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Lisa Keefe Doctoral Dissertation Seminar

Contextualized Measurement of Self-efficacy and College Students’ Perceived Sources of Self-efficacy in Introductory Plant Science Courses. Lisa Keefe Doctoral Dissertation Seminar. Overview. Introduction Theoretical Framework Review of Literature Dissertation Conceptual Framework

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Lisa Keefe Doctoral Dissertation Seminar

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  1. Contextualized Measurement of Self-efficacy and College Students’ Perceived Sources of Self-efficacy in Introductory Plant Science Courses Lisa Keefe Doctoral Dissertation Seminar

  2. Overview • Introduction • Theoretical Framework • Review of Literature • Dissertation Conceptual Framework • Study #1 • Study #2 • Implications for Practice

  3. Introduction Science Literacy & Career

  4. Theoretical Framework • Bandura (1997)definition of SE: belief in personal capabilities to organize and execute tasks required to produce specific results within a specific context • 4 Sources of SE I do… I hear… I see… I feel…

  5. Review of Literature • Self-efficacy (SE) = good predictor of academic performance. • SE has been studied in the sciences • Need for context-specific studies • Sources of SE also important but few existing studies (Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the literature and future directions. Review of Educational Research, 78(4), 751-796 Schunk, D., Pintrich, P. R., & Meece, J. (Eds.). (2007a). Motivation in dducation: Theory, research and applications (3rd ed.): Pearson. Klassen, R., & Usher, E. (2010). Self-efficacy in educational settings: Recent research and emerging directions. In S. Karabenick & T. Urdan (Eds.), Advances in motivation and achievement (Vol. 16a): Emerald Group Publishing Limited. Gore, P. A. (2006b). Academic self-efficacy as a predictor of dollege outcomes: Two incremental validity studies. Journal of Career Assessment, 14(1), 92-115. doi: 10.1177/1069072705281367

  6. Conceptual Framework

  7. Study 1-Measuring Self-efficacy • Current Instruments • Participants • Development • Data collection and analysis • Results • Limitations • Measuring Plant SE (Instrument Development) • EFA n=248 • CFA n=241

  8. Current Instruments • Science Motivation Questionnaire (Glynn, Taasoobshirazi, & Brickman, 2009) Baldwin, J. A., Ebert-May, D., & Burns, D. J. (1999). The development of a college biology self-efficacy instrument for nonmajors. Science Education, 83(4), 397-408. Glynn, S. M., Taasoobshirazi, G., & Brickman, P. (2009). Science Motivation Questionnaire: Construct validation with nonscience majors. Journal of Research in Science Teaching, 46(2), 127-146. doi: 10.1002/tea.20267 Dalgety, J., Coll, R. K., & Jones, A. (2003). Development of chemistry attitudes and experiences questionnaire (CAEQ). Journal of Research in Science Teaching, 40(7), 649-668 Uzuntiryaki, E., & ÇapaAydın, Y. (2009). Development and Validation of Chemistry Self-Efficacy Scale for College Students. Research in Science Education, 39(4), 539-551.

  9. Participants HORT 101, BTNY 110 & AGRY 105 major (M), science major (SM) and non-science major (NSM) CFA:Fall 2012 (n=241) M=24% SM=19% NSM=57% EFA:Spring 2012 (n=248) • M=20% • SM=32% • NSM=48% 80% White/caucasian & 50% male/female ratio

  10. Development

  11. Data Collection and Analysis • Students told about the research before participating. Also asked if concurrently enrolled and not to fill out questionnaire twice • 1st group factor analysis (EFA) • 2nd group confirmatory factor analysis (CFA)

  12. EFA Results

  13. ITEM1 .72 ITEM2 .83 ITEM3 .66 .61 ITEM4 .61 ITEM5 .61 ITEM6 e1 .79 ITEM7 .67 e2 ITEM8 e8 PC .66 .82 e3 ITEM9 e9 GS .68 e4 ITEM10 e10 .68 ITEM11 e11 e5 .69 .67 .71 ITEM12 e12 e6 e7 ITEM13 e13 ITEM14 e14 MS .71 ITEM15 e15 .75 .84 ITEM16 e16 .66 ITEM17 e17 .64 CFI (0.92) RMSEA (0.08) GFI (0.88) GSSE PCSE MSSE

