-making process of male students. The

results of Chi-square analysis supported the research hypothesis (H1) that parental

income is likely to be related to students’ career decision-making at higher secondary

level.

Table 4.2.2

Association between parental and female students’ career decision-making

Parental Income Career Decision-making Total

Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Up to 10000 8

(6.0)

6

(6.0)

5

(6.0)

5

(6.0) 24

11000-20000 14

(9.4)

5

(9.6)

14

(9.4)

5

(9.6) 38

21000-30000 19

(14.1)

17

(14.4)

15

(14.1)

6

(14.4) 57

31000-40000 8

(22.6)

25

(22.9)

21

(22.6)

37

(22.9) 91

41000 and above 14

(10.9)

11

(11.1)

8

(10.9)

11

(11.1) 44

Total 63 64 63 64 254


χ2 = 36.919, df = 12, p < .000, V= .220

Chi-Square test indicates non-significant result at 5% level

Diagram 4.2.2

The Table 4.2.2 indicates the results of association between mother’s income and

female students’ career decision-making. Out of 256 female students’ sample, only

two students were excluded from the analysis because of either they had no parents or

skipped this question.

8

65 5

14

5

14

5

19

17

15

6

8

25

21

37

14

11

8

11

0

5

10

15

20

25

30

35

40


Pare

nta

l in

com

e in

fleu

nce

s


Up to 10000

11000-20000

21000-30000

31000-40000

41000 &

above

The results of Chi-square test indicates the significant association of relationship

between parental income and students’ career decision-making (χ2 = 36.919, df = 12,

p < .000). The analysis indicates that the calculated value of χ2 is greater than the table

value with 12 degree of freedom at 5% level of significance and the corresponding p-

value is smaller than .05, which shows that both the variables are dependent and there

is a significance association of relationships between the variables in question. The

Cramer’s V test (V= .220) also indicates a moderate positive relationship between

variables. It can be concluded from the analysis that parental income plays an

important role to determine the career decision of female students. The results of Chi-

square analysis supported the research hypothesis H1 that parental income is likely to

be related to students’ career decision-making at higher secondary level.

Based on the above analysis of Table 4.2.1 (χ2 = 66.616, df = 12, p < .000) and 4.2.2

(χ2 = 36.919, df = 12, p < .000), it has been deduced that parental income do affect the

students’ choices at higher secondary level and has central role to determine students

prospective future career. Further analysis was conducted for father and mother’s

income influences on students’ career decision-making process. It was found that

father’s income has profound effects on students’ choices. Stronger association of

relationship was found for male students (χ2 = 78.693, df = 12, p < .000) than female

(χ2 = 34.629, df = 12, p < .001). Variation of effects was found between mother’s

income and students’ career decision-making. Mother’s income exerts no effects on

student’s career selection process. The evidences supported the research (H1) that

parental income is likely to be related to students’ career decision-making at higher

secondary level. Therefore, the (Ho) null hypothesis is rejected and (HA) hypothesis is

accepted.


Ho: There is no relationship between family background and students’ career decision-

making.

H1: There is a relationship between family background and students’ career decision-

making.

Table 4.3.1

Association between family background influences and male students’ career

decision-making

Family Background

Influences

Career Decision-making Total

Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 50

(38.3)

43

(36.4)

19

(37.0)

33

(33.3) 145

Neutral 5

(16.1)

9

(15.3)

34

(15.6)

13

(14.0)

61

Disagree 6

(6.6)

6

(6.6)

6

(6.4)

7

(5.7)

25

Total 61 58 59 53

231


χ2 = 46.041, df = 6, p < .000, V= .316


Diagram 4.3.1

50

43

19

33

5

9

34

13

6 6 6 7

0

10

20

30

40

50

60


Fa

mil

y b

ack

gro

un

d i

nfl

uen

ces


Agree

Neutral

Disgaree

The Table 4.3.1 shows the results of association between family background and male

students’ career decision-making. Out of 256 male students, 231 students have

endorsed the family background influences in their career decision-making.

Therefore, students who denied the family background influences were excluded from

the final analysis. The Chi-square results show statistically significant relationships

between family background and male students career decision-making (χ2 = 46.041,

df = 6, p < .000). The calculated value of χ2 is greater than the table value with 6

degree of freedom at 5% level of significance and the corresponding p-value is

approximately zero, which shows that both the variables are strongly dependent and

there is a significant association of relationships between the variables in question.

Cramer’s V statistical test was employed to determine the direction and strength of

relationship between variables. The calculated value of Cramer’s V test (V= .316)

indicates strong positive relationship between variables. It has been inferred from the

analysis that family background plays an important role to shape the career decision

of male students. The results of Chi-square analysis supported the research hypothesis

(H1) that family background is likely to be related to students’ career decision-making

at higher secondary level.

Table 4.3.2

Association between family background influences and female students’ career

decision-making

Family Background

Influences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 51

(38.1)

45

(36.3)

19

(39.3)

38

(39.0) 153

Neutral 5

(11.7)

7

(11.1)

14

(12.1)

21

(12.1)

47

Disagree 6

(12.2)

7

(11.6)

31

(12.6)

5

(12.6)

49

Total 62 59 64 64

249


χ2 = 65.757, df = 6, p < .000, V= .363


Diagram 4.3.2

The Table 4.3.2 indicates the association between family background influences and

female students’ career decision-making. Out of 256 female students’ sample, only 7

students denied the family background influences in career decision-making. Chi-

square test was conducted for 249 female students.

The Chi-square analysis shows a strong association of relationship between family

background influences and female students career decision-making (χ2 = 65.757, df =

51

45

19

38

57

14

21

6 7

31

5

0

10

20

30

40

50

60


Fam

ily b

ack

gro

un

d i

nfl

uen

ces


Agree

Neutral

Disgaree

6, p < .000). The calculated value of χ2 is greater than the table value with 6 degree of

freedom at 5% level of significance and the corresponding p-value is approximately

zero, which shows that both the variables are strongly dependent and there is a

significant association of relationships between variables in question. Direction and

strength of relationship was further analysed by employing Cramer’s V test, which

shows a very strong positive relationship between variables (V= .363). It has been

concluded from the analysis that family background plays an important role to shape

the career decision of female students. The results of Chi-square analysis supported

the research hypothesis H1 that family background is likely to be related to students’

career decision-making at higher secondary level.

From the above analysis of Table 4.3.1 and 4.3.2 it is inferred that family background

has influenced the students’ choices at higher secondary level and do play an

important role to determine students future career choices. The calculated values of χ2

in Table 4.3.1 and 4.3.2 are greater than the table value with 6 degree of freedom at

5% level of significance and corresponding p-value is approximately zero, which

signify the association of relationships between variables. From the above Chi-square

analysis it is pertinent to establish that family background to a large extent influenced

the career choices of students at higher secondary level. Unlike male, female students

valued more the family conformity in their decision-making process. The findings

supported the research hypothesis (HI) that family background is likely to be related

to students’ career decision-making. Therefore, the null hypothesis (Ho) is rejected

and alternate hypothesis (HA) is accepted.


Ho: There is no relationship between parental occupational background characteristics

influences and students’ career decision- making.

H1: Parental occupational background characteristics influences are likely to be

related to students’ career decision- making.

Table 4.4.1

Association between parental occupational background and male students’


Parental Occupational

Background Influences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 8

(7.1)

6

(7.9)

9

(5.7)

5

(7.2) 28

Neutral 36

(31.2)

32

(34.9)

14

(25.1)

41

(31.8) 123

Disagree 8

(7.1)

6

(7.9)

9

(5.7)

5

(7.2) 28

Total

51

57

41

52

201


χ2 = 25.572, df = 6, p < .000, V= .252


Diagram 4.4.1

86

9

5

36

32

14

41

86

9

5

0

5

10

15

20

25

30

35

40

45


Infl

uen

ce o

f p

aen

tal

occ

up

ati

on

al

cha

ract

eris

tics


Agree

Neutral

Disgaree

The Table 4.4.1 indicates the results of association between parental occupational

background characteristics and male students’ career decision-making. Parental

occupational background characteristics variable category was created on the basis of

mean score of father’s and mother’s occupational characteristics influences. From the

256 male students’ sample, 55 students did not qualify for the final statistical analysis.

