INFLUENCING GIRLS
TO PURSUE A CAREER IN THE
CREATIVE INFORMATION TECHNOLOGIES
Michele Mosco
Arizona State University College of Teacher Education and Leadership
April 3, 2008
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INFLUENCING GIRLS TO PURSUE A CAREER IN THE CREATIVE INFORMATION TECHNOLOGIES
Introduction
A leaky pipeline is often cited as the cause for the underrepresentation of women in
computer-related professions. At different stages in their education and entrance into the job
market, women lose interest in these careers at a higher rate than do men, leaving the field after
high school, during college, or before beginning a job in the field (Gurer & Camp, 2002;
Woszczynski, Myers, & Beise, 2003). Proponents of the “leaky pipeline” theory generally assert
that female interest in technology decreases through college student years and early working
years (Gurer & Camp, 2002). However, it seems that females might not be leaking from the
pipeline at greater rates than males; instead, they might not be entering the pipeline at all.
As a programming student in the early 1980’s, the gender composition of students in my
classes was balanced. In addition, having previously taught technology classes to elementary
school students in the 1990’s and 2000’s, I found both male and female students eager to learn
and use technology skills. Now, I wonder how well-represented females are in technology
courses at the high school in which I am currently the librarian.
This suburban metro high school, in its eighteenth year of existence, is predominantly
Hispanic (48%) and White (36%) (National Center for Education Statistics, n.d.). Although only
23% of the students are registered for free and/or reduced lunch, the elementary feeder schools’
average rate is 51.6%. The school’s state achievement testing results are above the state and
county averages, and the graduation rate has increased to just under 90%. The school’s guidance
department approximates that 25% of graduates are university-bound, with an additional 50%
enrolling in a community college, trade school, or the military (M. Gollihar, personal
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communication, November 30, 2007). Clearly the students have the potential for success in a
wide variety of rewarding careers.
However, my high school’s limited courses in the creative information technology fields,
including such careers as web design and development, multimedia, and digital imaging,
surprised me. No computer art, digital photography, or media courses are available at this school.
“Web Publishing” is available for sophomores and juniors who have met the prerequisite “Word
Processing” course, which is required for all students. But the female enrollment for “Web
Publishing” has averaged 23% since the course was first offered for the 2005-2006 school year
(Fictional High School, 2005-2007). This is problematic.
Since 2004, approximately 90% of the after-school web publishing club members have
been male (Fictional High School, 2005-2007). And while female students are interested in
graphic and communication arts because the school’s Artists and Writers Association, a new club
for the 2006-2007 school year, is approximately 75% female, I continue to question: Why are
girls marginalized from high school computer courses other than word processing (S. Rosichelli,
personal communication, February 3, 2008; Sanders & Tescione, 2007)? Why aren’t girls
entering the pipeline toward creative information technology careers in high school?
Theoretical Framework
To determine why adolescent females are not exhibiting interest in creative information
technology careers, it is vital to examine how individuals actually choose a career. Interventions,
then, can be developed to influence or affect this process. Although many career development
theories have been employed to posit how individuals determine a career path, many of these are
incongruent with current cultural and societal norms and populations under study (Creamer et al.,
2007; Kerka, 1998; Stitt-Gohdes, 1997).
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Applicable to the current study is the social cognitive career theory which seeks to
explain career choice through outcome expectations and self-efficacy (as summarized by Lent,
2004). Outcome expectations include those beliefs that an individual holds about the
consequences of his/her behavior (Lent, 2004). If, for example, an individual pursues a
particular career, outcome expectations refer to what the individual imagines will occur. What
will they be doing? Will they be comfortable in the work environment? Will they enjoy the
work? Will the work be fulfilling? With whom will they be working?
Self-efficacy refers to a person’s belief that they can be successful in a certain career
addressing the question, for example:- Will I be successful in this career (Bandura, 1997)? Self-
efficacy is modified through several factors, the strongest being a person’s accomplishments or
their mastery experiences. Gaining mastery experiences in a field increases a person’s
confidence that they will flourish in a particular career.
According to Lent (2004), providing exposure and efficacy-building experiences to
career opportunities is vital to expanding adolescents’ career interests. It is through an
individual’s outcome expectations and self-efficacy that a person develops personal goals.
Additionally, when Smith (2002) extended the social cognitive career theory to the information
technology field, computer self-efficacy through mastery experiences and outcome expectations
were significant predictors of interest in information technology careers. Thus, career choice
according to the social cognitive career theory, depends upon both a person’s outcome
expectations and their perceived self-efficacy which is developed through mastery experiences.
