What Lies beneath Sustainable Education? Predicting and Tackling Gender Differences in STEM Academic Success
Abstract
:1. Introduction
1.1. Definition of Gender Equity
1.2. The Case of the Kingdom of Saudi Arabia
2. Materials and Methods
2.1. Sample
2.2. Procedure
3. Results
3.1. Description of Gender Differences in the Sample
3.2. Do Precursors Predict College Performance Differently for Female and Male Students?
4. Discussion
5. Conclusions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Buchingham-Hatfield, S. Gender equality: A prerequisite for sustainable development. Geography 2002, 87, 227–233. [Google Scholar] [CrossRef] [Green Version]
- Maceira, H.M. Economic benefits of gender equality in the EU. Intereconomics 2017, 52, 178–183. [Google Scholar] [CrossRef] [Green Version]
- Kabeer, N.; Natali, L. Gender equality and economic growth: Is there a win-win? IDS Work. Pap. 2013, 2013, 1–58. [Google Scholar] [CrossRef]
- Corbett, C.; Hill, C. Solving the Equation: The Variables for Women’s Success in Engineering and Computing; AAUW: Washington, DC, USA, 2015. [Google Scholar]
- Catalyst. The Bottom Line: Connecting Corporate Performance and Gender Diversity; Catalyst: New York, NY, USA, 2004; pp. 1–29. [Google Scholar]
- Tesch-Römer, C.; Motel-Klingebiel, A.; Tomasik, M.J. Gender differences in subjective well-being: Comparing societies with respect to gender equality. Soc. Indic. Res. 2008, 85, 329–349. [Google Scholar] [CrossRef]
- Voyer, D.; Voyer, S.D. Gender differences in scholastic achievement: A meta-analysis. Psychol. Bull. 2014, 140, 1174–1204. [Google Scholar] [CrossRef]
- Hedges, L.V.; Nowell, A. Sex differences in mental test scores, variability, and numbers of high-scoring individuals. Science 1995, 269, 41–45. [Google Scholar] [CrossRef] [Green Version]
- Else-Quest, N.M.; Hyde, J.S.; Linn, M.C. Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychol. Bull. 2010, 136, 103–127. [Google Scholar] [CrossRef]
- Feingold, A. Cognitive gender differences are disappearing. Am. Psychol. 1988, 43, 95–103. [Google Scholar] [CrossRef]
- Alghamdi, A.K.H.; Al-Hattami, A.A. The accuracy of predicting university students’ academic success. J. Saudi Educ. Psychol. Assoc. 2014, 1, 1–8. [Google Scholar]
- Beede, D.N.; Julian, T.A.; Langdon, D.; McKittrick, G.; Khan, B.; Doms, M.E. Women in STEM: A Gender Gap to Innovation. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1964782 (accessed on 20 December 2020).
- Ceci, S.J.; Williams, W.M. Sex differences in math-intensive fields. Curr. Dir. Psychol. Sci. 2010, 19, 275–279. [Google Scholar] [CrossRef] [Green Version]
- Stoet, G.; Geary, D.C. The gender-equality paradox in science, technology, engineering, and mathematics education. Psychol. Sci. 2018, 29, 581–593. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jung, E.; Kim, J.Y.E. Women in Engineering: Almost no gap at university but a long way to go for sustaining careers. Sustainability 2020, 12, 8299. [Google Scholar] [CrossRef]
- Subrahmanian, R. Gender equality in education: Definitions and measurements. Int. J. Educ. Dev. 2005, 25, 395–407. [Google Scholar] [CrossRef]
- United Nations (UN). The 2030 Agenda for Sustainable Development: A New Roadmap to Achieve Gender Equality and the Empowerment of Women and Girls. Available online: https://sustainabledevelopment.un.org/content/documents/9783ESCWA_2030%20Agenda%20for%20Sustainable%20Development-Gender%20Equality.pdf (accessed on 16 December 2020).