The Chi-square results show the association of parental occupational backgrounds

characteristics and male students’ career decision-making (χ2 = 25.572, df = 6, p <

.000). The calculated value of χ2 is greater than the table value with 6 degree of

freedom and the corresponding p-value is approximately zero, which shows that both

the variable are strongly dependent and there is a significant association of

relationships between the variables in question. Cramer’s V statistic (V= .252)

indicates strong positive relationship between variables. It has been deduced from the

analysis that parental occupational background characteristics are influential on male

students’ career choice selection process and to a large extent determine their

anticipated career option. The results of Chi-square analysis supported the research

hypothesis (H1) that parental occupational background characteristics are likely to be

related to students’ career decision-making at higher secondary level.

Table 4.4.2

Analysis of bivariate relationship between parental occupational influences and

female students’ career decision-making

Parental Occupational

Background Influences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 7

(7.6)

6

(8.3)

14

(8.2)

5

(7.9) 32

Neutral 32

(30.2)

33

(33.6)

22

(33.0)

42

(31.8) 129

Disagree 12

(12.8)

17

(14.1)

19

(13.8)

6

(13.3) 56

Total

51

56

55

53

215


χ2 = 19.527, df = 6, p < .003, V= .213

Chi-Square test indicates non-significant result at 5% level

Diagram 4.4.2

The Table 4.4.2 indicates the association of parental occupational background

characteristics and female students’ career decision-making. Female students who had

either both parents not working or denied the parental occupational background

76

14

5

3233

22

42

12

17

19

6

0

5

10

15

20

25

30

35

40

45

Pre-medical Pre-engineering General group Commerce

Infl

uen

ce o

f p

aen

tal

occ

up

ati

on

al

chara

cter

isti

cs

Career decsion-making

Agree

Neutral

Diagree

characteristics influences were not exposed to statistical analysis. Therefore, χ2

analysis was conducted for 215 female students.

The Chi-square results indicate that parental occupational background characteristics

has significant association of relationship with female students’ career decision-

making at higher secondary level (χ2 = 19.527, df = 6, p < .003). The calculated value

of χ2 is greater than the table value with 6 degree of freedom and the corresponding

p-value is smaller than .05, which shows that both the variables are dependent and

association of relationships exist between variables. The strength and direction of

relationship was further validated by Cramer’s V (.213), shows a moderate positive

relationship between the variables. It is deduced from the analysis that parental

occupational background characteristics influenced the female students’ career

decision-making process. The results of Chi-square analysis supported the research

hypothesis (H1) that parental occupational background characteristics are likely to be

related to male students’ career decision-making at higher secondary level.

Based on the above analysis of Table 4.4.1 and 4.4.2, it has been concluded that

parental occupational backgrounds characteristics explained the career decision-

making process of students at higher secondary level. Both male and female students

are on the odds to take their parental occupational status as a point of reference for

their prospected future occupations. Further analysis of the data revealed that, unlike

mother, father’s occupational background characteristics were influential of both

students (male students χ2 = 42.434, df = 6, p < .000, V= .327 and female students χ2

= 29.197, df = 6, p < .000, V= .261). It indicates that majority of students take their

father’s occupational status as a point of reference and on the odds to pursue their

career similar as their father’s occupation. The results validated the research

hypothesis that parental occupational background characteristics are likely to be

related to students’ career decision-making at higher secondary level. Therefore, the

(Ho) hypothesis is rejected and (HA) hypothesis is accepted.


Ho: There is no relationship between peer group influences and students’ career

decision- making.

H1: Peer group influences are likely to be related to students’ career decision-making.

Table 4.5.1

Association between peer group influences and male students’ career decision-

making

Peer Group Influences Career Decision-making Total

Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 30

(36.9)

34

(38.2)

44

(36.3)

39

(35.6) 147

Neutral 10

(10.8)

20

(11.2)

7

(10.6)

6

(10.4)

43

Disagree 17

(9.3)

5

(9.5)

5

(9.1)

10

(9.0)

37

Total 57 59 56 55

227


χ2 = 24.455, df = 6, p < .000, V= .232


Diagram 4.5.1

30

34

44

39

10

20

7 6

17

5 5

10

0

5

10

15

20

25

30

35

40

45

50


Pee

r g

rou

p i

nfl

uen

ces


Agree

Neutral

Disgaree

The Table 4.5.1 indicates the association of peer group influences and male students’

career decision-making at higher secondary level. Out of 256 male students’ sample,

29 students disregard the peer group influences in their career decision these students

were not included in final statistical analysis.

The Chi-square results in the table indicate a statistical significant association of

relationships between peer group influences and male students career decision-

making at higher secondary level (χ2 = 24.455, df = 6, p < .000). The calculated value

of χ2 is greater than the table value with 6 degree of freedom at 5% level of

significance. The corresponding p-value is very small approximately zero i.e. .000,

which shows that both variables are strongly dependent and there is a statistically

significant association of relationships between variables in question. Cramer’s V test

(V= .232) further predicted moderate positive relationship between variables. It has

been concluded from the analysis that peer group played an important role to shape

the career decision of male students at higher secondary level. The results supported

the research hypothesis (H1) that peer group influences are likely to be related to male

students’ career decision-making.

Table 4.5.2

Association between peer group influences and female students’ career

decision-making

Peer Group Influences Career Decision-making Total

Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 47

(35.2)

48

(35.8)

24

(36.9)

27

(38.1) 146

Neutral 7

(15.7)

7

(15.9)

29

(16.4)

22

(17.0)

65

Disagree 5

(8.2)

5

(8.3)

9

(8.6)

15

(8.9)

34

Total 59 60 62 64

245


χ2 = 43.616, df = 6, p < .000, V= .298


Diagram 4.5.2

The Table 4.5.2 indicates the peer group influences in female students’ career

decision-making process. Chi-square statistical analysis was conducted for those

female students who perceived that peer group had played an important role to

determine their career decision at higher secondary level. 11 students were excluded

from the final statistical analysis.

47 48

24

27

7 7

29

22

5 5

9

15

0

10

20

30

40

50

60


Pee

r gro

up

in

flu

ence

s


Agree

Neutral

Disgaree

The Chi-square results indicate statistically significant relationships between peer

group influences and female students’ career decision-making at higher secondary

level (χ2 = 43.616, df = 6, p < .000). The calculated value of χ2 is greater than the table

value with 6 degree of freedom at 5% level of significance. The corresponding p-value

is approximately zero i.e. .000, which shows that both the variables are strongly

dependent and there is a statistically significant association of relationships between

variables. Cramer’s V test (V= .298) indicates an approximately strong moderate

positive relationship between peer group influences and female students career

decision-making. It has been be concluded from the analysis that peer group played

an important role to influence the career decision of female students at higher

secondary level. The results supported the research hypothesis (H1) that peer group

influences are likely to be related to students’ career decision-making.

From the above analysis of Table 4.5.1 and 4.5.2, it has been concluded that peer

group had influenced the students’ choices at higher secondary level and students put

value on peer relationship in their career selection process. The calculated values of

χ2 in Table 4.5.1 and 4.5.2 are greater than the table value with 6 degree of freedom

at 5% level of significance and corresponding p-value is approximately zero, which

shows that peer group plays an important role to shape the career decision of male and

female students at higher secondary level. Results also endorsed the strong peer group

influences among female students (χ2 = 43.616) than male students. From the above

Chi-square analysis it is pertinent to establish that peer group to a large extent

influenced the career choices of students at higher secondary level. The findings

supported the research hypothesis (HI) peer group influences are likely to be related

to students’ career decision-making. Therefore, the null hypothesis (Ho) is rejected

and alternate hypothesis (HA) is accepted.


Ho: There is no relationship between gender differences and students’ career decision-

making.

H1: There is a relationship between gender differences and students’ career decision-

making.