It is these factors, then, that are vitally important to understanding why females do not enter the
information technology career pipeline.
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Review of Literature
In the eighties when computers became available to the general population, researchers
began to seek an explanation for the low participation rates of females in the field. While the
technology has dramatically evolved since that time, societal norms, such as gender expectations
in traditionally male-dominated fields, have also changed. Thus, although there are numerous
studies investigating the underrepresentation of females in information technology careers, many
cannot be applied to today’s information technology field.
Of those that are more current and do apply to this study, I used the social cognitive
career theory’s components— outcome expectations and self-efficacy to filter from the research
the most salient impediments to girls’ choice of creative information technology careers. See
Appendix A.
Outcome Expectations: With Whom Will I Work? Stereotypes of Computer Workers
According to the social cognitive career theory, people consider with whom they will be
working when choosing a career (Lent, 2004). Research has shown that girls perceive
computing professionals to be overwhelmingly male (Cooper & Weaver, 2003) and indeed they
are. According to a 1999 study, 80 percent of information technology professionals are male
(American Association of University Women Educational Foundation [AAUWEF], 2000) while
a 2005 study by the Information Technology Association of American (ITAA) found that women
comprised 24.9% of those employed in professional computing fields in 2004. More specific to
the current study, in the web design/development field, females comprise only 16% of those
employed (A List Apart, 2007).
In addition, both genders picture computer experts as males wearing glasses and
possessing superior intelligence with less than average social skills (ITAA, 2005; Jepson & Perl,
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2002; Margolis, Fisher, & Miller, 1999; Margolis & Fisher, 2002; Mercier, Barron, and
O’Connnor, 2006; Zarrett & Malanchuk, 2005). Computer professionals are also perceived as
having difficulty separating themselves from their non-creative, solitary work on a computer in a
cubicle (Cohoon & Aspray, 2006; Howe, Berenson, and Vouk, 2007). The media perpetuates
this image, an example of which is the Geek Squad television commercials for Best Buy Co.,
Inc. (see, for example “Agents Up Close” at http://www.geeksquad.com/agents). Unfortunately,
the field truly is predominantly male, but the “geeky” image, while prevalent, is false
(AAUWEF, 2000). Thus, adolescent females must be introduced to those employed in these
fields, both male and female, to witness the reality of the range of personalities they posses.
Outcome Expectations: What Will I Do? A Lack of Career Information
In choosing a career, consideration is given to not only with whom one will work, but
also to what one will be doing (Lent, 2004). There must be a match between what the person
enjoys doing and what they believe a job entails. In terms of gratifying computer activities,
several studies found gender differences in adolescents’ computer use. Boys tend to enjoy
computing for its own sake, while girls were more apt to use computing to accomplish something
(Cohoon & Aspray, 2006; Cukier, Shortt, & Devine, 2002; Lang, 1999; Margolis & Fisher,
2002). Indeed studies that compared the gender differences in type of computing activity found
that boys were more likely to play games whereas girls were more likely to use computers for
communication and homework (Colley & Comber, 2003; Hunley et al., 2005; Ogan, Robinson,
Ahuja, & Herring, 2006). In several studies, girls ranked endeavors such as designing and
creating, as the technology-related activities with which they were most satisfied (AAUWEF,
2002; Magoun, Eaton & Owens, 2002; Margolis & Fisher, 2002; Olszewski-Kubilius & Seon-
Young, 2004). Researchers also found that girls are more likely to choose information
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technology as a career when their computer experiences are tied to other fields, such as
medicine, education, and the arts, as well as human and social contexts (Creamer, Burger, &
Meszaros, 2004; Margolis et al., 1999; Upitis, 2001). Information technology does link to these
fields in many contexts, but girls perceive these careers to utilize much different proficiencies in
a highly isolated environment.
Unfortunately, both genders have relatively little information about the responsibilities
and roles of these careers (Harris & Wilkinson, 2004). When high school students were asked to
rate the skills most necessary for a computer-related career, fast typing, basic computer skills,
and logic ranked highest while creativity, communication skills, and graphics came in last
(Klawe, 2001). Researchers also note that girls perceive information technology careers as
solitary endeavors in which communication skills are unnecessary (AAUWEF, 2002; Davies,
Klawe, Nhus, Ng, & Sullivan, 2000). The media readily portray career responsibilities for those
employed in workplaces such as hospitals and courtrooms, but rarely do movies and television
shows include computer professionals (Jepson and Perl, 2002). Perhaps because of the
familiarity with careers portrayed in the media, nearly half the girls surveyed by Barker, Snow,
Garvin-Doxas, and Weston (2006) aspired to professional emergent careers which included
medicine, law, law enforcement, the armed forces, and architecture. Consequently, because
students do not understand the competencies required for creative information technology
careers, they cannot accurately predict the outcome expectations for those careers and are not apt
to choose them.