- The Millennium Development Goals Report. 2015. Available online: http://www.un.org/millenniumgoals/2015_MDG_Report/pdf/MDG%202015%20rev%20(July%201).pdf (accessed on 16 December 2020).
- World Commission on Environment and Development (WCED). Report of the World Commission on Environment and Development: Our Common Future. Available online: https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf (accessed on 16 December 2020).
- Kabeer, N. Can the MDGs Provide a Pathway to Social Justice? The Challenge of Intersecting Inequalities. Available online: http://www.mdgfund.org/sites/default/files/MDGs_and_Inequalities_Final_Report.pdf (accessed on 16 December 2020).
- Glick, P.; Fiske, S.T.; Mladinic, A.; Saiz, J.L.; Abrams, D.; Masser, B.; Adetoun, B.; Osagie, J.E.; Akande, A.; Alao, A.; et al. Beyond prejudice as simple antipathy: Hostile and benevolent sexism across cultures. J. Personal. Soc. Psychol. 2000, 79, 763–775. [Google Scholar] [CrossRef]
- Bassey, S.A.; Bubu, N.G. Gender inequality in Africa: A re-examination of cultural values. Cogito Multidiscip. Res. J. 2019, 11, 21–36. [Google Scholar]
- Fontanella, L.; Sarra, A.; Di Zio, S. Do gender differences in social institutions matter in shaping gender equality in education and the labour market? Empirical evidence from developing countries. Soc. Indic. Res. 2020, 147, 133–158. [Google Scholar] [CrossRef]
- Potrafke, N.; Ursprung, H.W. Globalization and gender equality in the course of development. Eur. J. Political Econ. 2012, 28, 399–413. [Google Scholar] [CrossRef] [Green Version]
- Reuben-Shemia, D. Power and social change: The case of the European social justice movement. Soc. Altern. 2017, 36, 51–59. [Google Scholar]
- Sharp, G. The Politics of Nonviolent Action; Porter Sargent Publishers: Boston, MA, USA, 1973. [Google Scholar]
- Smith, L.; Abouammoh, A. Higher Education in Saudi Arabia; Springer: Dordrecht, The Netherlands, 2013. [Google Scholar]
- Dreher, A. Does globalization affect growth? Evidence from a new Index of Globalization. Appl. Econ. 2006, 38, 1091–1110. [Google Scholar] [CrossRef] [Green Version]
- Dreher, A.; Gaston, N.; Martens, P. Measuring Globalization: Gauging Its Consequences; Springer: Berlin, Germany, 2008. [Google Scholar]
- Gygli, S.; Haelg, F.; Potrafke, N.; Sturm, J. The KOF Globalisation Index—Revisited. Rev. Int. Organ. 2019, 14, 543–574. [Google Scholar] [CrossRef] [Green Version]
- UNESCO’s International Institute for Educational Planning. Gender Parity Index (GPI). Available online: https://learningportal.iiep.unesco.org/en/glossary/gender-parity-index-gpi (accessed on 16 December 2020).
- Ménoret, P. The Saudi Enigma: A History; Zed Books: London, UK, 2005; pp. 1–99. [Google Scholar]
- Murphy, C. A Kingdom’s Future: Saudi Arabia through the Eyes of Its Twentysomethings; Wilson Center: Washington, DC, USA, 2012. [Google Scholar]
- Sakr, N. Women and media in Saudi Arabia: Rhetoric, reductionism and realities. Br. J. Middle East. Stud. 2008, 35, 385–404. [Google Scholar] [CrossRef]
- Vision 2030 Kingdom of Saudi Arabia. Available online: https://vision2030.gov.sa/en (accessed on 16 December 2020).