Table 4.6.1

Association between the influence of gender differences and male students’


Influence of Gender

Differences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 12

(12.9)

5

(12.6)

8

(12.1)

28

(15.3) 53

Neutral 26

(24.9)

26

(24.3)

26

(23.3)

24

(29.5)

102

Disagree 10

(10.2)

16

(10.0)

11

(9.6)

5

(12.5)

42

Total 48 47 45 57

197


χ2 = 26.038, df = 6, p < .000, V= .257


Diagram 4.6.1

12

5

8

28

26 26 26

24

10

16

11

5

0

5

10

15

20

25

30


Infl

uen

ce o

f g

end

er d

iffe

ren

ces


Agree

Neutral

Disgaree

The results of Table 4.6.1 shows association of relationship between gender

differences and male students’ career decision making. Statistical analysis was

conducted for those students who perceived gender differences as an important

dimension of their career decision. Out of 256 male students sample, 63 students were

excluded from the final analysis because of they denied the gender differences

influences dimension in their career decision-making process.

The results of Chi-square analysis show a significant association of relationships

between gender differences and male students career decision-making process (χ2 =

26.038, df = 6, p < .000). The calculated value of χ2 is greater than the table value with

6 degree of freedom at 5% level of significance. The corresponding p-value is

approximately zero i.e. .000, which shows that both the variables are strongly


variables in question. Relationship between variables was further analysed by

employing Cramer’s V test. The calculated value of Cramer’s V test indicates (V=

.257) a moderate positive moderate relationship between variables. It is pertinent to

conclude from the analysis that gender differences played an important role to shape

the career decision of male students at higher secondary level. The results supported

the research hypothesis (H1) that gender differences influences are likely to be related

to students’ career decision-making.

Table 4.6.2

Association between the gender influences and female students’ career

decision-making

Influence of Gender

Differences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 17

(26.6)

43

(28.1)

32

(30.2)

21

(28.1) 113

Neutral 29

(17.2)

5

(18.2)

16

(19.5)

23

(18.2)

73

Disagree 5

(7.3)

6

(7.7)

10

(8.3)

10

(7.7)

31

Total 51 54 58 54

217


χ2 = 34.989, df = 6, p < .000, V= .284


Diagram 4.6.2

The Table 4.6.2 indicates the association of relationships between gender differences

influences and female students career decision-making process. Out of 256 female

students sample, 39 students were excluded from statistical analysis because of they

disregard the gender differences dimension in their career decision-making process.

17

43

32

21

29

5

16

23

56

10 10

0

5

10

15

20

25

30

35

40

45

50


Infl

uen

ce o

f gen

der

dif

fere

nce

s


Agree

Neutral

Disgaree

The results of Chi-square test indicates significant association of relationship between

gender difference influences and female students career decision-making process (χ2=


6 degree of freedom at 5% level of significance. The corresponding p-value is very

small approximately zero i.e. .000, which shows that both variables are strongly


variables in question. Cramer’s V test (V= .284) further extended the relationship and

indicates a moderate positive relationship between variables. It has been concluded

from the analysis that female students do consider the gender differences dimension

in their career decision at higher secondary level. The results supported the research

hypothesis (H1) that gender differences influences are likely to be related to students’

career decision-making.

From the above analysis of Table 4.6.1 and 4.6.2, it has been deduced that gender

differences had reportedly influenced the students’ choices at higher secondary level

and students put value on gender differences dimension in their career selection

process. The calculated values of χ2 in Table 4.6.1 and 4.6.2 are greater than the table

value with 6 degree of freedom at 5% level of significance and corresponding p-value

is approximately zero, which shows that both the students do consider the gender

differences dimension in their career decision-making. Female students (χ2 = 34.989)

were found to be more sensitive to this effects and on the odds to choose career

trajectories that reflect traditionally feminine characteristics. From the above Chi-

square analysis it is pertinent to establish that gender differences to a large extent

influenced the career choices of students at higher secondary level. The findings

supported the research hypothesis (HI) that a gender differences influences are likely

to be related to students’ career decision-making. Therefore, the null hypothesis (Ho)

is rejected and alternate hypothesis (HA) is accepted.


Ho: There is no relationship between psychological factors and students’ career

decision- making.

H1: The psychological factors influences are likely to be related to students’ career

decision- making.

Table 4.7.1

Association between psychological factors influences and male students’ career

decision-making

Psychological Factors

Influences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 42

(27.7)

23

(29.3)

18

(29.3)

32

(28.8)

115

Neutral 6

(20.0)

24

(21.1)

34

(21.1)

19

(20.8)

83

Disagree 6

(6.3)

10

(6.6)

5

(6.6)

5

(6.5) 26

Total 54 57 57 56

224


χ2 = 34.081, df = 6, p < .000, V= .276


Diagram 4.7.1

42

23

18

32

6

24

34

19

6

10

5 5

0

5

10

15

20

25

30

35

40

45


Psy

ch

olo

gic

al fa

cto

rs in

flu

ence

s


Agree

Neutral

Disgaree

The Table 4.7.1 indicates the psychological influences on male students’ career

decision-making. The statistical analysis was conducted for those students who

perceived psychological factors influences in their career decision-making process.

Therefore, 32 male students were excluded from statistical analysis.

The Chi-square test results indicate a statistically significant association of

relationships between psychological factors influences and male students’ career

decision-making (χ2 = 34.081, df = 6, p < .000, V= .276). The calculated value of χ2

is greater than the table value with 6 degree of freedom at 5% level of significance.

The corresponding p-value is very small approximately zero (p < .000), which shows

that both the variables are strongly dependent and there is a statistically significant

association of relationships between variables in question. Relationship between

variables was further analysed by employing Cramer’s V test (V= .276). Which shows

a moderate positive relationship between variables. It has been inferred from the

above analysis that psychological factors played an important role to shape the career

decision of male students at higher secondary level. The results supported the research

hypothesis (H1) that psychological factors influences are likely to be related to male

students’ career decision-making at higher secondary level.

Table 4.7.2

Association between psychological factors influences and female students’


Psychological Factors

Influences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 38

(37.2)

40

(39.8)

31

(39.8)

47

(39.2)

156

Neutral 8

(8.3)

15

(8.9)

5

(8.9)

7

(8.8)

35

Disagree 10

(10.5)

5

(11.2)

24

(11.2)

5

(11.0) 44

Total 56 60 60 59

235


χ2 = 31.068, df = 6, p < .000, V= .257


Diagram 4.7.2

The Table 4.7.2 shows the association of relationships between psychological factors

influences and female students’ career decision-making. Out of 256 female students

21 students were excluded from final statistical analysis because of they denied the

psychological factors influences in their career decision-making process. Therefore,

Chi-square test was conducted for 235 female students.

3840

31

47

8

15

57

10

5

24

5

0

5

10

15

20

25

30

35

40

45

50


Psy

cho

log

ica

l fa

cto

rs in

flu

ence

s


Agree

Neutral

Disgaree

The Chi-square results indicate a significant association of relationships between

psychological factors influences and female students’ career decision-making (χ2 =


6 degree of freedom at 5% level of significance. The corresponding p-value is



variables. Cramer’s V test was employed to further analyse the strength and direction

of relationship between variables. Cramer’s V test (V= .257) shows moderate positive

relationship between variables. It indicate that psychological factors influences to

some degree determine the female students’ choices at higher secondary level. The

results supported the research hypothesis H1 that psychological factors influences are

to be related to female students’ career decision-making.

From the above analysis of Table 4.7.1 and 4.7.2, it has been deduced that students do

consider the psychological factors influences in their career decision at higher

secondary level. As the calculated values of χ2 in Table 4.7.1 and 4.7.2 are greater

than the table value with 6 degree of freedom at 5% level of significance and the

corresponding p-value is approximately zero, It is pertinent to establish that

psychological factors influences play an important role to shape the career decision of

students at higher secondary level. Moreover, female students were found to be more

prone to psychological factors influences than their counterpart. The findings

supported the research hypothesis (HI) that psychological factors influences are likely

to be related to students’ career decision-making at higher secondary level. Therefore,

the null hypothesis (Ho) is rejected and alternate hypothesis (HA) is accepted.


