Exams disadvantage women in introductory biology

PLoS ONE

Volumn 12, Issue 10, 2017, Pages

  Ballen, Cissy J ^a   Salehi, Shima ^b   Cotner, Sehoya ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

^b STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ANXIETY; BIOLOGY; CONTROLLED STUDY; COURSE CONTENT; DISEASE COURSE; FEMALE; HUMAN; MAJOR CLINICAL STUDY; STUDENT; EDUCATION; MALE; SEX DIFFERENCE;

BIOLOGY; FEMALE; HUMANS; MALE; SEX FACTORS;

EID: 85031741894     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0186419     Document Type: Article

References (51)

1. Beede DN, Julian TA, Langdon D, McKittrick G, Khan B, Doms ME. Women in STEM: A gender gap to innovation. Economics and Statistics Administration Issue Brief. 2011(04–11).
2. UNESCO. Gender and EFA 2000–2015: achievements and challenges. In: UNESCO, editor. Paris, France: United Nations Educational, Scientific and Cultural Organization; 2015.
3. Hale K, Burke A. Women, Minorities, and Persons with Disabilities in Science and Engineering: 2017 Arlington, VA: National Science Foundation; 2017. Available from: https://www.nsf.gov/statistics/2017/nsf17310/.
4. Greenwald AG, Krieger LH. Implicit bias: Scientific foundations. California Law Review. 2006; 94 (4):945–67.
5. Moss-Racusin CA, Dovidio JF, Brescoll VL, Graham MJ, Handelsman J. Science faculty’s subtle gender biases favor male students. Proc Natl Acad Sci U S A. 2012; 109(41):16474–9. https://doi.org/10.1073/pnas.1211286109 PMID: 22988126
6. West TV, Heilman ME, Gullett L, Moss-Racusin CA, Magee JC. Building blocks of bias: Gender composition predicts male and female group members’ evaluations of each other and the group. J Exp Soc Psychol. 2012; 48(5):1209–12.
7. Hall RM, Sandler BR. The classroom climate: a chilly one for women? 1982. Washington, DC: Association of American Colleges and Universities.
8. Eagly AH, Mladinic A. Are people prejudiced against women? Some answers from research on attitudes, gender stereotypes, and judgments of competence. Eur Rev Soc Psychol. 1994; 5(1):1–35.
9. Sheltzer JM, Smith JC. Elite male faculty in the life sciences employ fewer women. Proc Natl Acad Sci U S A. 2014; 111(28):10107–12. https://doi.org/10.1073/pnas.1403334111 PMID: 24982167
10. Reuben E, Sapienza P, Zingales L. How stereotypes impair women’s careers in science. Proc Natl Acad Sci U S A. 2014; 111(12):4403–8. https://doi.org/10.1073/pnas.1314788111 PMID: 24616490
11. Sugimoto CR, Lariviere V, Ni C, Gingras Y, Cronin B. Global gender disparities in science. Nature. 2013; 504(7479):211–3. PMID: 24350369
12. Lester J. Women in male-dominated career and technical education programs at community colleges: Barriers to participation and success. J Women Minor Sci Eng. 2010; 16(1).
13. Clance PR. The impostor phenomenon: Overcoming the fear that haunts your success: Peachtree Pub Ltd; 1985.
14. Cotner S, Ballen C, Brooks DC, Moore R. Instructor gender and student confidence in the sciences: a need for more role models. J Coll Sci Teach. 2011; 40(5):96–101.
15. Young DM, Rudman LA, Buettner HM, McLean MC. The influence of female role models on women’s implicit science cognitions. Psychol Women Q. 2013; 37(3):283–92.
16. Gillen A, Tanenbaum C. Exploring gender imbalance among STEM doctoral degree recipients. Washington, DC: American Institutes for Research. 2014.
17. Eddy SL, Brownell SE, Wenderoth MP. Gender gaps in achievement and participation in multiple introductory biology classrooms. CBE Life Sci Educ. 2014; 13(3):478–92. https://doi.org/10.1187/cbe.13-10-0204 PMID: 25185231
18. Lorenzo M, Crouch CH, Mazur E. Reducing the gender gap in the physics classroom. Am J Phys. 2006; 74(2):118–22.
19. Miyake A, Kost-Smith LE, Finkelstein ND, Pollock SJ, Cohen GL, Ito TA. Reducing the gender achievement gap in college science: A classroom study of values affirmation. Science. 2010; 330(6008):1234–7. https://doi.org/10.1126/science.1195996 PMID: 21109670
20. Brewe E, Sawtelle V, Kramer LH, O’Brien GE, Rodriguez I, Pamelá P. Toward equity through participation in Modeling Instruction in introductory university physics. Phys Rev Phys Educ Res. 2010; 6 (1):010106.
21. Pollock SJ, Finkelstein ND, Kost LE. Reducing the gender gap in the physics classroom: How sufficient is interactive engagement? Phys Rev Phys Educ Res. 2007; 3(1):010107.
22. Bell AE, Spencer SJ, Iserman E, Logel CE. Stereotype threat and women’s performance in engineering. J Eng Educ 2003; 92(4):307–12.
23. Cheema J, Galluzzo G. Analyzing the gender gap in math achievement: Evidence from a large-scale US sample. Res Ed. 2013; 90(1):98–112.
24. Hyde JS, Mertz JE. Gender, culture, and mathematics performance. Proc Natl Acad Sci U S A. 2009; 106(22):8801–7. https://doi.org/10.1073/pnas.0901265106 PMID: 19487665
