Female top performers in higher education STEM and humanities: socio-emotional perceptions and digital learning-related characteristics during COVID-19

Year 2020, Volume: 8 Issue: 4, 1373 - 1385, 15.12.2020

Albert Ziegler , Svenja Bedenlier Michaela Gläser - Zikuda Bärbel Kopp Marion Händel

https://doi.org/10.17478/jegys.811344

Cited By: 1

Abstract

In Germany, the 2020 summer semester was substantially influenced by the COVID-19 pandemic. In an empirical study, we focus on female top performing students in STEM and the humanities. Of particular interest was whether the measures associated with the pandemic constitute a risk-factor for a re-traditionalization of gender roles. Before lectures or courses began, students at a full-scale university were invited to participate in an online survey. We investigated four research questions: 1) Are women underrepresented in our sample among the top performers in STEM and the humanities? Are there gender differences among top performers with regard to (2) digital readiness, (3) socio-emotional and (4) learning related variables? The sample of the study consisted of 2,849 higher education STEM and humanities students. The study took place as an online survey. In the week before the start of the official lecture period, all students enrolled at the university were invited to take part via an e-mail correspondence from the Vice President of Education (survey access link). Participation in the survey took place via the Questback platform and was activated for 10 days. The cut-off point for the ability level was set at the 95th percentile of previous university achievements. To test Q1, we performed a hierarchical loglinear analysis with posthoc Chi² tests. In research questions Q2 - Q4 two-way ANOVAs were used to test the effects of gender and subject. Results indicate equal shares of female and male students among the top performers, with women overrepresented in the humanities and men overrepresented in STEM relative to their proportion of the student population. The analysis of socio-emotional and learning-related factors showed risk factors for high performing female students such as lower self-efficacy, but no major emotional vulnerability. Overall, the data suggest that at the beginning of the COVID-19 pandemic, female top performers had still been able to compensate for the risk factors.

Keywords

Gender, STEM, Humanities, Higher Education, High Ability, COVID-19, Digital Learning, Socio-emotional perceptions

Thanks

Albert Ziegler suggested the topic of the article to his co-authors. All researchers in this study have the same contributions.