Ho: There is no relationship between economic factors influences and students’ career

decision- making.

H1: The economic factors influences are likely to be related to students’ career

decision-making.

Table 4.8.1

Association between economic factors influences and male students’ career

decision-making

Economic Factors

Influences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 50

(41.0)

49

(40.5)

11

(39.8)

52

(40.5)

162

Neutral 8

(12.7)

7

(12.5)

30

(12.3)

5

(12.5)

50

Disagree 5

(9.0)

6

(9.0)

20

(9.0)

5

(9.0) 36

Total 63 62 61 62

248


χ2 = 80.658, df = 6, p < .000, V= .403


Diagram 4.8.1

50 49

11

52

8 7

30

55 6

20

5

0

10

20

30

40

50

60


Eco

no

mic

fa

cto

rs in

flu

ence

s


Agree

Neutral

Disgaree

The Table 4.8.1 shows the relationships between economic factors influences on male

students’ career decision-making process. The statistical analysis was conducted for

248 male students, the remaining 8 students were excluded from the analysis because

they disregard the economic factors influences in their career decision-making.

The Chi-square results indicate a significant association of relationships between

economic factors influences and male students’ career decision-making (χ2 = 80.658,

df = 6, p < .000, V= .403). The calculated value of χ2 is greater than the table value

with 6 degree of freedom at 5% level of significance. The corresponding p-value is



variables. Cramer’s V test was employed to further analyse the strength and direction

of relationship between variables. The test (V= .403) shows strong positive

relationship between variables which means that variables are dependent and had

effects on positive direction. It is pertinent to establish that male students highly

valued the economic dimension in the career selection process. The results supported

the research hypothesis (H1) that economic factors influences are likely to be related

to students’ career decision-making.

Table 4.8.2

Association between economic factors influences and female students’ career

decision-making

Economic Factors

Influences


Pre-

Medical

Pre-

Engineering

General

Group

Commerce

Agree 46

(39.1)

43

(39.7)

22

(38.4)

46

(39.7)

157

Neutral 8

(14.7)

9

(14.9)

23

(14.4)

9

(14.9)

59

Disagree 7

(7.2)

10

(7.3)

5

(7.1)

7

(7.3) 29

Total 61 62 60 62

245


χ2 = 42.702, df = 6, p < .000, V= .295


Diagram 4.8.2

The Table 4.8.2 shows the association of relationships between economic factors

influences on female students’ career decision-making process. The statistical

analysis was conducted for 245 female students, the remaining 11 students were

excluded from the analysis because they denied the economic factors influences in

their career decision-making process.

46

43

22

46

89

23

97

10

57

0

5

10

15

20

25

30

35

40

45

50


Eco

nom

ic f

act

ors

in

flu

ence

s


Agree

Neutral

Disgaree

The Chi-square results signify the association of relationships between economic

factors influences and female students’ career decision-making (χ2 = 42.702, df = 6, p

< .000, V= .295). The calculated value of χ2 is greater than the table value with 6

degree of freedom at 5% level of significance. The corresponding p-value is lesser

than zero i.e. .000, which shows that both the variables are dependent and a

relationship exist between the variables. Moreover, Cramer’s V test was employed to

test the strength and direction of relationship between variables. A very week positive

relationship was found between the variables (V= .295). It is pertinent to establish that

female students put less weight on economic dimension in the career selection

process. The results supported the research hypothesis (H1) that economic factors

influences are likely to be related to students’ career decision-making.

Data in the Table 4.8.1 and 4.8.2 indicate the results of χ2 analysis, which shows that

economic factors influences emerged as the predictors of students prospective career

choices at higher secondary level. As the calculated values of χ2 in Table 4.8.1 and

4.8.2 are greater than the table value with 6 degree of freedom at 5% level of

significance and the corresponding p-value is approximately zero. It can be inferred

from the analysis that economic factors influences play an important role to determine

students’ career decision-making at higher secondary level. Unlike female students,

male students (χ2 = 80.658) were found more sensitive to economic factors influences

in their carer decision-making. The findings supported the research hypothesis (HI)

that economic factors influences are likely to be related to students’ career decision-

making at higher secondary level. Therefore, the null hypothesis (Ho) is rejected and

alternate hypothesis (HA) is accepted.

CHAPTER 5

SUMMARY, CONCLUSION, LIMITATIONS, RECOMMENDATIONS AND

IMPLICATIONS

This chapter includes the summary that shows the brief description of procedures

undertaken and major findings of the study. Moreover, conclusion, limitations,

recommendations and implications are also presented in this chapter.

5.1 Summary

The aim of the present study was to investigate the determinants of career decision-

making among higher secondary level students of Karachi. The various dimensions

of career decision-making were assessed on a structured questionnaire and elicited

related information from students such as, parental education, parental occupation,

parental income, students’ knowledge and perceptions about career decision, students’

level of satisfaction about their current career, family background influences, parental

occupational background characteristics, peer group influences, gender differences,

psychological and economic factors influences. In order to obtain overall picture of

the data a descriptive analyses were conducted including the measure of central

tendency (mean and standard deviation) and graphical presentation. Cronbach’s alpha

was employed to test the degree of reliability of for items used in the thesis. The

calculated values of Cronbach’s alpha indicate a high degree of reliability for each

items (Family background = .863, Father’s occupational background characteristics =

.914, Mother’s occupational background characteristics = .893, Peer group influences

= .848, Gender differences = .793, Psychological influences = .878, economic factors

influences = .832). Bivariate analysis was carried out for establishing association of

relationship between variables in question. In order to measure the strength and

direction of relationship between independent and dependent variables, Cramer’s V

correlation coefficient was employed which shows a positive relationship between

variables.

Since the sample of the study consisted of students of higher secondary level of

Karachi. On the first stage through convenient sampling method four government

(50%) and private (50%) colleges were selected located in Karachi city. On the second

stage, stratified random sampling method was employed and an appropriate sample

size of 512 students was drawn from each stratum within population .e. Pre-medical,

Pre-engineering, General Group and Commerce (50% each). Both genders were

equally represented in the sample i.e. 50% male and 50% female. The mean age for

male students was 17.99 years and for female students 17.75 years. Majority of

students living within nuclear family (male 57.8% and female 53.5%) and because of

urban population lower percentage of students living within joint family system

(40.2% male and 45.3% female students).

The descriptive analyses show that most of students (male students 85.2% and female

students 86.3%) had prior knowledge about the career decision-making. Career

decision-making was perceived differently by the students, for instance, male students

viewed career decision-making as a choice of profession 22.1%, whereas for female

students it was the achievement of desired goals 19.9%. Moreover, all the students

agreed (male students 95.3% and female students 99.6%) on the importance of career

decision-making and considered it as a very important decision of their life. The study

results revealed that both students (male students 52.0% and female students 43.8%)

made their career decision at secondary level (9th and 10th) and no differences were

found on the basis of gender and college type. For the first choice of career, male

students (35.5%) were interested to pursue their career other than the present career

and were interested to engage in pre-engineering, pre-medical and commerce fields.

However, female students 20.3% had the tendency to pursue their career in pre-

medical, caring fields and pre-engineering. Therefore, the study found gendered

pattern of career preferences between male and female students. The findings were

consistent with Simpson (2001) and Francis et al., (2003) studies, who found that

female students are more inclined to choose creative and caring fields for their future.

The summary of the findings of main research variables are as under;

5.1.1 Parental Educational Influences

Parental education was categorized in five major groups i.e. elementary level

education, secondary level education, college level education and university level

education. The study found that majority of students’ parents had elementary level

education (male students 35.2% and female students 29.3%), secondary level

education (male students 32.0% and female students 34.0%), college level education

(male students 19.1% and female students 27.7%) and university level education

(male students 13.7% and female students 9.0%). The study also found that Pre-

medical and Pre-engineering students’ parental education was higher than Commerce

and General Group students.

