Using Social-Cognitive Theory to Predict Students

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Neag School of Education
Task Value, Self-Efficacy, and Experience
Predicting Military Students Attitudes Toward
Self-Paced, Online Learning
Anthony R. Artino, Jr. Program in Cognition and
Instruction Department of Educational Psychology
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Overview

• Background
• Research Questions
• Methods
• Results
• Discussion
• Limitations Future Directions

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BackgroundInterest in Self-Regulated Learning

• Interest in academic self-regulation has grown
• How do students become masters of their own
  learning processes?
• Self-regulated learners efficiently control their
  own learning experiences by
• Establishing a productive work environment and
  using resources effectively
• Organizing and rehearsing information to be
  learned
• Holding positive beliefs about their
  capabilities, the value of learning, and the
  factors that influence learning (Schunk
  Zimmerman, 1998)

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BackgroundGrowth of Online Learning

• Online education has emerged as a viable
  alternative to traditional classroom instruction
  (Moore, 2003 Tallent-Runnels et al., 2006)
• Survey of 1000 U.S. colleges and universities
• 63 of schools offering undergraduate
  face-to-face courses also offer undergraduate
  courses online (Sloan Consortium, 2005)
• Department of Defense committed to transforming
  majority of face-to-face training to online
  learning (United States General Accounting
  Office, 2003)

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BackgroundA Learner-Centered Focus

• A shift from an instructor-centered to a
  learner-centered focus
• Without an ever-present instructor, students do
  not received as much guidance/structure
• Students must take greater responsibility for the
  management/control of their own learning

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BackgroundLinking Self-Regulation and Online
Learning

• Ultimately, online students may need
• well-developed self-regulated learning skills to
  guide their cognition and behavior in these
  highly independent environments (Bandura, 1997
  Schunk Zimmerman, 1998)

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BackgroundSocial Cognitive Self-Regulation
Person
Behavioral Self-Regulation
Covert Self-Regulation
Environment
Behavior
Environmental Self-Regulation
(Adapted from Bandura, 1997)
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BackgroundImportant Personal Variables

• Prior research in traditional classrooms, and
  limited research with online learning, has
  revealed the importance of
• Task Value
• Self-Efficacy
• Prior Experience
• Positively related to students use of SRL
  strategies, academic achievement, satisfaction,
  and choice behaviors

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Purpose of the Study

• To determine if the linkages between task value,
  self-efficacy, prior experience, and adaptive
  learning outcomes extend to military students
  learning in the context of self-paced, online
  training

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Research Questions

• RQ1 How do task value, self-efficacy, and prior
  experience with online learning relate to
  students overall satisfaction, perceived
  learning, and intentions to enroll in future
  online courses?
• RQ2 Are there significant differences in the
  predictor and outcome variables when comparing
  students reporting on required courses versus
  students reporting on courses they chose to
  complete?

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Methods

• Convenience sample of military personnel (n
  204) from the Naval Operational Medicine
  Institute
• Completed an online survey regarding
• the most effective self-paced, online course
  they had completed within the last two years
• Participants indicated if the course was one they
  chose to take or were required to complete

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MethodsSurvey Components

• Section 1
• 25 items Likert-type response scale
• 1-completely disagree to 7-completely agree
• Principle axis factor analysis with oblique
  rotation (Oblimin delta 0)
• 3 interpretable factors accounting for 61.6 of
  the total variance in items
• Task Value (14 items a .95)
• I liked the subject matter of this course.
• I will be able to use what I learned in this
  course in my job.
• Self-Efficacy for Learning with Self-Paced,
  Online Training (7 items a .89)
• I can perform well in a self-paced, online
  course.
• I am confident I can learn without the presence
  of an instructor to assist me.
• Satisfaction (4 items a .91)
• Overall, I was satisfied with my online learning
  experience.
• This online course met my needs as a learner.

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MethodsSurvey Components

• Section 2
• Background and demographics items
• Three individual items used as variables
• Experience
• In your estimation, how experienced are you with
  self-paced, online learning?
• 1-extremely inexperienced to 7-extremely
  experienced
• Perceived Learning
• In your estimation, how well did you learn the
  material presented in this course?
• 1-not well at all to 7-extremely well
• Choice
• What is the likelihood that you will enroll in
  another self-paced, online Navy course if you are
  not required to do so?
• 1-definitely will not enroll to 7-definitely will
  enroll

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ResultsParticipant Characteristics

• Gender
• 53 women (26)
• 150 men (74)
• Age
• Mean Age 39.0 years
• SD 9.3 years
• Range 22-69

• Educational Experience
• High School/GED (n 21, 10)
• Some College (n 51, 25)
• 2-Year College (n 24, 12)
• 4-Year College (B.S./B.A.) (n 25, 12)
• Masters Degree (n 48, 24)
• Doctoral Degree (n 15, 7)
• Professional Degree (M.D./J.D.) (n 16, 8)