- Ahmad, A.; Ali, A.A.M. The first interior design engineering program in Saudi Arabia: Relevancy to introduce the program at Yanbu University College. Procedia-Soc. Behav. Sci. 2013, 102, 335–339. [Google Scholar] [CrossRef] [Green Version]
- Luo, Y.; Al-Harbi, K. The utility of the bifactor method for unidimensionality assessment when other methods disagree: An empirical illustration. Sage Open 2016, 6, 1–7. [Google Scholar] [CrossRef]
- Hofstede, G. Culture’s Consequences: Comparing Values, Behaviors, Institutions and Organizations across Nations; Sage: Thousand Oaks, CA, USA, 2001. [Google Scholar]
- Hofstede, G.H.; Hofstede, G.J.; Minkov, M. Cultures and Organizations: Software of the Mind; McGraw-Hill: New York, NY, USA, 2010. [Google Scholar]
- McLaren, J. Evaluating Programs for Women: A Gender-Specific Framework; Prairie Women’s Health Centre of Excellence: Winnipeg, MB, Canada, 2000; pp. 6–7. [Google Scholar]
- Al Rawaf, H.S.; Simmons, C. The education of women in Saudi Arabia. Comp. Educ. 1991, 27, 287–295. [Google Scholar] [CrossRef]
- Farenga, S.J.; Joyce, B.A. Intentions of young students to enroll in science courses in the future: An examination of gender differences. Sci. Educ. 1999, 83, 55–75. [Google Scholar] [CrossRef]
- Farenga, S.J.; Joyce, B.A. What children bring to the classroom: Learning science from experience. Sch. Sci. Math. 1997, 97, 248–252. [Google Scholar] [CrossRef]
- Seymour, E.; Hunter, A.B.; Laursen, S.L.; DeAntoni, T. Establishing the benefits of research experiences for undergraduates in the sciences: First findings from a three-year study. Sci. Educ. 2004, 88, 493–534. [Google Scholar] [CrossRef] [Green Version]
- Ceyhan, G.D.; Tillotson, J.W. Early year undergraduate researchers’ reflections on the values and perceived costs of their research experience. Int. J. Stem Educ. 2020, 7, 54. [Google Scholar] [CrossRef]
- Roberts, G.E. Conducting mathematical research with undergraduates. PRIMUS 2013, 23, 785–797. [Google Scholar] [CrossRef] [Green Version]
- Ben-Eliyahu, A.; Moore, D.; Dorph, R.; Schunn, C.D. Investigating the multidimensionality of engagement: Affective, behavioral, and cognitive engagement across science activities and contexts. Contemp. Educ. Psychol. 2018, 53, 87–105. [Google Scholar] [CrossRef]
- Ortiz-Marcos, I.; Breuker, V.; Rodríguez-Rivero, R.; Kjellgren, B.; Dorel, F.; Toffolon, M.; Uribe, D.; Eccli, V. A Framework of global competence for engineers: The need for a sustainable world. Sustainability 2020, 12, 9568. [Google Scholar] [CrossRef]
- Ashraf, M.W.; Alanezi, F. Incorporation of sustainability concepts into the Engineering Core Program by adopting a micro curriculum approach: A case study in Saudi Arabia. Sustainability 2020, 12, 2901. [Google Scholar] [CrossRef] [Green Version]
- Dator, J.A. Advancing Futures: Futures Studies in Higher Education; Praeger: Westort, CT, USA, 2002. [Google Scholar]