It has been deduced from Chi-square analysis that across gender, parental education

exerts significant effects on students’ choices at post-secondary level. When

magnitude of effects were compared across gender it was found that for male students

the effects of parental level of education were greater (χ2 = 45.430, p < .000, V= .243)

than female students (χ2 = 22.624, p < .007, V= .172). Moreover, further analysis of

Chi-square suggests that the effects of father’s level of education was stronger and

influential than mother’s level of education, for instance, across gender Chi-square

value of father’s education was greater (male students χ2 = 59.701, p< .000 and female

students χ2 = 30.927, p< .000) than mother’s level of education (male students χ2 =

26.182, p < .002 and female students χ2 = 8.807, p <.455). It shows that most of the

students got their father’s level of education as a point of reference either for further

education or particularly for choosing a specific field of study for their future.

Differences in the effects of parental level of education on male and female students’

choices are the reflection of the fact that Pakistani society is a traditional oriented

society and gives preference to invest more in male child education than female child.

These findings of the study are consistent with previous studies which suggested that

parental years of schooling has strong effects on students secondary level track

choices and parental more years of schooling increases the probability of students to

enrol into advanced and technical fields. Although, students were differently effected

from parental education, stronger association of relationship was found for male

students but this association of relationship was weaker for female students (Ermisch

and Francesconi; 2001 and Dustmman, 2004). On the basis of the above findings it

has been deduced that education is intergenerationaly reproduced and students are on

the odds to choose the similar are more advanced field as their parents, particularly as

their father. The study found support for the research hypothesis that parental level of

education is likely to be related to students’ career-decision making at higher

secondary level.

5.1.2 Parental Income Influences

Parental income was categorized into five group i.e. up to 10,000, 11,000-20,000,

21,000-30,000 and 31,000-40,000 and 41,000 and above. The descriptive analyses

indicate the average parental income for male (mean= 3.44) and for female students

(mean = 3.53). The study found that parental income of female students were found

marginally higher than male students. Moreover, the findings also suggested that

private college students had higher parental income (mean= 3.48) than govt. college

students (mean= 3.07). It indicates that private college students were belonged from

well off families.

The bivariate analysis reported a strong association of relationship between parental

income and students’ field of study choices at post-secondary level. The analysis

suggested a large and significant effects for male students (χ2 = 66.616, p < .000, V=

.297) than female students (χ2 = 36.919, p < .000, V= .220). This gendered pattern

influences of parental income is the reflection of the fact that parents are much

inclined towards investing more in male child education because they considered it as

their economic resources are reproduced. Having invested more in male child

education parents are more likely to receive benefits in the future. Whereas, investing

in female child education decreases the probability to receive the prospective benefits.

Therefore, parents make greater investment in male child education by mobilizing all

their resources not only to complement to secure male child future career but also

provide means for upward social mobility. The study findings are supported by the

previous studies which show a significant association of relationship between parental

income and students post-secondary track choices (Goyette and Mullen, 2006; and

Trusty et al., 2000). The findings of the study lend support to research hypothesis that

parental income is associated with students’ career decision-making process at post-

secondary level.


The current study found that family background explain the students’ career decision-

making process at higher secondary level. Majority of students (90.23% of male

students and 97.26% of female students) believed that family background played an

important role in shaping their career decision at higher secondary level. Findings

from descriptive analysis show that majority of students reported that they were

persuaded by their family members (male students 54.1% and female students 43.0%),

had family member in the same field (male students 52.8% and female students

54.2%), had discussed and consulted with family members (male students 71.9% and

female students 67.5%), encouraged and supported by the family (male students

66.2% and female students 66.3%), influenced from their home environment (male

students 54.1% and female students 54.2%), family economic influences (male

students 56.3% and female students 49.0%), had family expectations (male students

64.9% and female students 61.4%), received career related information at home (male

students 64.9% and female students 60.6%), had selected the career what their family

had chosen (male students 52.8% and female students 54.2%), family already had

chosen a career (male students 36.4% and female students 31.3%), and career chosen

by family is not what I want (male students 32.9% and female students 16.9%).

The bivariate analysis suggested that students give importance to family background

while making career decision and had the tendency to make their career decisions that

conformed to familial expectations. The magnitude of effects vary by gender, for

example, greater value of Chi-square was reported for female students (χ2 = 65.757, p

< .000, V= .363) than male students (χ2 = 46.041, p < .000, V= .316). It indicates that

familial background characteristics bolstered the career selection process of female

students to make their decision more in conformity with familial expectations. The

study found that certain family factors that might potentially affect the students’ career

aspirations and expectations. These factors might be family persuasion, family

members in the field, family support and encouragement, family economic resources,

family expectations and access to valuable career related information. It has been

inferred from the analysis that family background shaped the students choices at post-

secondary level by introducing both the opportunities and constrained associated

within each career options. However, compared the value of Chi-square analysis it

was evidently depicted that male students give lower ratings to familial influences in

their career decision than female students. It may be due to the family traditions and

cultural reinforcement that precipitate female students in their decision. The findings

are corroborate with previous studies which show that family background is one of

the strong explanatory variable of students career decision-making process at post-

secondary level (Salami 2004; Kimberly et al., 2009; and Stoke, 2007)

The results of the study supported the research hypothesis that there is an association

of relationship between family background and students’ career decision-making at

higher secondary level.


The current study found that parental occupational backgrounds characteristics

influenced the students’ career choices at post-secondary level. Despite that very

limited number of students had working mother’s only, majority of students

considered the parental occupational background characteristics influences in their

career decision-making process (Male students 77.7% and female students 84.0%).

Majority of students fathers were belonged form service and sales workers

occupational group (male students 32.4% and female students 24.6%), professionals

group (male students 19.5% and female students 28.5%) and technicians and associate

professionals group (male students 23.8% and female students 20.3%). Whereas,

majority of students’ mothers were either retired, house wife or had no occupation

(male students 87.5% and female students 80.5%) whereas, students reported that

their mother had professionals’ occupational background (male students 9.4% and

female students 16.0%).

The Chi-square analysis shows that both the students were differently influenced in

their career decision-making process, for example, parental occupational background

characteristics influences were more pronounced for male students (χ2 = 25.572, df =

6, p < .000, V= .252) than female students (χ2 = 19.527, df = 6, p < .003, V= .213).

Discrepancies in influences were found between father’s and mother’s occupational

background characteristics. A robust association of relationship was found between

father’s occupational background characteristics and students career decision-making

process (Male students χ2 = 36.444, p < .000 and female students χ2 = 39.500, p <

.000) whereas, mother’s occupational background characteristics were found less

significant and statistically exerted no influences on students anticipated career

choices. It shows that students take their father’s occupational status as a point of

reference to pursue their career in similar or related occupations. The study also found

that parental occupational characteristics affects the students’ occupational aspirations

and may foster both positive and negative influences. The findings accord with those

of other studies conducted by Lapepel et al., (2001), Oren et al., (2013), Korupp et al.,

(2002) and Tziner et al., (2012).

The findings of the study supported the research hypothesis that parental occupational

background characteristics are significantly associated with students’ career decision-

making process at post-secondary level.

5.1.5 Peer Group Influences

The study found strong peer group influences in students career decision-making.

Most of students (male students 88.67% and female students 95.71%) endorsed the

peer group influences in their career decision-making. As majority of students stated

that they had a friend in the career (male students 63.9% and female students 62.0%),

depended on friends for help (male students 64.8% and female students 63.7%),

discussed and consulted with friends (male students 68.3% and female students

62.9%), helped by the friends (male students 65.6% and female students 65.7%),

selected friends suggested career (male students 56.4% and female students 61.6%),

followed peer group decision (male students 58.6% and female students 60.8%),

influenced by the friends successful story (male students 54.6% and female students

69.4%), had chosen another career if did not discussed with friends (male students

55.5% and female students 65.7%), friends had influenced the career choices (male

students 52.9% and female students 67.8%), and were not engaged in the career what

friends had suggested (male students 34.8% and female students 39.6%).