References

• Alabbasi, A.M., Alaa, A.E., & Ziegler, A. (2020). Are gifted students more emotionally intelligent than their non-gifted peers? A meta-analysis. High Ability Studies, 31. https://dx.doi.org/10.1080/13598139.2020.1770704
• Allmendinger, J. (2020a). Die Frauen verlieren ihre Würde [Women lose their dignity]. Zeit online, 12. Retrieved from https://www.zeit.de/gesellschaft/zeitgeschehen/2020-05/familie-corona-krise-frauen-rollenverteilung-rueckentwicklung/komplettansicht
• Allmendinger, J. (2020b). „Frauen werden entsetzliche Retraditionalisierung erfahren.“ [„Women will experience a terrible retraditionalization.“] Retrieved from https://www.ardmediathek.de/daserste/video/anne-will/-frauen-werden-entsetzliche-retraditionalisierung-erfahren--/das-erste/Y3JpZDovL25kci5kZS9lYWJlZTI4ZC1jMGNiLTQ3MDYtOWZiNC0wN2U5MTk3YTExYTU/
• Anderson, K.J. (2015). Modern misogyny: Anti-feminism in a post‐feminist era. Oxford: Oxford University Press.
• Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S.-L. (2009). Measuring self-regulation in online and blended learning environments. The Internet and Higher Education, 12(1), 1–6. http://dx.doi.org/10.1016/j.iheduc.2008.10.005
• Beckwith, J. (1983). Gender and math performance: Does biology have implications for educational policy? Journal of Education, 165(2), 158-174. doi:10.1177/002205748316500204
• Beierlein, C., Kemper, C. J., Kovaleva, A., & Rammstedt, B. (2013). Short scale for measuring general self-efficacy beliefs (ASKU). MDA, 7(2). https://doi.org/10.12758/mda.2013.014
• Benbow, C. & Stanley, J. C. (1980). Sex differences in mathematical ability: Fact or artifact? Science, 210, 1262–1264. DOI: 10.1126/science.7434028
• Berntsen, D., Rubin, D. C., & Siegler, I. C. (2011). Two versions of life: Emotionally negative and positive life events have different roles in the organization of life story and identity. Emotion, 11(5), 1190–1201. https://doi.org/10.1037/a0024940
• Bian, L., Leslie, S.-J., & Cimpian, A. (2017). Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science 355, 389–391. doi:10.1126/science.aah6524
• Braun, A., März, A., Mertens, F., & Nisser, A. (2020). Rethinking education in the digital age. Retrieved from https://www.vditz.de/fileadmin/media/publications/pdf/EPRS_STU_2020_641528_EN.pdf
• Brody, L. R., & Hall, J. A. (2010). Gender, emotion, and socialization. In J. C. Chrisler & D. R. McCreary. (Eds.), Handbook of gender research in psychology (pp. 429-454). New York, NY: Springer. doi:10.1007/978-1-4419-1465-1_21
• Card, D. & Giuliano, L. (2016). Universal screening increases the representation of low-income and minority students in gifted education. PNAS, 113(48), 13678-13683. https://doi.org/10.1073/pnas.1605043113
• Ceci, S. J., & Williams, W. M. (Eds.). (2007). Why aren't more women in science? Top researchers debate the evidence. Washington, DC: American Psychological Association. https://doi.org/10.1037/11546-000
• Cidlinská, K. (2019). How not to scare off women: Different needs of female early-stage researchers in STEM and SSH fields and the implications for support measures. Higher Education, 78(2), 365–388. https://doi.org/10.1007/s10734-018-0347-x
• Crawford, B. F., Snyder, K. J., & Adelson, J. L. (2019). Exploring obstacles faced by gifted minority students through Bronfenbrenner’s bioecological systems theory. High Ability Studies, 31(1), 43-74. https://doi.org/10.1080/13598139.2019.1568231
• Crowley, K., Callanan, M. A., Tenenbaum, H. R., & Allen, E. (2001). Parents explain more often to boys than to girls during shared scientific thinking. Psychological Science, 12(3), 258-261. doi:10.1111/1467-9280.00347
• Dai, D. & Kuo, C. C. (Eds.) (2017). Gifted education in Asia: Problems and prospects. Charlotte, NC: Information Age Publishing.
• Delaney, J. & Devereux, P. J. (2019). It's not just for boys! Understanding gender differences in STEM. IZA paper, 12176. Retrieved from https://voxeu.org/article/understanding-gender-differences-stem
• DiPrete, T. A. & Eirich, G. M. (2006). Cumulative advantage as a mechanism for inequality: A review of theoretical and empirical developments. Annual Review of Sociology, 32(1), 271-297. https://doi.org/10.1146/annurev.soc.32.061604.123127
• Eagly, A. H., & Miller, D. I. (2016). Scientific Eminence: Where are the women? Perspectives on Psychological Science, 11(6), 899-904. doi:10.1177/1745691616663918
• Eddy, S., Brownell, S. E., & Wenderoth, M. P. (2014). Gender gaps in achievement and participation in multiple introductory biology classrooms. CBE-Life Sciences Education, 13(3), 478–92. https://doi.org/10.1187/cbe.13-10-0204