- Kraidy, M.M. A tale of two modernities: What two preeminent scholars in Saudi Arabia and Latin America tell us about modernity and cross-cultural connections. Nacla Rep. Am. 2018, 50, 90–96. [Google Scholar] [CrossRef]
- Le Renard, A. A Society of Young Women: Opportunities of Place, Power, and Reform in Saudi Arabia; Stanford University Press: Palo Alto, CA, USA, 2014. [Google Scholar]
- Bursztyn, L.; González, A.L.; Yanagizawa-Drott, D. Misperceived social norms: Women working outside the home in Saudi Arabia. Am. Econ. Rev. 2020, 110, 2997–3029. [Google Scholar] [CrossRef]
Variables | Female Interior Design | Male Engineering | Female Business | Male Business |
---|---|---|---|---|
College Precursors | ||||
High School Grade Point Average (HSGPA) | 91.55 (0.30) | 88.12 (0.27) | 91.30 (0.21) | 85.48 (0.34) |
EPT | 43.99 (0.95) | 55.32 (0.83) | 45.69 (0.68) | 55.93 (1.01) |
Field Choice | 34.65% | 61.57% | 65.35% | 38.43% |
College Competencies | ||||
Communication | 85.63 (0.24) | 82.36 (0.18) | 85.42 (0.17) | 79.88 (0.25) |
Reasoning | 86.32 (0.30) | 82.46 (0.25) | 86.30 (0.23) | 79.71 (0.33) |
Math | 78.25 (0.34) | 78.23 (0.25) | 78.46 (0.24) | 73.82 (0.29) |
Self-Assessment | 84.98 (0.22) | 81.41 (0.17) | 86.47 (0.17) | 79.25 (0.26) |
Natural Sciences | 81.21 (0.35) | 78.74 (0.22) | 80.62 (0.28) | 76.40 (0.35) |
Ethics | 91.15 (0.22) | 87.21 (0.17) | 90.83 (0.16) | 84.56 (0.24) |
Motivation to Graduate | ||||
Credit Hours Completed | 130.31 (0.15) | 138.47 (0.08) | 126.06 (0.07) | 125.84 (0.06) |
Years to Graduation | 5.49 (0.04) | 5.61 (0.04) | 5.34 (0.03) | 5.51 (0.06) |
Motivation | 24.51 (0.18) | 25.83 (0.18) | 24.55 (0.14) | 24.51 (0.26) |
College Precursors | B | Standard Error of the Mean | Beta | t-Test | Significance (≤) |
---|---|---|---|---|---|
Female Students | |||||
(constant) | 56.450 | 1.661 | |||
HSGPA | 0.293 | 0.018 | 0.357 | 16.655 | 0.000 |
EPT | 0.048 | 0.005 | 0.187 | 8.736 | 0.000 |
Field Choice | 0.222 | 0.273 | 0.017 | 0.813 | ns |
Male Students | |||||
(constant) | 68.639 | 1.552 | |||
HSGPA | 0.092 | 0.017 | 0.128 | 5.340 | 0.000 |
EPT | 0.061 | 0.006 | 0.260 | 10.925 | 0.000 |
Field Choice | 2.271 | 0.294 | 0.184 | 7.712 | 0.000 |
College Precursors | B | Standard Error of the Mean | Beta | t-Test | Significance (≤) |
---|---|---|---|---|---|
Female Students | |||||
(constant) | 55.547 | 2.238 | |||
HSGPA | 0.320 | 0.024 | 0.298 | 13.470 | 0.000 |
EPT | 0.035 | 0.007 | 0.104 | 4.682 | 0.000 |
Field Choice | 0.000 | 0.368 | 0.000 | −0.001 | ns |
Male Students | |||||
(constant) | 69.386 | 2.136 | |||
HSGPA | 0.081 | 0.024 | 0.085 | 3.438 | 0.001 |
EPT | 0.061 | 0.008 | 0.192 | 7.877 | 0.000 |
Field Choice | 2.571 | 0.405 | 0.156 | 6.343 | 0.000 |
College Precursors | B | Standard Error of the Mean | Beta | t-Test | Significance (≤) |
---|---|---|---|---|---|
Female Students | |||||
(constant) | 33.569 | 2.266 | |||
HSGPA | 0.468 | 0.024 | 0.411 | 19.463 | 0.000 |
EPT | 0.048 | 0.007 | 0.136 | 6.440 | 0.000 |
Field Choice | −0.249 | 0.373 | −0.014 | −0.669 | ns |
