A Gender Gap Grade Analysis of Hard Sciences Courses in a School of Pharmacy


A student survey was conducted to determine perceptions of such things as differential treatment due to gender, level of preparedness for courses in the hard sciences, and gender performances of students in the sciences. Additionally, students’ grades of sixteen courses with a heavy hard science focus were analyzed by taking the percent of a letter grade sorted by male or female to determine if there was a significant gender difference in the final grades. Our objectives were to: 1) determine if the underrepresentation of women in some health-related jobs is due to discouragement of females to enter these professions or perceptions of success in hard science courses, 2) examine grades in courses with a strong biology and chemistry focus to see if a significant difference due to gender exists. We concluded that a gender gap in hard sciences grades at the School of Pharmacy did exist but the gap was not large and was not present in all courses. The majority of women were not discouraged to pursue a science based career, but there was a difference in the perceived confidence that many females exhibit in the ability to learn material in the hard science courses and in their preparedness for hard science exams.

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Hahn, E. , Santanello, C. , Worthington, R. & Ferguson, M. (2013). A Gender Gap Grade Analysis of Hard Sciences Courses in a School of Pharmacy. Creative Education, 4, 646-650. doi: 10.4236/ce.2013.410093.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Ames, C., & Archer, J. (1988). Achievement goals in the classroom: Student’s learning strategies and motivation processes. Journal of Educational Psychology, 80, 260-267.
[2] Anita Borg Institute for Women and Technology (2012). Solutions to recruit technical women. http://anitaborg.org/files/Anita-Borg-Inst-Solutions-To-Recruit-Technical-Women1.pdf
[3] Beilock, S. L., Rydell, R. J., & McConnell, A. R. (2007). Stereotype threat and working memory: Mechanisms, alleviation, and spillover. Journal of Experimental Psychology General, 136, 256-276. http://dx.doi.org/10.1037/0096-3445.136.2.256
[4] Else-Quest, N. M., Hyde, J. S., & Linn, M. C. (2010). Cross-national patterns of gender difference in mathematics: A meta-analysis. American Psychological Association, 136, 103-127.
[5] Ferrinman, K., Lubinski, D., & Benbow, C. (2009). Work preferences, life values, and personal views of top math/science graduate students and the profoundly gifted: Developmental changes and gender differences during emerging adulthood and parenthood. Journal of Personality and Social Psychology, 97, 517-532. http://dx.doi.org/10.1037/a0016030
[6] Goldin, C. (2004). Gender gap: The concise encyclopedia of economics.
[7] Guelich, J. M., Singer, B. H., Castro, M. C., & Rosenberg, L. E. (2002). A gender gap in the next generation of physician-scientists: Medical student interest and participation in research. Journal of Investigative Medicine, 50, 412-418. http://dx.doi.org/10.2310/6650.2002.32475
[8] Martens, A., Johns, M., Greenberg, J., & Schimel, J. (2006). Combating stereotype threat: The effect of self-affirmation on women’s intellectual performance. Journal of Experimental Social Psychology, 46, 236-243. http://dx.doi.org/10.1016/j.jesp.2005.04.010
[9] Miyake, A., Kost-Smith, L. E., Finkelstein, N. D., Pollock, S. J., Cohen, G. L., & Ito, T. A. (2010). Reducing the gender achievement gap in college science: A classroom study of values affirmation. Science, 2330, 1234-1237. http://dx.doi.org/10.1126/science.1195996
[10] Mullis, I., & Jenkins, L. (1988). The science report card (Report No. 17-S-01). Princeton, NJ: Educational Testing Service.
[11] Pajares, F. (2005). Gender differences in mathematics self-efficacy beliefs. In A. M. Gallagher, & J. C. Kaufman (eds.), Gender differences in mathematics: An integrative psychological approach. Boston, MA: Cambridge University Press.
[12] Schiebinger, L. L. (2001). Has feminism changed science? Cambridge, MA: Harvard University Press.
[13] Shea, P., Pickett, A., & Pelz, W. (2003). A follow-up investigation of “teaching presence” in the SUNY Learning Network. Journal of Asynchronous Learning Networks, 7, 61-80.
[14] Shepardson, D. P., & Pizzini, E. L. (1992). Gender bias in female elementary teachers’ perceptions of the scientific ability of students. Science Education, 76, 147-153.
[15] Sonnert, G. (2009). Parents who influence their children to become scientists: Effects of gender and parental education. Social Studies of Science, 39, 927-941.
[16] Spencer, S. J, Steele, C. M., & Quinn, J. (1999).Stereotype threat and women’s math performance. Journal of Experimental and Social Psychology, 35, 4-28. http://dx.doi.org/10.1006/jesp.1998.1373
[17] US Bureau of Labor Statistics (2010). BLS information. http://www.bls.gov/bls/blswage.htm
[18] US Department of Labor (2011). Women in the labor force: A databook. http://www.bls.gov/cps/wlf-databook2010.htm

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