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. Acknowledgments Physics faculty: Michael Dubson Noah Finkelstein Kathy Perkins Steven Pollock Carl Wieman Ph. D. students: Charles Baily Lauren Kost Benjamin Spike Chandra Turpen Postdocs: Stephanie Chasteen Steven Goldhaber Laurel Mayhew Archie Paulson Noah Podolefsky School of Ed members: Valerie Otero Kara Gray Bud Talbott III May Lee 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

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 Lorenzo et. al. Am. J. Phys. 74, 118 (2006) Harvard Claim: Fully interactive courses eliminate the gender gap. Interactive Engagement techniques better than Traditional Lecture Hake, Am. J. Phys. 66, 64 (1998)

4. 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 Effect Size HS GPA * 0.47 SAT – Math * 0.33 ACT – Math * 0.14 FemalesMales 1 year HS Physics * 80%89% 1 year HS Calculus 70%67% * = statistically significant difference

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

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

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).

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

24. Gender Gaps in Physics 2

26. 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)

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

28. 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

29. Normalized Gain

30. Normalized Gain by semester

31. Multiple Regression

32. Matched Analysis – 1110 Gain r pre,gain = 0.281