Self-Efficacy: Can I Do This Job? Skills Development
Self efficacy refers to a person’s belief that they can be successful in a particular career
(Bandura, 1997). According to the social cognitive career theory, it plays a key role when a girl
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considers choices for a career and can be cultivated through successful, enjoyable computer
experiences. Stitt-Gohdes (1997) asserts that this is critical to introducing women to male-
dominated career choices. The self-efficacy of females entering male-dominated careers is lower
than the self-efficacy of those entering traditionally female careers (Bandura, Barbaranelli,
Caprara, & Pastorelli, 2001). Because information technology careers are perceived and are in
fact male dominated, females pursuing computer careers tend to have lower self-efficacy, which
according to Bandura (1997) may hinder their ability to perform and succeed.
Many believe that boys approach computers with more self-confidence because a
pervasive leisure activity for them is computer game playing (Margolis & Fisher, 2002).
However, according to national study, the amount of computer and internet use does not differ
significantly by gender (DeBell & Chapman, 2006). In fact, 15-17 year-old girls are more likely
to maintain a blog (an electronic journal) than boys in the same age group (Lenhart & Madden,
2005). Yet several researchers found that even with equal expertise, males possessed greater
self-confidence in their abilities and indeed often overstated their ability level (Colley &
Comber, 2003; Davies et al., 2000; Herring, Ogan, Ahuja, & Robinson, 2006; Howe et al., 2007;
Oosterwegel, Littleton, & Light, 2004; Zarrett, Malanchuk, Davis-Kean, & Eccles, 2006).
Consequently, it might be girls’ perceptions that they arrive at the computer with less skills and
experience than boys, not fact. Therefore, providing girls with technology experiences in which
they feel successful may positively influence girls’ self-efficacy and in turn, their desire to elect
technology-related careers as career options.
Raising Girls’ Interest in Entering the Pipeline
In this intervention, I am seeking to increase the number of females who actually enter
the creative information technology career pipeline. To do so, I will focus on those barriers that
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appear most applicable to today’s creative information technology field. Hopefully this
intervention will help ameliorate the following barriers to participation: stereotypes (Who will I
work with?), lack of career information (What will I do?), and mastery experiences with specific
technology skills and thus, its related self-efficacy (Can I do this job?). This action will focus on
increasing girls’ interest in utilizing computers for web design/development, digital image
manipulation, and multimedia--the creative information technology careers—which did not exist
during previous research studies on gender equity in the field.
The Intervention: “TAG: Technology and Girls” Club
Utilizing a female-segregated intervention as advocated by Cooper and Weaver (2003)
and Magoun et al. (2002), I will develop a girls-only technology club at my high school. The
club, comprised of activities enumerated in Appendix B, has tentatively been titled “TAG:
Technology and Girls.” It will meet for 90 minutes weekly over a ten-week period, and during
this time, the female participants will be provided with female role models in the industry, with
information about creative technology careers, and with opportunities for success developing
creative technology skills. This will be done to determine whether (1) Presenting female role
models who are employed in creative information technology careers will stimulate female
participants’ interest in these careers by negating the prevalent stereotypes and addressing the
outcome expectation of “With whom will I work?”; (2) Information about creative information
technology careers will increase girls’ interest in pursuing these careers by addressing the
outcome expectation of “What will I do?”; and (3) Providing computer skills instruction to
increase girls’ foundational skills in creative information technology will increase their
hypothetical interest and self-efficacy in these careers addressing the self-efficacy question of
“Will I be successful in this job?”.
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Participants
The participants in the study will consist of fifteen girls who attend the high school at
which I am the librarian. Because girls enrolled in advanced math and science classes are already
destined for careers in math and sciences and are typically recruited for science, technology,
engineering, and math (STEM) enrichment activities, a different population will be targeted to
avoid the “saving the saved” situation (Barker et al., 2006, p.115). Since the focus of my study
is on creative information technology careers, girls who are interested in creative endeavors and
have foundational computer skills will be targeted for participation.
