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Impact of Student Motivation & Learning Strategies on Physical Geology Performance

Explore how student values, motivations, and strategies influence academic success in geology courses. The study examines various factors like self-efficacy and study habits using MSLQ. Results show significant correlations between specific subscales and student performance.

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Impact of Student Motivation & Learning Strategies on Physical Geology Performance

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  1. The Effect of Student Motivation and Learning Strategies on Performance in Physical Geology Courses: GARNET Part 4, Student Performance Ann BYKERK-KAUFFMAN, Ronald K. MATHENEY, Matthew NYMAN, David McCONNELL, Jennifer A. STEMPIEN, David A. BUDD, Lisa GILBERT, Megan JONES, Catharine KNIGHT, Katrien KRAFT, Ryan NELL, Dexter PERKINS, Rachel TEASDALE, Tatiana VISLOVA, and Karl R. WIRTH

  2. How do students’ values, motivations, expectations, and study strategies affect their performance in our classes? GARNET: Geoscience Affective Research Network

  3. MSLQ Instrument Motivated Strategies for Learning Questionnaire* (MSLQ) used to investigate how aspects of the affective domain varied for students. GARNET: Geoscience Affective Research Network * Pintrich, P.R., Smith, D.A.F., Garcia, T., and McKeachie, W.J., 1991, NCRIPTL Report 91-B-004

  4. Examples of Questions Comprising Subscales Self-Efficacy (one of the “Motivation” subscales) • I believe I will receive an excellent grade in this class. • I’m confident I can understand the basic concepts taught in this course. • I’m certain I can understand the most difficult material presented in the readings for this course. • I’m confident I can understand the most complex material presented by the instructor in this course. • I’m confident I can do an excellent job on the assignments and tests in this course. • I expect to do well in this class. • I’m certain I can master the skills being taught in this class. • Considering the difficulty of this course, the teacher, and my skills, I think I will do well in this class. GARNET: Geoscience Affective Research Network

  5. Examples of Questions Comprising Subscales Time and Study Environment (one of the “Study Strategies” subscales) • I usually study in a place where I can concentrate on my course work. • I make good use of my study time for this course. • I find it hard to stick to a study schedule. (REVERSED) • I have a regular place set aside for studying. • I make sure I keep up with the weekly readings and assignments for this course. • I attend class regularly. • I often find that I don’t spend very much time on this course because of other activities. (REVERSED) • I rarely find time to review my notes or readings before an exam. (REVERSED). GARNET: Geoscience Affective Research Network

  6. Students are scored separately on each of the 15 subscales, on a 7-point scale. GARNET: Geoscience Affective Research Network A high score on any of the subscales should, theoretically, enhance performance.

  7. Which of the 15 MSLQ subscales significantly affect student performance? By how much? GARNET: Geoscience Affective Research Network

  8. Method: Forward Stepwise Regression of MSLQ subscales against student performance (e.g. final grade) GARNET: Geoscience Affective Research Network • We consider the significance of each MSLQ subscale individually, then test combinations of significant subscales. • We can clearly see the individual contribution made by each MSLQ subscale to student performance. • E.g. X1 and X4 are more influential to the student performance than X2 and X3. • Multiple correlated regressors (X1-X4) make it difficult to tell which MSLQ subscale is the most significant contributor to student performance.

  9. Result of this Step-Wise Analysis: • Model Equation for Student Score • Score = 1.17 + 5.7(TS) +4.5(SE) -3.01(R) GARNET: Geoscience Affective Research Network Significant MSLQ Subscales

  10. Result of this Step-Wise Analysis: • Model Equation for Student Score • Score = 1.17 + 5.7(TS) +4.5(SE) -3.01(R) GARNET: Geoscience Affective Research Network The bigger this number, the more significance that subscale has.

  11. The average final score per class ranged from 70% to 90% Average Score GARNET: Geoscience Affective Research Network Class ID In order to make valid comparisons across classes and institutions, we calculated each student’s percentile rank within his/her class.