The bivariate analysis shows statistically significant association of relationship

between peer group influences and students career decision-making (male students χ2

= 24.455, p < .000, V= .232 and female students χ2 = 43.616, p < .000, V= .298). The

study found gender dichotomy in peer group effects and female students were found

more sensitive to peer group influences than male students. The study also found that

both students perceived their network of friends as a source of social and educational

capitals and imitate them in many ways such as in educational choices. It is

noteworthy, that female students were on the odds to be more responsive to group

phenomena and put high value on peer group norms and made their decision with peer

group conformity. Moreover, the study shows that peer group emerges as the shaper

of students’ aspirations and played an important role both as a modeler and definer to

influences the students’ career decision-making. The findings of the study are

consistent with previous studies that reported the vital role of peer group in structuring

students’ life courses and indicated discrepancies of peer group effects among

students across gender (Kiuru et al., 2007; Frank et al., 2008; Jennifer 2012; and

Thomas and Webber, 2001).

The study findings supported the research hypothesis that peer group influences are

likely to be related to students’ career decision-making at higher secondary level.


The study found considerable evidence for the gender differences influences in

students’ career decision-making. As most of the students reported (male students

76.95% and male students 84.79%) the importance of gender differences in their

career decision-making. Majority of students rated that they were influenced by the

differences in interest areas by gender dimension (male students 48.2% and female

students 53.5%), gender based socio-cultural expectations (male students 48.7 % and

female students 67.7%), differences in requirements of certain occupations (male

students 46.2% and female students 60.8%), working conditions influences (male

students 39.1% and female students 58.1%), specific gender role attachment (male

students 42.1% and female students 53.5%), own gender limited to other career

options (male students 43.0% and female students 53.5%), gender stereotyping

influences (male students 40.6% and female students 47.5%), engaged in the career

which suited my gender (male students 48.5% and female students 64.5%).

The Chi-square analysis shows statistically significant effects of gender differences

influences in students’ career decision-making. The study found that both the students

were differently influenced in their decision as the χ2 values show a robust association

of relationship for female students career decision (χ2 = 26.038, p < .000, V= .257)

than male students (χ2 = 34.989, p < .000, V= .284). This significant differences are

the reflection of embedded gender perception emanating from the early socialization

into the specific gender role. Therefore, male students had the tendency to opt for

masculine fields, while female students are more interested to engage in the feminine

characteristics fields. This observed gender pattern in career decision-making lead to

gender segregation in education and many outcomes in the later stages of life.

Consequently, female students are underrepresented in male dominated fields and

overrepresented in other fields. These differences might be explained by the widely

shared cultural belief about gender that channelize male and female students in

substantially to different career routs. The study found that gender identity as a

complex factor influencing aspirations, values and orientations of students which can

be linked to varying dispositions towards education and work. The findings of this

study are generally accord with other studies describing the gender differences in

career selection process at post-secondary level (Charles and Bradley 2009; Francis,

2002; Shelly, 2004; and Francis et al., 2003).

The study findings revealed that gender differences influences seemed to be a strong

determinant to explain the career decision of students at higher secondary level. The

study findings supported the research hypotheses that gender differences are likely to

be related to students’ career decision-making at higher secondary level.

5.1.7 Psychological Factors Influences

Psychological factors play a central role to channelize students into trajectories that

are congruence with their personality traits, cognitive ability, expectations and self-

efficacy. The study found that across gender, students (male students 87.5% and

female students 91.79%) endorsed the importance of psychological factors influences

in their carer decision-making process. Majority of students were found that they had

free choice of making career decision (male students 72.4% and female students

27.7%), had personal interest in the career (male students 42.4% and female students

55.3%) had their own skills, competencies and abilities (male students 48.7% and

female students 63.4%), serendipitous events influences (male students 33.9% and

female students 47.7%), easy access to this particular career (male students 41.5% and

female students 59.1%), had lack of access to or information of other career options

(male students 43.3% and female students 59.9%), were motivated by the teacher

(male students 46.5% and female students 66.0%), and were influenced by the school

attended (male students 44.7% and female students 57.9%).

The bivariate analysis suggested that regardless of gender, students considered the

importance of psychological factors influences in their career decision-making

process. However, unlike female students, male students were found more sensitive

to psychological factors influences. For example, the Chi-square value suggested

strong association of relationship between psychological factors influences and male

students (χ2 = 34.081, p < .000, V= .276) career decision process than female students

(χ2 = 31.068, p < .000, V= .257). Female students were found more sensitive to

different psychological influences than male students. The study also found that

female students were dependent in their decision and had chosen their career in a

random fashion. These findings of the study were corroborated with previous studies

conducted by Mau, (2002), Gushue et al., (2006), Osoro et al., (2000).

On the basis of aforementioned findings, it has been deduced that psychological

factors influences are likely to be related to students’ career decision at higher

secondary.


Findings of the study suggested that across gender (male 96.87% and female 98.70%)

students valued the economic factors influences in their higher secondary track

choices. The study findings demonstrate that selection of a particular field of study

depends on the importance of anticipated labour market participation opportunities

(male students 54.0% and female students 59.6%), high financial rewards associated

within the career (male students 54.4% and female students 47.8%), enabling to run

their own business in the future (male students 60.9% and female students 56.7%),

future success (male students 78.6% and female students 75.5%), better quality of life

in the career (male students 66.1% and female students 64.4%), achieving high social

status (male students 69.8% and female students 75.2%), and associated social

prestigious within the career (male students 60.1% and female students 60.8%).

The bivariate analysis suggested statistically significant effects of economic factors

influences on students’ career decision-making. The study found that the influences

were more profound in male students (χ2 = 80.658, df = 6, p < .000, V= .403) career

decision-making than female students (χ2 = 42.702, df = 6, p < .000, V= .295).

Discrepancies of effects indicate that male students put weight on after degree

advantages such as labour market opportunities, monetary returns from their degree,

personal success and associated better quality of life in the career. The study also

found that female students valued the prestigious dimension of their career more than

their counterpart. It shows that male students felt pressure to achieve more financial

advantages and payback to support their families. Therefore, the findings shed light

on the fact that male students play an important role to constitute social and economic

capitals that will lead toward upward social mobility. The findings of the study are

consistent with those of other studies conducted by Hirschb (2008), Staniec (2004),

Arcidiacono (2004) and Finnie and Frenette (2003).

The study findings supported the main research hypothesis that economic factors are

associated with students’ career decision-making at higher secondary level.

5.2 Theoretical Implication

The study found that the early socialization process at home and the background

variables significantly shaped the students career choices. Students were found to

make their decision with conformity to families’ traditions. Family was emerged as

the source of capitals and parental educational and occupational backgrounds were

found to be influential on students’ career decision-making process. Both students

take their parental status as a point of reference for achieving the similar position as

their parents and students are on the odds to reproduce their parental resources. These

findings of the study are supported by the social reproduction theory which suggested

that family social origin plays a major role in child educational attainment. Family

backgrounds constitute social and cultural capitals for the students. Family provides

access to useful information by envisioned students to make a well informed career

decision. The theory suggested that parents are investing in child education because

of they want to reproduce their own resources in future.

The study also found that students imitate their parents and adopt their peer in their

career decision. The gender identity and gender role reinforcement to a large extent

shape the students educational and occupational preferences. Social learning theory

of career decision making considered the influence of environmental conditions such

as family traditions, social and economic forces and the genetic endowment such as

gender as the influential factors to construct career choices among students. Overall

the study findings are supported by two theoretical perspectives i.e. social

reproduction theory and social learning theory. The study found association between

underlying theoretical assumptions and the major findings of the study.

5.3 Conclusion

In recent years sociological research has provided greater insight into the role of forces

that mould the career choices of students. Education is seen as stepping stone for status

attainment in social hierarchy. Studies have identified career preferences as one of the

major areas of concern for young people entering into college level education.

Therefore, greater emphasis is placed on those forces which precipitate students to

choose one career over other. The purpose of the current study was to explore the

determinants of career decision-making that precipitate students in career decision-

making at higher secondary level.

