copyright(c) 2003 insook lee all rights reserved 1 self-regulation, self-efficacy and e-learning...

1 copyright(c) 2003 Insook Lee All rights reserved

Self-Regulation, Self-Efficacy and e-Learning Strategies during e-Learning and

Academic Achievement

Insook Lee Sejong University

AECT 2003 Annual ConferenceAnaheim, CA. USA

2003. 10.23


the maturity of information society. the increase of the demands for distributed learning, lifelong learning, and learner-regulated learning

cyberspace: openness, flexibility, decentralization the increase of needs for self regulation (Knowles, 1998) Within the increased flexibility of the new technology, the

learning results may vary depending on individual learners’ intellectual competencies and learning preferences(Jacobson & Spiro, 1995; Owston, 1997; Windschitl, 1998).

Introduction


Introduction self regulated learning’s impacts on learning

processes and learning achievement: • various research evidences • Its impacts are prospected to be stronger in e-learning

environment (Hartley & Bendixen, 2001). • But, most research on e-learning simply applies and

presupposes the same learning strategies identified and discussed in the traditional face-to-face learning environment.

• increased need for reconsideration of self regulated learning roles within e-learning context in a systemic and multidimensional way.


to examine self-regulated learning strategies(Zimmerman & Martinez-Pons), self-efficacy (Pintrich & DeGroot), and e-learning strategies (Lee) within the e-learning environment

to search for implications for instructional interventions. 1. How are the self-regulated learning strategies, self-

efficacy, and e-learning strategies related to student academic achievement within the e-learning environment?

2. What are the relations among self-regulated learning

strategies, self-efficacy, and e-learning strategies?

Goals of Study


meaningful learning : the foremost goal of education

characteristics of meaningful learning: The concept of ‘self-regulated’ is emphasized.

self-regulation: broad and complex concept. Each researcher proposes his/her own concepts and categories according to his/her theoretical background and interests.

Literature Review


Zimmerman(1990): explaining self-regulation with the systematic use of meta-cognitive, motivational and behavioral learning strategies

meta-cognitive: practicing of planning, goal setting, organization, self-monitoring, self-evaluation

motivational aspects (Paris, Lipson, & Wixson, 1983; Pintrich & De Groot, 1990) : self-efficacy, self-consequencing, internal task interest, efforts and endurance (Borkowski et. al., 1990; Henderson, 1986; Schunk, 1986; Zimmerman & Martinez-Pons, 1986)

Behavioral aspects: seeking assistance, seeking information, seeking for appropriate learning environment, self instruction, and self reinforcement, etc. (Diaz & Neal, 1992; Henderson, 1986; Rohrkemper, 1989; Zimmerman, 1990; Zimmerman & Martinez-Pons, 1986).

Literature Review


Time management considered to be part of resource management

(Zimmerman & Martinez-Pons, 1986), part of self-management (Pintrich and DeGroot, 1999)

can deeply influence learning ability Effective use of learning time is the product of learning

strategies such as planning and goal setting (Zimmerman, Greenberg, & Weinstein, 1994).

Literature Review


Time management: Macan, Shahani, Dipboye, & Phillips (1990)

Time management: multi-dimensional characteristics

Critical relations among time management, learning performance and stress

Time management: Delucchi. Rohwer, & Thomas (1987) Identifying the relations between learning time allocation

styles and learning achievement

Literature Review


Time management: Britton & Tesser (1991)

Time management behavior predicted learning achievement more than IQ (SAT score) did.

College students, time management test, after 4 years, comparing with GPA.

Literature Review


Time management: Trueman & Hartley (1995)

British college students. applying Britton & Tesser’s research frame(1991). scales of time management and one semester’s GPA

findings in 3 categories different from Britton & Tesser’s

daily planning and long term planning: more outstandingly appeared in this research, comparing to Britton & Tessor’s.

confidence on long term planning: slightly but significantly correlated with various learning outcomes

Literature Review


Time management: e-learning E-learning demands learners abilities to operate their own

time, to process information, and to plan and manage materials (Hanna, Glowacki-Dudka, & Conceicao-Runlee, 2000).

Self-regulation is emphasized as the critical factors when considering e-learning environment design and instructional strategies.