• Ericsson, K. A., Hoffmann, R. R., Kozbelt, A., & Williams, A. M. (2018). The Cambridge handbook of expertise and expert performance. New York, NY: Cambridge University Press.
• FAU (2020a). Scholarship organisations. Retrieved from https://www.fau.eu/education/student-life/financing-your-studies/scholarship-organisations/
• FAU (2020b). ARIADNE TechNat. Retrieved from https://www.mentoring.fau.eu/ariadne-technat/
• FAU (2020c). Gender. Retrieved from https://www.gender-und-diversity.fau.de/gender/
• Feldon, D. F., Maher, M. A, Roksa, J., & Peugh, J. (2016). Cumulative advantage in the skill development of STEM graduate students: A mixed-methods study. American Educational Research Journal, 53(1), 132-161. doi:10.3102/0002831215619942
• Fliege, H., Rose, M., Arck, P., Levenstein, S., & Klapp, B.F. (2001). Validierung des “Perceived Stress Questionnaire“ (PSQ) an einer deutschen Stichprobe [Validation of the Perceived Stress Questionnaire (PSQ) on a German sample]. Diagnostica, 47(3), 142–152. https://doi.org/10.1026//0012-1924.47.3.142
• Fliege, H., Rose, M., Arck, P., Walter, O.B., Kocalevent, R. D., Weber, C., & Klapp, B.F. (2005). The Perceived Stress Questionnaire (PSQ) reconsidered: Validation and reference values from different clinical and healthy adult samples. Psychosomatic Medicine, 67(1), 78–88. https://doi.org/10.1097/01.psy.0000151491.80178.78
• Ganem, N. M. & Manasse, M. (2011). The relationship between scholarships and student success: An art and design case study. Education Research International, 1— 8. https://doi.org/10.1155/2011/743120
• Gierveld, J.D.J., & van Tilburg, T. (2006). A 6-item scale for overall, emotional, and social loneliness. Research on Aging, 28(5), 582–598. https://doi.org/10.1177/0164027506289723
• Gong, X., Wong, N., & Wang, D. (2018). Are gender differences in emotion culturally universal? Comparison of emotional intensity between Chinese and German samples. Journal of Cross-Cultural Psychology,49(6), 993-1005. doi:10.1177/0022022118768434
• González, C. (2001). Undergraduate research, graduate mentoring, and the university's mission. Science, 293, 1624-1626, DOI: 10.1126/science.1062714
• Gottzén, L., Mellström, U., & Shefer, T. (Eds.) (2020). Routledge international handbook of masculinity studies. London: Routledge. https://doi.org/10.4324/9781315165165
• Grunspan, D. Z, Eddy, S. L, Brownell, S. E., Wiggins, B. L, Crowe, A. J, & Goodreau, S. M. (2016). Males under-estimate academic performance of their female peers in undergraduate Biology classrooms. PLoS ONE 11(2): e0148405. https://doi.org/10.1371/journal.pone.0148405
• Hargrove, L. Godin, D., & Dodd, B. (2008). College outcomes comparisons by AP and Non-AP High School experiences. Retrieved from: http://research.collegeboard.org/publications/content/2012/05/college-outcomes-comparisons-ap-and-non-ap-high-school-experiences
• Hentschel, S., Eid, M. & Kutscher, T. (2017). The influence of major life events and personality traits on the stability of affective well-being. Journal of Happiness Studies, 18, 719–741. https://doi.org/10.1007/s10902-016-9744-y
• Herrmann, S. D., Adelman, R. M., Bodford, J. E., Graudejus, O., Okun, M. A., & Kwan, V S. Y. (2016). The effects of a female role model on academic performance and persistence of women in STEM courses. Basic and Applied Social Psychology, 38(5), 258-268. https://doi.org/10.1080/01973533.2016.1209757
• Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations. Beverly Hills, CA: SAGE.
• Holman, E. A., Thompson, R. R., Garfin, D. R., & Cohen Silver, R. (2020). The unfolding COVID-19 pandemic: A probability-based, nationally representative study of mental health in the U.S. Sciences Advances. doi:10.1126/sciadv.abd5390
• Holmes, E. A., O'Connor, R. C., Perry, V. H., Tracey, I., Wessely, S., Arseneault, L., Ballard, C., Christensen, H., Cohen Silver, R., Everall, I., Ford, T., John, A., Kabir, T., King, K.,
• Madan, I., Michie. S., Przybylski, A. K., Shafran, R., Sweeney, A., Worthman, C. M., Yardley, L., Cowan, K., Cope, C., Hotopf, M., Bullmore, E. (2020). Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry, 7(6), 547-560. doi: 10.1016/S2215-0366(20)30168-1
• Hunter, J. E., Schmidt, F. L., & Judiesch, M. K. (1990). Individual differences in output variability as a function of job complexity. Journal of Applied Psychology, 75(1), 28–42.