The analysis of quantitative data in chapter four provided important findings and

subsequent discussion concerning the determinants of career decision-making

illustrates how career preferences are not simply individualised choice but are socially

embedded and therefore remain circumscribed by structure such as parental education,

parental income, parental occupational background characteristics, family

background, peer group, gender differences influences, psychological and economic

factors influences. The results of the current study show that across gender parents’

exerted statistically significant influences on students’ career decision-making

process. For instance, across gender parental education exhibits strong influences on

students’ choices but the magnitude of effects was found statically significant for male

students only. Unlike mother, father was emerged as the most influential individual

to determine students’ career choices. Father’s years of schooling and income were

appeared as the strong determinants to explain the students’ career decision-making

at higher secondary level. Moreover, the findings also suggested gender biases in

parental educational and income influences, for instance, the association of

relationship was stronger for male students than female. It indicates that parents put

high value on male child education and considered it as a future investment, therefore,

male child received most of the parental resources which indirectly led to reproduction

of parental resources.

A substantial evidences were found that socialization at home is a linchpin in

explaining students’ choices at higher secondary level. The study found polarity of

effects among students, for example, the association of relationship was more robust

for female students than male. It shows that female students are embroiled to make

their decision with conformity to familial backgrounds. Moreover, further analysis

suggested that female students in joint family were more dependent in their decision

than students leaving in nuclear family. The study found significant effects of parental

occupational background characteristics influences on students post-secondary track

choices. Unlike mother, father’s occupational characteristics were more influential on

students’ career decision-making process. The study findings also suggested that male

students are on the odds to take their parental occupational status as a point of

reference and made their decision congruent with their father’s occupational

characteristics.

Students’ friendship propinquity emerged as definers and modellers for affecting

students choices. Female students valued peer group conformity more than male

students. Whereas, male students made their decision independent of friends

influences. The gendered pattern style of career decision-making was found among

students. The widely shared culture belief about gender do explain the students’ career

choices at higher secondary level. Students were found to put weight on gender

identity in their decision and were on the odds to choose a field that is corresponding

with their gender. Consequently, majority of female students avoid masculine

dominated fields for their future and enrol in traditional feminine suited fields.

The study found that psychological factors influences to some degree determine

students career choices at secondary level. Both the students were on the odds to

consider the different psychological factors influences in their decision. The study

found substantial evidences that students career decision to a higher degree depend on

the expected economic returns in a particular field. The labour market participation

opportunities and associated economic advantages within the career are linchpin of

students’ decision at higher secondary level. The data also demonstrated that male

students put high value on after degree returns and were on the odds to opt for the

more lucrative, marketable and demanding fields.

5.4 Limitations of the Study

Although, the findings of the thesis advance our understanding regarding the

determinants of career decision-making of students at higher secondary level.

However, some limitations should be noted to put the findings of the study into a large

context.

First, relatively a small sample size was drawn from population. In particular, when

sample size was broken down by field of study. The universe of the study was large

i.e. higher secondary level students of Karachi, within available resources and time,

for the researcher it was not possible to draw a large sample size. Therefore, researcher

has restricted the sample size to 512 students.

Second, the generalizability of the study is limited to the students who enroled at

higher secondary level education and declared their major. As the data was collected

from college students to explore the determinants of career decision-making, who may

be different from other students. Therefore, when interpreting the results of the study,

need to be cautiously applied when applying to other college students in general.

Third limitation follows from the use of structured questionnaire. Researcher has

attempted to elicit all the possible information from the students in a logical way. All

the important considerations were kept in mind in the process of questionnaire

development. However, the questionnaire may have some shortcomings.

Forth, in the current study only measured peer effects, no differentiation was made

between school based and outside peer effects. Moreover, the cross sex friendship is

also exerted different influences on male and female students. Our sample did not

allow us to include these different dimensions of peer group effects in our analysis, if

it had been studied, some of the results might be different.

5.5 Recommendations

Keeping in view the results of the present study the following recommendations are

being proposed,

(i) The study found that socialization at home plays a very vital role in

developing child life choices. Therefore, the parenting practices may

be of crucial importance for intergenerational transmission of

education and work related preferences. Parents need to invest more in

child socialization process at home and to channelize children to

suitable careers for their future.

(ii) Parents needs to be effectively involved in the career decision-making

process of their children. It is suggested to parents to equally mobilize

their resources such as social and cultural capital to their children. It

will prevent students from selecting their career in random fashion and

will help them to make a well informed career decision.

(iii) The study highlighted that peer group creating forms of capitals that

shape the education and work related preferences of adolescents.

Students need to make their friendship ties with those who can play a

productive role in their life. Parents also needs to closely monitor their

children friendship propinquity.

(iv) The widely shared cultural belief about gender identity and specific

role reinforcement were the stumbling blocks in students’ decision.

Particularly, female students’ career choices were constrained by their

gender identity. Parents and teacher needs to aware female students

about the wide range of career choices where female students can

better play their role.

5.6 Suggestions for Future Research

(i) It would be interesting to further explore the dynamics of parents’

influences on children career choices. Because of the rapid social

changes particularly changes in the family in modern society the

parental authority are being eroded, leading to weaken family

influences. Future studies may therefore examine whether parental

influences on career choice has declined in contemporary society.

(ii) Karachi is a multi-culture city, students were belonged from diverse

ethnic groups. They have many common features but each ethnic group

has their own characteristics. Therefore, it would be interesting to

explore, whether there is any cultural differences in career decision-

making process among students belong from different cultural

backgrounds.

(iii) The research with more heterogeneous sample from different

geographic locations (rural and urban) may extend our understanding

regarding the students’ decision-making at higher secondary level.

(iv) Gendered pattern career decision-making style persists among students

and both students had their own areas of interest. Recognizing the

potential family responsibilities, female are observationally more

likely to interrupt their labour force participation to raise children and

look after their family. The future endeavours would need to examine

this dimension from different perspectives.

(v) The future endeavours would need to explore the different dimensions

of peer group effects, for example, school based and outside peer group

effects, tendency of making friendship with high academic achiever

students and lower achiever students and across gender peer group

effects among students.

5.7 Implications of the Study

This study contributes to the career decision-making literature by looking at different

influences that determine the students’ choices at higher secondary level. Based on

the above conclusion, it is the considered opinion of the researcher that the findings

of the study have profound implications for curriculum developer, college

administrator, teachers, career counsellors, parents and government authorities.

5.7.1 Implication for Curriculum Developer

It is strongly advised that curriculum developers need to develop curricula that focus

on the gender pattern of career decision-making style of the students. They need to

identify the kinds of situations that reinforce both the students to gender suited

subjects and to develop a mechanism that effectively address the inequitable

situations. They need to ensure to develop a curricula that reflectively address

concerns about gender equity.

5.7.2 Implication for College Administrators

College administration has professional obligations to ensure that college provides

students with adequate and relevant education. They need to address teacher-students

related factors that will positively impact on female students’ perception about

engineering related career participation. Teachers should be encourage to carry out

action researches into the gender dynamics of their classrooms with a view to effecting

desirable changes in them. College administrators should actively involve the parents

in the future career planning of their students.

5.7.3 Implication for Teachers

The literature shows that teachers are influential to shape the views and attitudes of

their students. Teachers have both moral and professional obligations to ensure that

their pedagogical approaches address the question of gender equity and adequately

addressing the gender stereotyping.

5.7.4 Implication for Guidance and Counselling

This is well defined fact that students’ aspirations to some degree determine their

anticipated career choices. For career guiding and counselling departments at college

level, if any, (we know very little about it) need to raise students’ awareness,

particularly the female students, on a wide range of career options available to them.

5.7.5 Implication for Parents

Parents’ words are powerful and can influence perceptions of students about subject,

performance and participation in the subject at college level. As it is well documented

in the literature that parents play significant role in shaping the way their children

view the world. The findings of the study will be helpful for the parents to understand

that how their behaviours and attitudes may influence their children perceptions and

aspirations. Parents need to equally mobilize their resources and provide equal

opportunities to both the children. Because the issue of gender stereotyping will not

be adequately address without taking parents abroad in this endeavour.

5.7.6 Implication for Concern Govt. Department

The findings of this study have implication for the Ministry of Education (MoE) to

take some policy measures to design a strategy that will provide a wider exposure to

students for exploring the different opportunities structures available to them.