• Burge(1993), Eastmond(1993)• Lee (2000), Lee (2002), Lee (2003) • Jo & Lim (2002)

Literature Review


Burge (1993): e-learning strategies Especially choice-making, expression, group interaction, and

organization of information

Eastmond (1993): e-learning strategies effective use of the features of multiple discussion,

information overload, and text ambiguity development of strategies required for online information

processing decision of how to contribute to cyber community transferred strategies from F2F: time management, learning

styles, social skills, positive attitudes, goal setting, information seeking, self-confidence

Literature Review


Lee (2000) : web based e-learning context college students’ e-learning strategies expression, information processing, self-regulation, and

seeking for human resources

Lee (2001): web based e-learning context adults learners over 20 years old. the relationship between

8 e-learning strategies and learning achievement time management, self-efficacy, and positive attitude:

positively predict learning achievement

Literature Review


Lee (2002) gender differences on self-regulated learning in the e-

learning context interaction, information processing, sincerity, and

persistence

Jo & Lim (2002) time management : negative predication on learning

achievement with the Goal based Scenario e-Learning context

Literature Review


Melburg and Others(1993) 800 adults, to develop assessment tools for the distance

education context by applying Weinstein’s LASSI 10 sub variables categories did not appear in the distance

education context. Also elements of each sub variable category was not well concordance with LASSI.

implications: 1. Adult learners in distance education environment may have

learning needs slightly different from traditional campus based one.

2. can’t fully assess learning strategies variables in distance or e-learning environment with traditional self-regulated variables only

Literature Review


Implications of Literature Review: Not everybody receives the same benefits from self-regulated

environment. Learners need to have self-regulation in learner-controlled

environment such as e-learning environment. high possibilities that self-regulation variables and categories

identified in traditional F2F settings may have some limitations in understanding self-regulated learning strategies in e-learning environment

Nonetheless, current literature lacks interests on holistic and specific understanding of self-regulation in e-learning environment itself.

Literature Review


Study Methods and ProceduresSubjects randomly selected 77 adult learners who were enrolled in one

of the Korea's Digital Distance Universities varied in terms of the majors, ages, and genders (22

freshmen &55 sophomores; 33 in social sciences, 22 in electronics and engineering, & 22 in arts; 46 males & 31 females). Age spans: 21∼57

Instruments Three kinds of questionnaires were employed and each item

was designed with 5-point Likert scales. self-regulated learning strategies by Zimmerman and

Martinez-Pons (a 14 Item questionnaire) self-efficacy by Pintrich and De Groot (a 9 item questionnaire) e-learning strategies by Lee (a 39-item survey questionnaire)


Zimmerman & Martinez-Pons’ 14 Self-regulated strategy:

1) Self-evaluating 2) Organizing & transforming 3) Goal setting & planning 4) Seeking information 6) Environment structuring 7) Self-consequencing 8) Rehearsing & memorizing 9) Seeking assistance Peer/Teacher/Adult, and 10) Reviewing Test/Notes/Texts

Internal consistency in the current study: Cronbach's α=.90

Study Methods and Procedures


Pintrich & DeGroot’s (1990) self-efficacy 9 self-efficacy items from Motivated Strategies for Learning

Questionnaire (MSLQ). Originally 7-point Likert scales but revised to 5 points. (Cronbach's α=.89)

• Compared with other students in this class I expect to do well.• I’m certain I can understand the idea taught in this course.• I expect to do very well in this class.• Compared with others in this class, I think I’m a good student.• I am sure I can do an excellent job oh the problems and tasks

assigned for this class.• I think I will receive a good grade in the class.• My study skills are excellent compared with others in this class• Compared with other students in this class I think I know a great deal

about the subject.• I know that I will be able to learn the material for this class.



Lee (2001) e-learning strategies 8 sub categories, 39 items, 5 point Likert scale

Expression (in text) α=.78 Multiplicity in interaction α=.83

Group Discussion I item Information overload α=.57

Information processing α=.81 Asynchronicity management α=.70

Time management α=.75 Information interpretation α=.74



Learning Achievement Analysis individual learner’s one semester GPA (4.3 point scale) totally 58 courses offered. midterm, final exam, assignments, and learning activities:

varied combinations

more than half of the courses used midterm and final exams only for grading.

20 courses used attendance rates for grading and in average 10% of the total grade points



Research Findings1. How are the self-regulated learning strategies, self-

efficacy, and e-learning strategies related to student academic achievement within the e-learning environment?

‘time management’ (Beta =0.55, R=0. 478, p <. 001): the most significant predictor on academic achievement

step-wise

variables R R² Β F PTime management 0.478 0.228 .551 17.461 .000

Information interpretation 0.540 0.292 -.263 11.961 .000


In addition, only Lee’s e-learning strategies significantly predicted academic achievement (F=3.37. p=0.03); however, not Zimmerman’s self-regulated learning strategies (F=2.44, P=.123) and Pintrich’s self-efficacy (F=3.51, p=0.065).

