1. 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

2. 2 Overview Background Research Questions Methods Results Discussion Limitations & Future Directions

3. 3 Background Interest 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)

4. 4 Background Growth 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)

5. 5 Background A 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

6. 6 Background Linking 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)

7. 7 Background Social Cognitive Self-Regulation Person EnvironmentBehavior Environmental Self-Regulation Behavioral Self-Regulation Covert Self- Regulation (Adapted from Bandura, 1997)

8. 8 Background Important 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

9. 9 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

10. 10 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?

11. 11 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

12. 12 Methods Survey 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; α =.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; α =.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; α =.91) –Overall, I was satisfied with my online learning experience. –This online course met my needs as a learner.

13. 13 Methods Survey 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

14. 14 Results Participant 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%) Master’s Degree (n = 48, 24%) Doctoral Degree (n = 15, 7%) Professional Degree (M.D./J.D.) (n = 16, 8%)

15. 15 Results RQ1: Pearson Correlations VariableMSD α 123456 1. Task Value4.471.16.95 .36**.17*.73**.58**.50** 2. Self-Efficacy5.361.07.89 .43**.58**.57**.41** 3. Experience5.191.37.91 .20**.36**.46** 4. Satisfaction4.561.42- .70**.59** 5. Perceived Learning4.531.45- .54** 6. Choice (Intentions to Enroll)4.321.88-  Means, Standard Deviations, Cronbach’s Alphas, and Pearson Correlations Between the Measured Variables. Note. N = 204. *p <.05. **p <.01.

16. 16 Results RQ1: Multiple Linear Regressions Variable SatisfactionPerceived Learning Choice (Intentions to Enroll) BSE BβB βB β 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 SummaryR 2 =.65, p <.001R 2 =.50, p <.001R 2 =.40, p <.001 Note. N = 204. *p <.05. **p <.001. Summary of Multiple Linear Regression Analyses Predicting Satisfaction, Perceived Learning, and Intentions to Enroll in Future Online Courses Multivariate Regression (Stevens, 2002): Wilks’ Λ =.25, F = 40.47, p <.001

17. 17 Results RQ2: Group Comparisons Variable Elective Course (n = 35) Required Course (n = 166) MSDM tdfCohen’s d Task Value5.21.864.321.144.29***62.38.81 Self-Efficacy5.561.035.341.061.1550.64- Experience5.491.255.141.391.3553.30- Satisfaction5.241.384.431.383.16**49.36.59 Perceived Learning 5.001.394.441.452.01*48.89.39 Choice5.661.454.051.854.83***59.91.90 Results of t-Tests Comparing Students Reporting on an Elective and Students Reporting on a Required Course Note. *p <.05. **p <.01. ***p <.001. 1-Way MANOVA; Wilks’ Λ =.86, F(6, 191) = 5.15, p <.001

18. 18 Discussion General 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

19. 19 Discussion Task 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

20. 20 Discussion Self-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

21. 21 Discussion Group 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

22. 22 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

23. 23 The End Questions? Paper can be downloaded at http://www.tne.uconn.edu/presentations.htm