• John, J. M., Gropper, H., & Thiel, A. (2019). The role of critical life events in the talent development pathways of athletes and musicians: A systematic review. Psychology of Sport & Exercise, 45. https://doi.org/10.1016/j.psychsport.2019.101565.
• Johnson, C. C., Peters-Burton, E. E., & Moore, T. J. (2016). STEM road map: A framework for integrated STEM education. New York: Routledge.
• Joyce, W. F. & Slocum, J. W. (2012). Top management talent, strategic capabilities, and firm performance. Organizational Dynamics, 41, 183—193. https://doi.org/10.1016/j.orgdyn.2012.03.001
• Kim, H. J., Hong, A. J., & Song, H. (2019). The roles of academic engagement and digital readiness in students’ achievements in university e-learning environments. International Journal of Educational Technology in Higher Education, 16, 21. https://doi.org/10.1186/s41239-019-0152-3
• Lincoln, A. E., Pincus, S., Koster, J. B., & Leboy, P. S. (2012). The Matilda effect in science: Awards and prizes in the United States, 1990s and 2000s. Social Studies of Science, 42, 307–320. doi:10.1177/0306312711435830
• Lott, J. L., Gardner, S., & Powers, D. A. (2009). Doctoral student attrition in the STEM fields: An exploratory event history analysis. Journal of College Student Retention: Research, Theory & Practice, 11(2), 247-266. doi:10.2190/CS.11.2.e
• Luong, K. T., Knobloch-Westerwick, S., & Niewiesk, S. (2020). Superstars within reach: The role of perceived attainability and role congruity in media role models on women's social comparisons. Communication Monographs, 87(1). doi:10.1080/03637751.2019.1622143
• Makarova, E., Aeschlimann, B. & Herzog, W. (2019). The gender gap in STEM fields: The impact of the gender stereotype of math and science on secondary students' career aspirations. Frontiers in Education, 4. 10.3389/feduc.2019.00060
• Meyer, M., Cimpian, A., & Leslie, S.-J. (2015). Women are underrepresented in fields where success is believed to require brilliance. Frontiers in Psychology, 6, Article 235. https://doi.org/10.3389/fpsyg.2015.00235
• Michaels, E., Handfield-Jones, H., & Axelrod, B. (2001). The war for talent. Boston: Harvard Business School.
• Milkman, K., Akinola, M. & Chugh, D. (2015). What happens before? A field experiment exploring how pay and representation differentially shape bias on the pathway into organizations. Journal of Applied Psychology, 100(6), 1678–1712. https://doi.org/10.1037/apl0000022
• Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012). Science faculty's subtle gender biases favor male students. PNAS, 109(41), 16474–16479. https://doi.org/10.1073/pnas.1211286109
• Murphy, M. C., Steele, C. M., & Gross, J. J. (2007). Signaling threat: How situational cues affect women in math, science, and engineering settings. Psychological Science, 18(10), 879–885. https://doi.org/10.1111/j.1467-9280.2007.01995.x
• O'Boyle, E., Jr., & Aguinis, H. (2012). The best and the rest: Revisiting the norm of normality of individual performance. Personnel Psychology, 65(1), 79–119. https://doi.org/10.1111/j.1744-6570.2011.01239.x
• Pfeiffer, S., Foley-Nicpon, M., & Shaunessy-Dedrick, E. (2018). APA handbook of giftedness and talent. Washington, DC: American Psychological Association.
• Petersen, J. (2013). Gender differences in identification of gifted youth and in gifted program participation: A meta-analysis. Contemporary Educational Psychology, 38(4), 342-348. https://doi.org/10.1016/j.cedpsych.2013.07.002
• Reutlinger, M., Pfeiffer, W., Stoeger, H., Vialle, W. & Ziegler, A. (2020). Domain-specificity of educational and learning capital: A study with musical talents. Frontiers in Psychology, 11: 561974. doi: 10.3389/fpsyg.2020.561974
• Rindermann, H. (2018). Cognitive capitalism: human capital and the well-being of nations. Cambridge, UK: Cambridge University Press.
• Rindermann, H., Sailer, M.,& Thompson, J. (2009).The impact of smart fractions, cognitive ability of politicians and average competence of peoples on social development. Talent Development & Excellence, 1, 3–25.
• Robinson-Cimpian, J. P., Lubienski, S. T., Ganley, C. M., & Copur-Gencturk, Y. (2014). Teachers’ perceptions of students’ mathematics proficiency may exacerbate early gender gaps in achievement. Developmental Psychology, 50(4), 1262—1281. https://doi.org/10.1037/a0035073
• Rokach. A. (2018). The effect of gender and culture on loneliness: A mini review. Emerging Science Journal, 2(2), 1-6. doi: 10.28991/esj-2018-01128
• Shavinina, L. (2009). Handbook on giftedness. New York: Springer.