  12. GARNET: Geoscience Affective Research Network Our stepwise regression of the Pre-Course survey results yielded the following formula: Score = 1.17 + 5.7(TS) +4.5(SE) -3.01(R) SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal

  13. Pre-Course MSLQ Scores Correlated with Performance, 2008-2009 Academic Year GARNET: Geoscience Affective Research Network 100% SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal 90 80% y = 0.086x + 45.41 70 60% Model Performance (Percentile Rank within Class) 50 40% 30 20% Model Score = 1.17 + 5.7(TS) +4.5(SE) -3.01(R) R2 = 0.06 10 0% 0% 20% 40% 60% 80% 100% Actual Performance (Percentile Rank within Class)

  14. GARNET: Geoscience Affective Research Network Our stepwise regression of the Post-Course survey results yielded the following formula: Score = -12.78 + 9.2(SE) +6.3(TS) -3.1(R) SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal

  15. Post-Course MSLQ Scores Correlated with Performance, 2008-2009 Academic Year GARNET: Geoscience Affective Research Network SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal 100% 90 80% y = 0.227x + 37.82 70 60% Model Performance (Percentile Rank within Class) 50 40% 30 20% Model Score = -12.78 + 9.2 (SE) +6.3(TS) -3.1(R) R2 = 0.23 10 0% 0% 10 20% 30 40% 50 60% 70 80% 90 100% Actual Performance (Percentile Rank within Class)

  16. Self-Efficacy Model Score = -12.78 + 9.2 (SE) +6.3(TS) -3.1(R) GARNET: Geoscience Affective Research Network • Students with high self-efficacyare confident that they can • Understand class material • Do well on assignments and exams • Master the skills taught in the course The factor that had the strongest correlation with performance was Self-Efficacy.

  17. Time and Study Environment Model Score = -12.78 + 9.2 (SE) +6.3(TS) -3.1(R) GARNET: Geoscience Affective Research Network • Spend scheduled time studying in a place free of distractions • Keep up with readings and assignments. • Attend class regularly Students who score high on the time and study environment scale

  18. Rehearsal Model Score = -12.78 + 9.2 (SE) +6.3(TS) -3.1(R) GARNET: Geoscience Affective Research Network • Reciting items from lists • Reading class notes and course readings • Memorizing key words Students who score high on the rehearsal scale spend study time repeatedly Rehearsal was negatively correlated with performance!

  19. Changes in MSLQ Scores over the Semester GARNET: Geoscience Affective Research Network Self Efficacy Pre Post Top 25% Middle 50% Bottom 25% Time and Study Environment Pre Post These changes were exactly in the wrong direction! Rehearsal Pre Post

  20. Post-Course Correlations Among the 15 Scales of the MSLQ (Motivated Strategies for Learning Questionnaire) GARNET: Geoscience Affective Research Network Strong Correlation Weak Correlation

  21. Self-Efficacy correlates strongly with • Internal Goal Orientation • Task Value • Control of Learning Beliefs GARNET: Geoscience Affective Research Network

  22. Intrinsic Goal Orientation GARNET: Geoscience Affective Research Network • Perceive learning tasks as ends in themselves, not just means to an end. • Are motivated by challenge, curiosity, and a desire for mastery. Students who score high on the intrinsic goal orientation scale

  23. Task Value GARNET: Geoscience Affective Research Network • Like the subject matter of the course. • Perceive the course material to be interesting, important and useful. Students who score high on the task value scale

  24. Control of Learning Beliefs GARNET: Geoscience Affective Research Network • Students who score high on the control of learning beliefsscale feel that their individual study efforts determine their academic performance.

  25. Time and Study Environment • correlated strongly with • Metacognitive Self-Regulation • Effort Regulation GARNET: Geoscience Affective Research Network

  26. Metacognitive Self-Regulation GARNET: Geoscience Affective Research Network Students who score high on the metacognitive self-regulation scale plan, monitor and regulate their cognitive activities. They tend to… • Stay focused in class and while studying • Vary their study strategies with varying conditions • Work to clear up confusions • Ask themselves questions to check for understanding

  27. Effort Regulation GARNET: Geoscience Affective Research Network Students who score high on the effort regulation scale persevere. They work hard, even when they feel lazy, are uninterested in the course material, or find the material to be difficult.

  28. Conclusions GARNET: Geoscience Affective Research Network • The MSLQ scores that are significantly correlated to student performance are • Self-Efficacy (positive correlation) • Time and Study Environment (positive correlation) • Rehearsal (negative correlation) • Changes in MSLQ scores over the semester are in exactly the wrong direction. • Self-Efficacy decreases • Time and Study Environment decreases • Rehearsal increases • Perhaps we can improve student performance by working to reverse these trends.

  29. Acknowledgements GARNET: Geoscience Affective Research Network • Thanks to NSF for funding this project • Thanks to the 320 student participants who patiently completed the 80-question MSLQ twice and agreed to let us use their data. • Special thanks to David McConnell for organizing the GARNET project. • Special thanks to Jen Stempien for her awesome SAS psychotherapy skills.

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