Girls will be eligible to participate in the workshop series based on several
characteristics. First, the girls who do not exhibit interest in programming or web design as
measured by lack of enrollment in these courses will be targeted. Second, girls who exhibit
interest in creative activities as measured by enrollment in visual arts classes or participation in
creative extracurricular activities, such as the Artists and Writers Association, will be targeted.
Third, girls who possess basic computing skills as evidenced by completion of the school’s one-
semester word processing course will be recruited for participation. Recruitment into the
program will occur via informational flyers posted throughout the high school campus (see
Appendix C), morning announcements presented over the public address system, and
announcements during arts classes.
Data Collection & Instrumentation: Survey
Both quantitative and qualitative data will be collected through administration of a
survey. An eight-section survey (see Appendix D), adapted from a survey used in a National
Science Foundation study (Creamer, Lee, & Meszaros, 2007 – see Appendix E), will be
administered to all participants. Each participant’s pre-intervention survey will be linked with the
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corresponding post-intervention survey and analyzed for program effects. Appendix A provides
a correlation chart to illustrate how the survey questions relate to the research questions. The
final version of the validated, pilot-tested survey will be administered to the club’s participants at
the beginning of the club and again at the final club session in the fall of 2008.
Instrumentation: Pilot Testing
The survey instrument will also be pilot tested during which errors in question
comprehension, processing and response communication will be pinpointed (Collins, 2003;
Fowler, 1995; Presser et al., 2004; Willis, 2005). The questions included in Appendix F will be
asked during an individual administration of the survey to five participants who agree to
participate in the pilot study and meet the criteria for participation for the club. .
In addition, criterion-related evidence of validity for the survey will be determined using
a second instrument (Appendix G), an interview which will be used to measure similar points of
inquiry. Each of these three interview questions should elicit the same response as its
corresponding survey question (see Appendix G for correspondence). Through these interview
questions, concurrent validity will be indicated if participant responses to the interview questions
correlate with their responses on the corresponding survey question.
Data Collection & Instrumentation: Researcher Observations
In addition to survey data, I will maintain a repository for observational and live field
notes. As a participant/observer, I will be listening and observing for indicators that demonstrate
a change in quantity and nature of stereotyping of computer workers, of information about these
careers, and of self-efficacy and technology skills. Additionally, as indicators are presented, I
will elicit further explanation from the participants through general probes, such as, “Why do
you say that?” or “What do you mean?” Through these researcher memos, I will document trends
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in participants’ behavior that indicate changes in stereotypes of computer professionals,
knowledge of computer careers, and self-efficacy.
Data Collection & Instrumentation: Individual Interviews
After the survey is administered at the final workshop session, five of the participants
will be randomly selected to participate in individual interviews. They will be asked the open-
ended questions found in Appendix J. These questions directly address the study’s research
questions.
Data Collection & Instrumentation: Participant Products & Researcher Evaluation
During the intervention workshops, the participants will create three major products: a
personal website, a digital story, and a manipulated image. Although these products do not
directly address stereotypes of information technology personnel and knowledge of computer
careers, these products will be used as evidence of each participant’s mastery experiences with
computer skills. Because a person’s self-efficacy increases given his/her mastery experiences
(Bandura, 1997), these products will be used to indirectly measure the participants’ self-efficacy
using these technology tools. I will use the rubric in Appendix H to assess these skill levels.
Data Analyses
These data types--surveys, field notes, interviews, and participant products--will be
triangulated during the analysis stage of this study to determine whether the club’s activities
cause a significant change in the participant’s perception of people employed in these careers,
the job responsibilities of these careers, and the participants’ self-efficacy related to the
technology skills introduced. First, the participants’ pre-intervention surveys as compared to
their post-intervention surveys will be used to assess change in the girls’ attitudes about people
employed in these fields, knowledge of job responsibilities, and their own computer skills and
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resulting self-efficacy. Second, my observations, qualitative field notes, and interviews will
provide additional data with which to confirm or disconfirm the findings revealed in the survey
data and the interviews. Finally, evaluation of the creative technology products produced by the
participants will provide supplementary data with which to measure mastery experiences and
indirectly, resulting levels of self-efficacy. Thus, analysis of the quantitative data will occur
simultaneously with the analysis of the qualitative data.
Quantitative data will be analyzed using Statistical Package for the Social Sciences
(SPSS) Version 15.0. Descriptive statistics will be calculated for the group’s responses to the
pre-intervention and post-intervention surveys. Inferential statistics will be used to examine
changes in the participants’ perspectives after program involvement using dependent samples
paired t-tests. Effect sizes will also be calculated to measure the magnitude of the effect of the
intervention.