Male Students | |||||
(constant) | 52.160 | 1.999 | |||
HSGPA | 0.211 | 0.022 | 0.225 | 9.565 | 0.000 |
EPT | 0.064 | 0.007 | 0.207 | 8.928 | 0.000 |
Field Choice | 3.896 | 0.379 | 0.240 | 10.275 | 0.000 |
College Precursors | B | Standard Error of the Mean | Beta | t-Test | Significance (≤) |
---|---|---|---|---|---|
Female Students | |||||
(constant) | 61.851 | 1.582 | |||
HSGPA | 0.248 | 0.017 | 0.319 | 14.772 | 0.000 |
EPT | 0.044 | 0.005 | 0.182 | 8.431 | 0.000 |
Field Choice | −1.482 | 0.260 | −0.122 | −5.703 | 0.000 |
Male Students | |||||
(constant) | 69.493 | 1.564 | |||
HSGPA | 0.085 | 0.017 | 0.120 | 4.898 | 0.000 |
EPT | 0.045 | 0.006 | 0.195 | 8.012 | 0.000 |
Field Choice | 1.964 | 0.297 | 0.162 | 6.620 | 0.000 |
College Precursors | B | Standard Error of the Mean | Beta | t-Test | Significance (≤) |
---|---|---|---|---|---|
Female Students | |||||
(constant) | 30.119 | 2.537 | |||
HSGPA | 0.517 | 0.027 | 0.404 | 19.219 | 0.000 |
EPT | 0.073 | 0.008 | 0.182 | 8.676 | 0.000 |
Field Choice | 0.578 | 0.417 | 0.029 | 1.386 | ns |
Male Students | |||||
(constant) | 56.270 | 2.014 | |||
HSGPA | 0.188 | 0.022 | 0.204 | 8.439 | 0.000 |
EPT | 0.073 | 0.007 | 0.240 | 10.036 | 0.000 |
Field Choice | 01.878 | 0.382 | 0.118 | 4.915 | 0.000 |
College Precursors | B | Standard Error of the Mean | Beta | t | Significance (≤) |
---|---|---|---|---|---|
Female Students | |||||
(constant) | 64.365 | 1.518 | |||
HSGPA | 0.298 | 0.016 | 0.393 | 18.524 | 0.000 |
EPT | −0.016 | 0.005 | −0.069 | −3.250 | 0.001 |
Field Choice | 0.212 | 0.250 | 0.018 | 0.848 | ns |
Male Students | |||||
(constant) | 67.922 | 1.474 | |||
HSGPA | 0.199 | 0.016 | 0.291 | 12.217 | 0.000 |
EPT | −0.007 | 0.005 | −0.030 | −1.290 | ns |
Field Choice | 2.120 | 0.280 | 0.179 | 7.580 | 0.000 |
College Precursors | B | Standard Error of the Mean | Beta | t | Significance (≤) |
---|---|---|---|---|---|
Female Students | |||||
(constant) | 6.866 | 1.227 | |||
HSGPA | 0.153 | 0.013 | 0.243 | 11.770 | 0.000 |
EPT | 0.081 | 0.004 | 0.414 | 20.043 | 0.000 |
Field Choice | 0.060 | 0.202 | 0.006 | 0.298 | ns |
Male Students | |||||
(constant) | 11.647 | 1.522 | |||
HSGPA | 0.097 | 0.017 | 0.137 | 5.761 | 0.000 |
EPT | 0.082 | 0.005 | 0.350 | 14.943 | 0.000 |
Field Choice | 1.111 | 0.289 | 0.091 | 3.847 | 0.000 |
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Pilotti, M.A.E. What Lies beneath Sustainable Education? Predicting and Tackling Gender Differences in STEM Academic Success. Sustainability 2021, 13, 1671. https://doi.org/10.3390/su13041671
Pilotti MAE. What Lies beneath Sustainable Education? Predicting and Tackling Gender Differences in STEM Academic Success. Sustainability. 2021; 13(4):1671. https://doi.org/10.3390/su13041671
Chicago/Turabian StylePilotti, Maura A. E. 2021. "What Lies beneath Sustainable Education? Predicting and Tackling Gender Differences in STEM Academic Success" Sustainability 13, no. 4: 1671. https://doi.org/10.3390/su13041671