Variables R R² F PE-learning strategiesSelf-efficacySelf-regulated Learning strategies

0.5770.2130.179

0.3330.0450.032

3.3723.5072.439

.003

.065

.123

total 0.588 0.346 2.641 .011

Research Findings


2. What are the relations among self-regulated learning strategies, self-efficacy, and e-learning strategies?

positive and moderately high relations among self-regulated learning strategies, self-efficacy, and e-learning strategies

e-Learningstrategies

Pearson CorrelationN

1.000 63

Self-efficacyPearson CorrelationN

.634** 1.000 62 76

Self-regulated Learning strategies

Pearson CorrelationN

.637** .605** 1.000 62 75 76

**p < .01

Research Findings

e-Learning strategies self-efficacy Self-regulated learning strategies


confirmed in the e-learning environment the close correlation between Zimmerman’s self-regulated learning strategies and Pintrich’s self-efficacy well identified in the traditional learning environment.

Moreover, identified the close correlation between e-learning strategies and self-regulated learning strategies/self-efficacy.

In the contrary, however, group discussion, information processing, and time management within Lee’s e-learning strategies were not associated with self-regulation and self-efficacy (p > 0.05) or slightly associated with. This result indicated that e-learning strategies may not be e-learning strategies may not be comprehensively dealt with by the traditional framework of comprehensively dealt with by the traditional framework of self-regulation and self-efficacyself-regulation and self-efficacy.

Research Findings


- - - - - - - - - -

.768** - - - - - - - - -

.570** .580** - - - - - - - -

.580** .583** .394** - - - - - - -

.702** .644** .396** .631** - - - - - -

.700** .705** .364** .453** .677** - - - - -

.369** .482** .212 .239* .460** .635** - - - -

.371** .458** .310* .594** .521** .378** .294* - - -

.513** .462** .263* .335** .536** .681** .605** .361** - -

.669** .562* .235* .449** .690** .715** .385** .159 .605** -

* P 〈 0.05, ** P 〈 0.01

Research Findingsvariables

Expression

ExpressionMultiplicity in interaction

Group Discussion

Information overload

Information processing

Asynchronicity management

Time management

Information interpretation

Self-efficacy

Self-regulated learning strategies

Multiple discussionDiscussion

managementInformation

overloadInformation management

Asynchronicity management

Time managementInformation

interpretationSelf-

efficacySelf-

regulated learning strategies


Discussion and Conclusion

1. What are the relations among self-regulated learning strategies, self-efficacy, and e-learning strategies?

the higher Zimmerman & Martinez-pons’ self regulation, the

higher Pintrich & DeGroot’s self-efficacy, the higher Lee’s e-learning strategies

in the e-learning environment: • the higher Pintrich & DeGroot’s self efficacy, the higher time

management - regular and efficient learning time use, successful use of asynchronous learning environment and potentiality

• The better Zimmerman & Martinez-pons’ self-regulation, the better asynchronocity management, information processing, and expression.


Positive correlation between Zimmerman & Martinez-pons’ self-regulation and Pintrich & DeGroot’s self-efficacy appears in the e-learning environment too.

But, some strategy variables with no or little relations are identified. What it means? the need for academic efforts to understand and identify specific self-regulation strategies newly appearing or more outstanding in e-learning environment

information interpretation, group discussion, time management, and information overload: high possibility to be ignored in the research framework in F2F environment.



2. How are the self-regulated learning strategies, self-efficacy, and e-learning strategies related to academic achievement within the e-learning envirionments?

Various research on time management that can predict learning achievement (Britton & Tesser, 1991; Trueman & Hartley, 1995) or that is correlated with learning achievement (Macan, Shahani, Dipboye, & Phillips, 1990) is confirmed in the current e-learning context.

Confirms various research that time management is the most predicting variable for learning achievement in e-learning environment (Lee, 2002; Lee, 2003; Jo & Lim, 2002).

Implies that there would be limitations in supporting self-regulation in e-learning environment if we rely on solely the models and schemes based on F2F environment such as Zimmerman & Martinez-pons’ and Pintrich & DeGroot’s….



Q & A

[email protected] http://www.sejong.ac.kr/~inlee

copyright(c) 2003 insook lee all rights reserved 1 self-regulation, self-efficacy and e-learning...

Documents