The persistence of the gender gap in introductory physics

AIP Conference Proceedings

Volumn 1064, Issue , 2008, Pages 139-142

  Kost, Lauren E ^a   Pollock, Steven J ^a   Finkelstein, Noah D ^a  

^a UNIVERSITY OF COLORADO   (United States)

Author keywords

Conceptual learning; Gender; Introductory physics; Physics education research

Indexed keywords

EID: 57049121316     PISSN: 0094243X     EISSN: 15517616     Source Type: Conference Proceeding    
DOI: 10.1063/1.3021237     Document Type: Conference Paper

References (20)

1. S.J. Pollock et al. Phys. Rev. ST PER 3, 010107 (2007).
2. M. Lorenzo et al. Am. J Phys. 74, 118 (2006).
3. R.K. Thornton and D.R. Sokoloff, Am. J. Phys. 66, 228, (1998).
4. L.E. Kost et al, "Investigating the Source of the Gender Gap in Introductory Physics", 2007 Physics Education Research Conference, AIP Conf Proceedings 951, AIP, Melville, NY, 2007, pp. 137-140.
5. E. Mazur, Peer Instruction: A User's Manual, Upper Saddle River, NJ: Prentice-Hall, 1997.
6. CAPA, http://www.lon-capa.org/: Mastering Physics, http://www. masteringphysics.com/.
7. L.C. McDermott and P.S. Schaffer, Tutorials in Introductory Physics, Upper Saddle River, NJ: Prentice-Hall, 2002.
8. V. Otero et al. Science 313, 445 (2006).
9. S, and then averaging the normalized scores.
10. W. Adams et al, Phys. Rev. ST PER 2, 010101 (2006).
11. L. McCullough, J Int. Women's Stud. 5, 20 (2004).
12. T.L. McCaskey et al, "Effects in assessment caused by splits between belief and understanding", 2003 Physics Education Research Conference, AIP Conf. Proceedings 720, AIP, Melville, NY, 2003, pp. 37-40.
13. E. Hazel et al. Int. J Sci. Ed. 19, 381 (1997).
14. Lomax, R.G., An Introduction to Statistical Concepts for Education and Behavioral Sciences, Mahwah, NJ: Lawrence Erlbaum Associates, 2001.
15. Because of ceiling effects, heteroskedasticity, non-normal data, and non-random sampling, our data do not meet the assumptions of multiple regression that allow for unbiased interpretation of statistical significance.
16. posttest is the standard deviation of the distribution of posttest scores for all students.
17. Mendenhall, W. and Sincich, T., A Second Course in Statistics: Regression Analysis, Upper Saddle River, NJ: Pearson Education Inc., 2003.
18. The analysis was run for several threshold values and also for several numbers of posttest categories. The results were similar in all cases.
19. Z. Hazari, et al. Sci. Ed. 91, 847 (2007).
20. D.E. Meltzer, Am. J Phys. 70, 1259 (2002).