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ResultsRQ1 Pearson Correlations
Means, Standard Deviations, Cronbachs Alphas,
and Pearson Correlations Between the Measured
Variables.
Variable M SD a 1 2 3 4 5 6
1. Task Value 4.47 1.16 .95 ? .36 .17 .73 .58 .50
2. Self-Efficacy 5.36 1.07 .89 ? .43 .58 .57 .41
3. Experience 5.19 1.37 .91 ? .20 .36 .46
4. Satisfaction 4.56 1.42 - ? .70 .59
5. Perceived Learning 4.53 1.45 - ? .54
6. Choice (Intentions to Enroll) 4.32 1.88 - ?
Note. N 204. p lt .05. p lt .01.
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ResultsRQ1 Multiple Linear Regressions
Summary of Multiple Linear Regression Analyses
Predicting Satisfaction, Perceived Learning, and
Intentions to Enroll in Future Online Courses
Variable Satisfaction Satisfaction Satisfaction Perceived Learning Perceived Learning Perceived Learning Choice(Intentions to Enroll) Choice(Intentions to Enroll) Choice(Intentions to Enroll)
Variable B SE B ß B SE B ß B SE B ß
Task Value .73 .06 .60 .54 .07 .43 .64 .10 .40
Self-Efficacy .52 .07 .39 .49 .08 .36 .22 .11 .12
Experience -.07 .05 -.07 .13 .06 .12 .46 .08 .33
Model Summary R2 .65, p lt .001 R2 .65, p lt .001 R2 .65, p lt .001 R2 .50, p lt .001 R2 .50, p lt .001 R2 .50, p lt .001 R2 .40, p lt .001 R2 .40, p lt .001 R2 .40, p lt .001
Multivariate Regression (Stevens, 2002)
Wilks ? .25, F 40.47, p lt .001
Note. N 204. p lt .05. p lt .001.
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ResultsRQ2 Group Comparisons
1-Way MANOVA Wilks ? .86, F(6, 191) 5.15, p
lt .001
Results of t-Tests Comparing Students Reporting
on an Elective and Students Reporting on a
Required Course
Variable Elective Course (n 35) Elective Course (n 35) Required Course (n 166) Required Course (n 166)
Variable M SD M SD t df Cohens d
Task Value 5.21 .86 4.32 1.14 4.29 62.38 .81
Self-Efficacy 5.56 1.03 5.34 1.06 1.15 50.64 -
Experience 5.49 1.25 5.14 1.39 1.35 53.30 -
Satisfaction 5.24 1.38 4.43 1.38 3.16 49.36 .59
Perceived Learning 5.00 1.39 4.44 1.45 2.01 48.89 .39
Choice 5.66 1.45 4.05 1.85 4.83 59.91 .90
Note. p lt .05. p lt .01. p lt .001.
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DiscussionGeneral Findings

• Findings generally support prior research that
  students motivational beliefs and prior
  experience are related to positive academic
  outcomes
• Results provide some evidence that these
  relationships extend to self-paced, online
  learning in the context of military training

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DiscussionTask Value

• Task value was a significant positive predictor
  of satisfaction, perceived learning, and choice
  behaviors
• Findings are consistent with prior research
• Task value ? cognitive engagement and academic
  performance (Pintrich De Groot, 1990)
• Task value ? overall satisfaction (Lee, 2002)
• Educational Implications
• Instructional elements designed to enhance value
  may improve overall satisfaction, learning, and
  choice behaviors

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DiscussionSelf-Efficacy

• Self-efficacy was a significant positive
  predictor of satisfaction and perceived learning,
  but not choice
• Findings are consistent with prior research
• Online education self-efficacy ? satisfaction
  and academic achievement (Lynch, 2002 Wang
  Newlin, 2002)
• Value beliefs tend to be better predictors of
  choice behaviors than expectancy beliefs (Eccles
  Wigfield, 1995)
• Educational Implications
• Instructional elements designed to enhance
  efficacy may improve students overall
  satisfaction and learning

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DiscussionGroup Differences

• Participants reporting on a course they chose to
  take conveyed significantly more positive
  attitudes than those reporting on required
  courses
• Findings consistent with motivation literature
  (Dai Sternberg, 2004 Pintrich Schunk, 2002)
• Educational Implications
• Organizational leaders may want to provide
  personnel with opportunities to exercise choice
  and control over their online learning activities

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Limitations Future Directions

• Limitations
• Data are correlational cannot make causal
  conclusions
• Some participants reporting on recent courses,
  some distant courses
• Use of self-reports only
• Social desirability bias
• Mono-method bias method itself may influence
  results
• Perceived learning variable is particularly
  problematic
• Future Directions
• Use more direct measures of student performance
  (i.e., course grades)
• Control for prior knowledge when studying
  interest/value (Tobias, 1994)
• Assess whether online interventions designed to
  enhance task value and self-efficacy also improve
  academic performance

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The End

• Questions?
• Paper can be downloaded at
• http//www.tne.uconn.edu/presentations.htm