Because the study involves a phenomenon—career choice—the grounded theory
approach will be used to allow theories to emerge from the qualitative survey and field
observation data (Glaser as cited in Dick, 2005). This process consists of four procedures
through which data will be explored (Strauss & Corbin as cited in Leedy & Ormond, 2001).
First, from each response, key words and phrases will be identified and labeled as codes for that
response (Miles, 1984). The responses will also be examined as a whole to determine any
overall idea(s) that may not be represented through individual words. These codes will then be
categorized into common groups that share similar characteristics. After open coding is
completed, axial coding will help to locate interconnections to form themes which will help to
illustrate the context within which the categories and codes will co-exist as well as help to
explain the conditions from which the codes arose. Third, the themes will be combined to
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develop a “story line” to describe what is happening in the situation being studied. Finally, a
theory will be hypothesized to explain participant responses and observational data.
Project Aspirations
The “Technology and Girls” club aspires to positively impact participants’ interest in
creative information technology careers (Timeline in Appendix I). In doing so, career
opportunities for these participants will hypothetically increase. Web design, in particular, is a
lucrative field in which over 50% of those employed earn more than $40,000 per year, with less
than 20% working more than 50 hours per week (A List Apart, 2007). The flexibility of this
career field is well-suited to women, who often juggle families and careers for many years.
Additionally, through the intervention, some participants may become attracted to other
information technology careers resulting in another positive effect.
In the local school community, increased interest in these careers may improve the
gender balance in both the web design course and the web design club, revitalizing both the
course enrollment and the club’s enrollment in the process. If this indeed is the result, this
intervention may serve as a model for other programs both at the high school and community
college levels.
On a national level, society benefits when females help America build a “high tech future
drawing from the broadest possible talent pool” (ITAA, 2005, p. 4). Indeed, it is this untapped
talent that concerns many researchers (Lang, 2003). Furthermore, although women consume
information technology products equally, these “same IT products and services…are conceived
and designed mostly without women’s input” (National Center for Women and Information
Technology, 2007, p.14). Both genders must be included in today’s knowledge-based economy,
as any exclusion will result in reduced economic status (Lang, 2003). It is imperative not only to
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prevent the leaks that may be present in the “pipeline,” but also to ensure that females enter the
pipeline for their own benefit as well as to benefit society as a whole.
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Appendix B
TAG: Tentative Activity Schedule
Week 1 Introductions Pre-Intervention Survey Intro to Digital Photography Self-Portrait Beginning
Week 2 Editing Self-Portrait Introduce Digital Storytelling Complete Storyboard Write Script
Week 3 Introduction to Windows Movie Maker Record Voice/Sound Edit Images
Week 4 Complete Digital Stories Week 5 Guest speaker – Art Institute of Phoenix Week 6 Introduce Web Design
Begin GooglePages Site Storyboard Pages Plan Images/Content
Week 7 Continue Work on Web Page Week 8 Guest speaker – Arizona State University
Continue Web Page Development Week 9 Complete Projects Week 10 Post-Intervention Survey
Gallery Display with Invitations to Parents and Faculty
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Appendix F
Pilot Testing
Cognitive Interview Process
As participant is completing survey
When participants pause or seem uncertain of how to respond, these clarifying questions will be asked so as to locate survey questions that may need to be modified.
1. What do you think this question is asking? 2. Why did you answer this question this way?
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Appendix G
Survey Validation Questions
1. Describe what you think a typical day is like for a person employed in the computer field.
(validates survey question 3-3)
2. When I say “information technology worker”, what image or picture comes to mind?
(validates survey question 3-4)
3. How confident are you of your computer skills? How much do you think you know
about computers in comparison to others? (validates survey question 3-1 and 3-2)
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Appendix I
Timetable
March 2008 Survey pilot testing and validation
May 2008-July 2008 Development of specific session’s activities
August 2008 Recruitment of participants
September 2008 Club begins
November 2008 Club ends
December 2008 Data analysis begins
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Appendix J
Individual Interview Questions
Post Intervention
1. Have the club’s activities increased your interest in technology careers? 2. Have the club’s activities given you a more complete picture of the people who work in
creative information technology careers? 3. Have the club’s activities increased your knowledge of the job responsibilities of the
creative information technology careers? 4. Has the club’s technology instruction increased your confidence working with
computers?