25. Nguyen H-HD, Ryan AM. Does stereotype threat affect test performance of minorities and women? A meta-analysis of experimental evidence. Amer Psych Assoc; 2008; 93(6):1314–1334
26. Rask K, Tiefenthaler J. The role of grade sensitivity in explaining the gender imbalance in undergraduate economics. Econ Educ Rev. 2008; 27(6):676–87.
27. Barr DA, Gonzalez ME, Wanat SF. The leaky pipeline: Factors associated with early decline in interest in premedical studies among underrepresented minority undergraduate students. Acad Med. 2008; 83 (5):503–11. https://doi.org/10.1097/ACM.0b013e31816bda16 PMID: 18448909
28. Pintrich PR, Smith DAF, Garcia T, McKeachie WJ. A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Technical report no. 91-B-004. The Regents of the University of Michigan. 1991.
29. Norman G. Likert scales, levels of measurement and the “laws” of statistics. Adv Health Sci Educ Theory Pract. 2010; 15(5):625–32. https://doi.org/10.1007/s10459-010-9222-y PMID: 20146096
30. Paterson L, Goldstein H. New statistical methods for analysing social structures: an introduction to multilevel models. Br Educ Res J. 1991; 17(4):387–93.
31. Kreft IG, Kreft I, de Leeuw J. Introducing multilevel modeling. Newbury Park, CA: Sage Publications; 1998.
32. Akaike H. A new look at the statistical model identification. IEEE transactions on automatic control. 1974; 19(6):716–23.
33. Rosseel Y. Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). Ghent, Belgium: Ghent University; 2012.
34. Schreiber JB, Nora A, Stage FK, Barlow EA, King J. Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of educational research. 2006; 99(6):323–38.
35. Hayes AF. Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Commun monogr. 2009; 76(4):408–20.
36. Kline RB. Principles and practice of structural equation modeling. Guilford publications; 2015.
37. Westrick PA, Le H, Robbins SB, Radunzel JM, Schmidt FL. College performance and retention: a meta-analysis of the predictive validities of ACT® scores, high school grades, and SES. Educ Assess. 2015; 20(1):23–45.
38. Hulleman CS, Harackiewicz JM. Promoting interest and performance in high school science classes. Science. 2009; 326(5958):1410–2. https://doi.org/10.1126/science.1177067 PMID: 19965759
39. Jones MG, Howe A, Rua MJ. Gender differences in students’ experiences, interests, and attitudes toward science and scientists. Sci Educ. 2000; 84(2):180–92.
40. Steele J, James JB, Barnett RC. Learning in a man’s world: Examining the perceptions of undergraduate women in male-dominated academic areas. Psychol Women Q. 2002; 26(1):46–50.
41. Croizet J-C, Després G, Gauzins M-E, Huguet P, Leyens J-P, Méot A. Stereotype threat undermines intellectual performance by triggering a disruptive mental load. Pers Soc Psychol Bull 2004; 30(6):721–31. https://doi.org/10.1177/0146167204263961 PMID: 15155036
42. Martens A, Johns M, Greenberg J, Schimel J. Combating stereotype threat: The effect of self-affirmation on women’s intellectual performance. J Exp Soc Psychol. 2006; 42(2):236–43.
43. Schmader T. Gender identification moderates stereotype threat effects on women’s math performance. J Exp Soc Psychol. 2002; 38(2):194–201.
44. Steele CM. A threat in the air. How stereotypes shape intellectual identity and performance. Amer Psychol. 1997; 52(6):613–29.
45. Freeman S, Eddy SL, McDonough M, Smith MK, Okoroafor N, Jordt H, et al. Active learning increases student performance in science, engineering, and mathematics. Proc Natl Acad Sci U S A. 2014; 111 (23):8410–5. https://doi.org/10.1073/pnas.1319030111 PMID: 24821756
46. Beichner RJ, Saul JM, Abbott DS, Morse JJ, Deardorff D, Allain RJ, et al. The student-centered activities for large enrollment undergraduate programs (SCALE-UP) project. Research-based reform of university physics. 2007; 1(1):2–39.
47. Eddy SL, Hogan KA. Getting under the hood: how and for whom does increasing course structure work? CBE Life Sci Educ. 2014; 13(3):453–68. https://doi.org/10.1187/cbe.14-03-0050 PMID: 25185229
48. Haak DC, HilleRisLambers J, Pitre E, Freeman S. Increased structure and active learning reduce the achievement gap in introductory biology. Science. 2011; 332(6034):1213–6. https://doi.org/10.1126/science.1204820 PMID: 21636776
49. Spencer SJ, Steele CM, Quinn DM. Stereotype threat and women’s math performance. J Exp Soc Psychol. 1999; 35(1):4–28.
50. Shapiro JR, Williams AM, Hambarchyan M. Are all interventions created equal? A multi-threat approach to tailoring stereotype threat interventions. J Pers Soc Psychol. 2013; 104(2):277. https://doi.org/10.1037/a0030461 PMID: 23088232
51. Owens M, Stevenson J, Hadwin JA, Norgate R. When does anxiety help or hinder cognitive test performance? The role of working memory capacity. Br J Psychol. 2014; 105(1):92–101. https://doi.org/10.1111/bjop.12009 PMID: 24387098