Consequently, students will be envisioned to choose the field of study that is more

market oriented. Moreover, literature on the opportunities structures and changes in

market demand need to be published on regular basis. This career related information

should accessible to all students for learning purposes.

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APPENDIX: 1

INTRODUCTORY NOTE

The purpose of this research study is to collect data for a Ph.D. (Sociology) thesis under the title of

“Determinants of Career Decision Making among Higher Secondary Level Students of

Karachi” Data will be collected among the students of Govt. and private colleges of Karachi, both

male and female students will be surveyed, the study will try to identify the determinants that

reportedly influenced the career decision making process of students at higher secondary level. I will

appreciate, you are taking the time to participate in the survey. This study is anonymous, your

responses are voluntary, and your individual privacy and confidentiality will be maintained in all

published and written data analysis resulting from the study. I ask you to answer each of the question

openly and honestly. You agree to take part in this research study by filling out the below

questionnaire.

PART (A)

A Personal & Demographic Information (please tick the relevant box)

Educational Information

College Student’s Class Group Selected i Govt. College i

First Year i Pre-Medical

ii Pre-Engineering ii Private College ii Second Year iii Commerce

iv General Group

B Demographic Information (please tick the relevant box)

Gender Student’s Age Family Type

i Male

i Joint Family

ii Nuclear Family

ii Female iii Single Parent Family

iv Other

C Father’s Information (please tick the relevant box)

Father’s Education Father’s

Occupation

Father’s Income

i No Education

i Up to 10000 ii Elementary Level

Education

ii 11000-20000

iii Secondary Level

Education

iii 21000-30000

iv Degree College Level

Education

iv 31000-40000

v University Level

Education

v 41000 and more

vi No Income

D Mother’s Information (please tick the relevant box)

Mother’s Education Mother’s

Occupation

Mother’s Income

i No Education

i Up to 10000 ii Elementary Level

Education

ii 11000-20000

iii Secondary Level

Education

iii 21000-30000

iv Degree College Level

Education

iv 31000-40000

v University Level

Education

v 41000 and more

vi vi No Income

PART-B

Student’s responses

1. Do you know about the term career decision making?

a. Yes b. No

2. If yes, what does it refer to?

a. Kind of inspiration

b. Choice of profession/occupation

c. Source of achieving authority

d. Achievement of desired goals

e. Availability of more job options in future

f. Way for achieving social status

g. Source of economic empowerment

h. Enhancing the intellectual ability/skills

3. In your opinion, does career decision making play any role in one’s life?

a. Yes b. No

4. If yes, in your opinion how much it is important in one’s life? (Please circle an

appropriate score from 1 to 7)

A Not at all important 1

B Low importance 2

C Slightly important 3

D Neutral 4

E Moderately important 5

F Very important 6

G Extremely important 7

5. At what stage of your life you have decided to choose this particular career for your

future concentration?

a. When I was in primary level

b. When I was enrolled in secondary level

c. When I entered in higher secondary level

6. Is it your first choice of career?

a. Yes b. No

7. If no, had you any other choice of career in your mind?

a. Yes b. No

8. If yes, what is/was your first choice for career?

9. Are you satisfied from your current choice of career?

a. Yes b. No

10. If yes, how much are you satisfied from your decision? (Please circle an appropriate

score from 1 to 5.

A Not at all satisfied 1

B Slightly satisfied 2

C Moderately satisfied 3

D Very satisfied 4

E Extremely satisfied 5

The following factors may have influenced your career decision making. Give a score from 1

to 5 to each of the factors where 1 represents Strongly Disagree, 2 Disagree, 3 Dependent, 4

Agree, and 5 Strongly Agree.

11. In your opinion, does family background play any role in career decision making?

a. Yes b. No

12. If yes, give a score from 1 to 5 to each of the statements;

I choose this career because of;

S.No Statements 1 2 3 4 5

A My family members persuaded me to choose this career

B One or more of my family members are in the same field

C I have discussed my career choice with family members

D My family members have encouraged/advised me to

choose this career

E My home environment influenced my career decision

F My own financial/economic conditions have influenced

my career decision

G My family expected me to study in this career

H I have received career related information from my

family

I I am engaged in the career what my family have chosen

for me

J My family has already chosen a career

K Career chosen by my family is not what I want

210

13. In your opinion, does parent occupational background characteristics play any role in

influencing one’s career decision?

a. Yes b. No

14. If yes, how much do you agree or disagree with the following statements;

The influences of Father’s Occupational Background Characteristics

I choose this career decision because of;


A I am intended to work in my father’s profession

B My father’s profession gives him the feeling of being

respected by other

C My father’s profession gives him interesting and

challenging things to do

D My father’s profession gives him feeling of security in

the future

E My father’s profession provides him with an income that

satisfies him

F My father’s profession gives him opportunity to make as

much money as their friends/relatives

G My father’s profession gives him the opportunity to the

kind of work that is well suited to his abilities

H My father’s profession gives him more advancement

opportunities

I My father’s profession provides him a pleasant working

conditions

J My father’s profession gives him opportunity to get full

credit for work done

K My father’s profession give him opportunity to work

independently of other

L My father’s profession keeps him busy all the time

M My father’s profession gives him opportunity to be of

service to people

The influences of Mother’s Occupational Background Characteristics

I choose this career decision because of;


A I am intended to work in my mother’s profession

B My mother’s profession gives her the feeling of being

respected by other

C My mother’s profession gives her interesting and

challenging things to do

D My mother’s profession gives her feeling of security in

the future

E My mother’s profession provides her with an income

that satisfies her

F My mother’s profession gives her opportunity to make

as much money as their friends/relatives

G My mother’s profession gives her the opportunity to the

kind of work that is well suited to his abilities

H My mother’s profession gives her more advancement

opportunities

I My mother’s profession provides her a pleasant working

conditions

J My mother’s profession gives her opportunity to get full

credit for work done

K My mother’s profession give her opportunity to work

independently of other

L My mother’s profession keeps her busy all the time

M My mother’s profession gives her opportunity to be of

service to people

15. In your opinion, does friend(s)/friendship play any role in influencing one’s career

decision?

a. Yes b. No

16. If yes, how much do you agree or disagree with following statements;



A I have a friend in this career

B I have a friend(s) that I can depend on him/her for help

C I have discussed and consulted with him about own

choice of career

D My friend(s) have helped me in choosing this career

E I have selected the career what my friend(s) have

suggested

F All of my friends have agreed to select the same career

in higher secondary level

G Successful story of my friend(s) have influenced my

career decision

H I would have chosen another career if did not discussed

with my friends

I My friend have influenced own career decision

J I am not engaged in the career what my friend(s) have

chosen for me

17. In your opinion, does a person gender play any role in influencing one’s career

decision?

a. Yes b. No

18. If yes, how much do you agree or disagree with following statements;

I choose this career because of; S.No Statements 1 2 3 4 5

A Differences in interest areas by gender has influenced

own choice of career

B Differences in socio-cultural expectations by gender has


C Differences in requirements of certain professions have


D Working condition in a certain career suited one gender

only

F Influenced by the specific gender role attached with own

choice of career

G My gender is limited me to others career option

H The gender stereotyping have influenced own career

choice

I I am engaged in the career which suited my gender

19. In your opinion, does a psychological factors play any role in influencing one’s career

decision?

a. Yes b. No

20. If yes, how much do you agree or disagree with following statements



A I have free choice to make my career decision

B I have personal interest in the career

C My own skills, competencies and abilities

D It was a chance, luck or circumstances only

E Easy access to this particular career

F Lack of access to or information of other career option

G Teacher(s) motivation to choose this particular career

H The school I have attended has influenced my career

decision

21. In your opinion, does a psychological factors play any role in influencing one’s career

decision?

a. Yes b. No

22. If yes, how much do you agree or disagree with following statements



A More labour market participation opportunities

B It will enable me to run my own business

C More financial reward in this career

D I want to be a successful person in future

E Quality of life associated with this career

F Achieving high social status in the society

G Society considers it important

determinants of career decision-making...

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