  14. Please rate how confident you are in your ability to perform the following tasks today. 1) Not at all confident 2) Slightly confident 3) Somewhat confident 4) Mostly confident 5) Extremely confident • PCSE • Explain how a plant produces food and uses energy. • Predict how a plant will respond to a given environmental condition. • GSSE • Instruct a classmate on how to write an experiment report. • Ask a research question that could be answered experimentally. • MSSE • Use concepts of life science in solving everyday problems at home. • Tutor another student in a 1st year life science course.

  15. Limitations and Recommendations • Minimally adequate model fit • Small # of students • Demographics (High non-science majors/low racial diversity)

  16. For Practice • Measures SE of core (lynchpin) plant science concepts • Measures SE of translatable science skills • Fills a need for SE questionnaire aimed at core plant science concepts/skills and may have use in any introductory plant science class

  17. Study 2-Sources of Self-efficacy in an introductory plant science class • Participants • Deductive analysis • Results • Limitations • Exploring Sources of Plant SE (Qualitative) • Short-answer (initial coding) n=200+ • Interviews (Provisional Coding) n=4 • Literature (Triangulation)

  18. Participants Short-answer (n=>200) • 200+ students enrolled in HORT 101, AGRY 105 or BTNY 110 • Spring semester 2012 and Fall 2012 Interview-Fall semester 2012 (n=4) • 2 Landscape Architecture majors • Alice had taken a plant biology dual-credit course • Melinda’s parents own a landscaping company • 2 Agricultural Education majors • Rose had little experience but parents dabbled in row crops • Adam had an interest in gardening

  19. Deductive Analysis Realism assumes a single, blurry reality; therefore, we made every effort to triangulate our data in order to illustrate a single, complex reality as experienced through context and perception (Sobh & Perry, 2006).

  20. Short-answer • Please rate how confident you are in your ability to perform the following tasks as of today— • Achieve success in another life science class • Receive good grades on exams in this course • “Think about the reasons you considered when answering the question above. Describe briefly all of the reasons on which you based your confidence rating to this particular question. Include everything that comes to mind in the spaces provided.” Hutchison, M. A., Follman, D. K., Sumpter, M., & Bodner, G. M. (2006). Factors influencing the self-efficacy beliefs of first-year engineering students. Journal of Engineering Education, 39-47.

  21. Results of Short-answer and Interviews

  22. Example Provisional Coding Initial coding “We kind of covered a lot compared to what we would have covered in high school so I guess that amount of material surprised me first and foremost. Some of it was a little more than I thought was, not necessarily that it was more than what should have been taught, it was just more coming in with no knowledge, like prior knowledge of any of this.” Saldana, J. (2013). The coding manual for qualitative researchers (2nd ed.). Washington D.C.: Sage.

  23. Limitations • Overlapping constructs - Further qualitative study focusing on the interaction of these constructs • A narrow perspective from the limited number and diversity of interviews.

  24. Practice • Process of measuring sources of SE provide a framework for college departments of any field to better assess student outcomes early in a course • Qualitative inquiry can be time consuming, but when using deductive analysis, the time commitment can be manageable. • Sources could be studied with a rating scale

  25. Summary of Implications for Practice

  26. Acknowledgements Committee Members: Neil Knobloch Kathryn Orvis Levon Esters Jon Harbor Plant Scientist Team: Kathryn Orvis Lori Snyder Michael Zanis John Cavaletto NIFA Grant 2010-01801: Enhancing science capacity in introductory Animal, Plant, and Food sciences courses Students enrolled in HORT 101, AGRY 105 & BTNY 210 2011-2012 Grant Team Leaders: Bryan Hains Mark Balschweid

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