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Examining the Gender Gap in Introductory Physics

Examining the Gender Gap in Introductory Physics. Lauren Kost Steven Pollock, Noah Finkelstein Department of Physics, University of Colorado at Boulder May 4, 2009.

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Examining the Gender Gap in Introductory Physics

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  1. Examining the Gender Gap in Introductory Physics Lauren Kost Steven Pollock, Noah Finkelstein Department of Physics, University of Colorado at Boulder May 4, 2009

  2. This material is based upon work supported by the National Science Foundation under Grant No. REC 0448176, CAREER: Physics Education and Contexts of Student Learning. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the NSF Acknowledgments • Postdocs: • Stephanie Chasteen • Steven Goldhaber • Laurel Mayhew • Archie Paulson • Noah Podolefsky • School of Ed members: • Valerie Otero • Kara Gray • Bud Talbott III • May Lee • Physics faculty: • Michael Dubson • Noah Finkelstein • Kathy Perkins • Steven Pollock • Carl Wieman • Ph. D. students: • Charles Baily • Lauren Kost • Benjamin Spike • Chandra Turpen

  3. Motivation • AIP Statistics: • 50% of physics students in HS are female • 22% of bachelors in physics go to females • 10% of faculty in physics are female Interactive Engagement techniques better than Traditional Lecture Harvard Claim: Fully interactive courses eliminate the gender gap. Hake, Am. J. Phys.66, 64 (1998) Lorenzo et. al. Am. J. Phys.74, 118 (2006)

  4. Gender Gaps at CU Boulder

  5. Gender Gaps at CU Boulder

  6. Gender Gaps at CU Boulder

  7. Conclusions (I) • Despite fully interactive techniques, gender gap persists at our institution • Harvard claims results independent of instructor, we see otherwise • Where does the gender gap come from? Why does it exist? • Do gender differences exist in other aspects of the introductory course?

  8. Gender Gaps in Course Grades

  9. Gender Gaps in CLASS Shifts

  10. Gender Gaps in Background * = statistically significant difference

  11. Impact of Pretest on Post Test 8% 22% 14% 22% 20% 21% 21% 16% 37% 19% rpre,post = 0.56

  12. Regression Analysis • Control for prior physics and math knowledge and incoming attitudes and beliefs • Multiple Regression • The average posttest gender difference is 3%(reduced from the observed difference of 10%). • 70% of the gender gap is accounted for by background differences.

  13. Conclusions (II) • Gender differences exist in several components of introductory course • Males and females are differently prepared • Differences in male and female backgrounds account for about 70% of the gender gap • How do males and females experience the introductory physics course?

  14. Current Work • Survey on student experiences • Clickers & Peer Instruction • Tutorials • Physics Identity • Epistemology • Sources of Self-Efficacy

  15. Peer Instruction • How comfortable do you feel discussing the physics content with your peers during clicker questions? p = 0.3

  16. Physics Identity • I feel like I could be a good physicist. p < 0.001

  17. Physics Self-Efficacy • I worried about my ability to solve physics problems on exams. p < 0.001 p < 0.001

  18. Different Experiences

  19. Conclusions (III) • The gender gap persists at our institution • Gender gap largely due to background differences of males and females • Preliminary evidence to suggest differences in how males and females experience the course

  20. Thank You • Find more info at: http://per.colorado.edu • Kost, et al, PRST PER 5, 010101 (2009).

  21. Physics Self-Efficacy • Physics makes me feel uneasy. p < 0.001 p < 0.001

  22. Gender Gaps in Physics 2

  23. Gender Gaps in Physics 2

  24. Courses, Student Population, and Data • 7 semesters introductory, calculus-based mechanics • 3 semesters Partially Interactive (without Tutorials) • 4 semesters Fully Interactive (with Tutorials) • Student population • 25% female • 50% engineering majors (6% physics majors) • 80% white • Data sources • Matched FMCE pre/post data (N ~ 2100) • Matched CLASS pre/post data (N ~ 1900) • Course grades (N ~ 3600) • Demographic and background data (N ~ 3600)

  25. Gender Gaps at CU Boulder Pollock, et. al. Phys. Rev. ST PER,3, 010107 (2007)

  26. Conclusions • Even when controlling for physics background, math skills, and attitudes and beliefs, gender is still a significant factor in posttest score. • Accounted for only 43% of variation in post test scores, other factors to consider

  27. Normalized Gain

  28. Normalized Gain by semester

  29. Multiple Regression

  30. Matched Analysis – 1110 Gain rpre,gain = 0.281

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