• Simonton, D. K. (2018). From giftedness to eminence: Developmental landmarks across the lifespan. In S. I. Pfeiffer, E. Shaunessy-Dedrick, & M. Foley-Nicpon (Eds.), APA handbook of giftedness and talent (p. 273–285). Washington: American Psychological Association. https://doi.org/10.1037/0000038-018
• Simonton, D. K. (2019). Talent development in the domain of academic psychology. In R. F. Subotnik, P. Olszewski-Kubilius, & F. C. Worrell (Eds.), The psychology of high performance: Developing human potential into domain-specific talent (p. 201–224). Washington: American Psychological Association. https://doi.org/10.1037/0000120-010
• Skelton, C. B., Francis, B. & Smulyan, L. (Eds.) (2006). Handbook of gender and education. London: Sage.
• Smits, N., & Vorst, H. C. M. (2007). Reducing the length of questionnaires through structurally incomplete designs: An illustration. Learning and Individual Differences, 17(1), 25–34. https://doi.org/10.1016/j.lindif.2006.12.005
• Stadler, H. & Duit, R. & Benke, G. (2000). Do boys and girls understand physics differently? Physics Education, 35, 417-423. 10.1088/0031-9120/35/6/307
• Steele, C. M. (2013). Whistling Vivaldi: How stereotypes affect us and what we can do. New York: Norton.
• Stoeger, H., Schirner, S., Laemmle, L., Obergriesser, S., Heilemann, M., & Ziegler, A. (2016). A contextual perspective on talented female participants and their development in extracurricular STEM programs. Annals of the New York Academy of Sciences, 1377, 53–66. 10.1111/nyas.13116
• Storage, D., Horne, Z., Cimpian, A., Leslie, S.-J. (2016). The Frequency of “Brilliant” and “Genius” in teaching evaluations predicts the representation of women and African Americans across fields. PLoS ONE 11(3): e0150194. https://doi.org/10.1371/journal.pone.0150194
• Subotnik, R. F., Olszewski-Kubilius, P., & Worrell, F. C. (2019). The psychology of high performance. Washington, DC: APA.
• Trusz, S. (2020). Why do females choose to study humanities or social sciences, while males prefer technology or science? Some intrapersonal and interpersonal predictors. Social Psychology of Education, 23, 615–639. https://doi.org/10.1007/s11218-020-09551-5
• Upson, S., & Friedman, L. F. (2012). Where are all the female geniuses? Scientific American Mind, 23(5), 63-65. doi: 10.1038/scientificamericanmind1112-63 Vindegaard, N., & Benros, M. E. (2020). COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain, Behavior, and Immunity, 30:S
• Vladut, A., Liu, Q., Leana-Tascila, M., Vialle, W. & Ziegler, A. (2013). A cross-cultural validation study of the Questionnaire of Educational and Learning Capital (QELC) in China, Germany and Turkey. Psychological Test and Assessment Modeling, 55, 462-478.
• Voyer, D., & Voyer, S. D. (2014). Gender differences in scholastic achievement: A meta-analysis. Psychological Bulletin, 140(4), 1174–1204. https://doi.org/10.1037/a0036620
• Wai, J. & Lakin, J. M. (2020). Finding the missing Einsteins: Expanding the breadth of cognitive and noncognitive measures used in academic services. Contemporary Educational Psychology, 63, 101920. https://doi.org/10.1016/j.cedpsych.2020.101920
• Warne, R. T. (2017). Research on the academic benefits of the advanced placement program: Taking stock and looking forward. SAGE Open, 1-16. doi:10.1177/2158244016682996
• Wood, W., & Eagly, A. H. (2002). A cross-cultural analysis of the behavior of women and men: Implications for the origins of sex differences. Psychological Bulletin, 128, 699-727. doi:10.1037/0033-2909.128.5.699
• Workman, J., & Heyder, A. (2020). Gender achievement gaps: the role of social costs to trying hard in high school. Social Psychology of Education (2020). https://doi.org/10.1007/s11218-020-09588-6
• Wu, D. J., Park, J., & Dasgupta, N. (2020). The influence of male faces on stereotype activation among women in STEM: An ERP investigation. Biological Psychology, 156. https://doi.org/10.1016/j.biopsycho.2020.107948
• Yalcinkaya, N. S. & Adams, G. (2020). A cultural psychological model of cross-national variation in gender gaps in STEM participation. Personality and Social Psychology Review, 1–26. https://doi.org/10.1177/1088868320947005
• Ziegler, A., Debatin, T., & Stoeger, H. (2019). Learning resources and talent development from a systemic point of view. Annals of the New York Academy of Sciences, 1445, 39—51. https://doi.org/10.1111/nyas.14018
• Zhou, Y., MacGeorge, E. L., & Myrick, J. G., (2020). Mental health and its predictors during the early months of the COVID-19 pandemic experience in the United States. International Journal of Environmental Research and Public Health, 17(17), 6315. https://doi.org/10.3390/ijerph17176315