The Effects of sexism against women on men's self-efficacy and performance in Mathematics: structural equation models from the theory of ambivalent sexism
DOI:
https://doi.org/10.15359/ru.37-1.19Keywords:
Sexism, Mathematics self-efficacy, Math Tests, Structural equations models, Bayesian statisticsAbstract
[Objective] This study is intended to explain the performance in mathematics tests of men at the high school and college levels, majoring in Social Sciences, Humanities and STEM, using a SEM model based on the theory of ambivalent sexism towards women. [Methodology] Data was obtained from high school boys in urban areas (2015), as well as college men majoring in the careers mentioned before. A structural equation model was estimated using maximum likelihood and generalized least squares estimation methods. Given non-compliance with the assumptions, estimates were made using Bayesian statistical methods. Finally, goodness-of-fit measures were evaluated. [Results] In the three groups studied, the relationships matched initial expectations. For high school boys, the relationship between hostile sexism and perceived equality in mathematics was not significant (coefficient: -0.02). In the case of college men majoring in Social Sciences and Humanities, the relationship between benevolent sexism and perceived equality in mathematics was also not significant (coefficient: 0.00). In the three cases, the higher the perception of equality, the higher the level of self-efficacy of the male students, which generates better performance in mathematical tests. Likewise, the higher the level of reasoning skills of the students, the higher their levels of self-efficacy. [Conclusions] Sexist ideologies negatively influence the perception of equality in mathematical contexts. Higher levels of perception of equality are related to higher levels of performance in Mathematics tests. The importance of reasoning skills in mathematical contexts was shown by the fact that all the estimated models showed such skills to be highly positively related to mathematical test results.
References
Ayotola, A., & Adedeji, T. (2009). The relationship between mathematics self-efficacy and achievement in mathematics. Procedia - Social and Behavioral Sciences, 1(1), 953–957. https://doi.org/10.1016/j.sbspro.2009.01.169
Bandura, A. & Adams, N. E. (1977). Analysis of self-efficacy theory of behavioral change. Cognitive Therapy and Research, 1(4), 287–310. https://doi.org/10.1007/BF01663995
Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist, 44(9), 1175–1184. https://doi.org/10.1037/0003-066X.44.9.1175
Bayes, T. (1763). LII. An essay towards solving a problem in the doctrine of chances. By the late Rev. Mr. Bayes, F. R. S. communicated by Mr. Price, in a letter to John Canton, A. M. F. R. S. Philosophical Transactions of the Royal Society of London, 53, 370–418. https://doi.org/10.1098/rstl.1763.0053
Bengtsson, H. (2021). A unifying framework for parallel and distributed processing in r using futures. The R Journal, 13(2), 208–227. https://doi.org/10.32614/RJ-2021-048
Birnberg, J. G. (1964). Bayesian Statistics: A Review. Journal of Accounting Research, 2(1), 108–116. https://doi.org/10.2307/2490159
Brooks, S. P., & Gelman, A. (1998). General Methods for Monitoring Convergence of Iterative Simulations. Journal of Computational and Graphical Statistics, 7(4), 434–455. https://doi.org/10.1080/10618600.1998.10474787
Brown, C. S. & Leaper, C. (2010). Latina and European American Girls’ Experiences with Academic Sexism and their Self-Concepts in Mathematics and Science During Adolescence. Sex Roles, 63(11), 860–870. https://doi.org/10.1007/s11199-010-9856-5
Casad, B. J., Franks, J. E., Garasky, C. E., Kittleman, M. M., Roesler, A. C., Hall, D. Y., & Petzel, Z. W. (2021). Gender inequality in academia: Problems and solutions for women faculty in STEM. Journal of Neuroscience Research, 99(1), 13–23. https://doi.org/10.1002/jnr.24631
Cheung, S. F. & Lai, M. H. C. (2021). Semptools: Customizing structural equation modelling plots. https://CRAN.R-project.org/package=semptools
Cliff, A., & Montero, E. (2010). El Balance entre Excelencia y Equidad en Pruebas de Admisión: Contribuciones de Experiencias en Sudáfrica y Costa Rica. Revista Iberoamericana De Evaluación Educativa, 3(2). https://revistas.uam.es/riee/article/view/4488
Drury, B. J., & Kaiser, C. R. (2014). Allies against Sexism: The Role of Men in Confronting Sexism. Journal of Social Issues, 70(4), 637–652. https://doi.org/10.1111/josi.12083
Epskamp, S. (2022). semPlot: Path diagrams and visual analysis of various SEM packages’ output. https://CRAN.R-project.org/package=semPlot
Fennema, E., & Sherman, J. A. (1976). Fennema-Sherman Mathematics Attitudes Scales: Instruments designed to measure attitudes toward the learning of mathematics by females and males. Journal for Research in Mathematics Education, 7(5), 324-326. http://dx.doi.org/10.2307/748467
Forgasz, H. J., Leder, G. C., & Gardner, P. L. (1999). The Fennema-Sherman Mathematics as a Male Domain Scale Reexamined. Journal for Research in Mathematics Education, 30(3), 342. https://doi.org/10.2307/749839
Garaigordobil, M., Aliri, J. (2011). Sexismo hostil y benevolente relaciones con el autoconcepto, el racismo y la sensibilidad intercultural. Universidad del País Vasco. Revista de psicodidáctica, 16(2), 331-350. https://ojs.ehu.eus/index.php/psicodidactica/article/view/998/1597
Glick, P. & Fiske, S. T. (1996). The Ambivalent Sexism Inventory: Differentiating Hostile and Benevolent Sexism. Journal of Personality and Social Psychology, 70(450), 491–512. https://doi.org/10.1037/0022-3514.70.3.491
Glick, P. & Fiske, S. T. (1999). The ambivalence toward men inventory: Differentiating Hostile and Benevolent Beliefs about Men. Psychology of Women Quarterly, 23(3), 519–536. https://doi.org/10.1111/j.1471-6402.1999.tb00379.x
Glick, P., & Whitehead, J. (2010). Hostility toward men and the perceived stability of male dominance. Social Psychology, 41(3), 177–185. https://doi.org/10.1027/1864-9335/a000025
Glick, P., Lameiras, M., Fiske, S. T., Eckes, T., Masser, B., Volpato, C., Manganelli, A. M., Pek, J. C. X., Huang, L., Sakalli-Uğurlu, N., Castro, Y. R., D’Avila Pereira, M. L., Willemsen, T. M., Brunner, A., Six-Materna, I., & Wells, R. (2004). Bad but Bold: Ambivalent Attitudes Toward Men Predict Gender Inequality in 16 Nations. Journal of Personality and Social Psychology, 86(5), 713–728. https://doi.org/10.1037/0022-3514.86.5.713
Goldberger, A. S. (1972). Maximum-Likelihood Estimation of Regressions Containing Unobservable Independent Variables. International Economic Review, 13(1), 1. https://doi.org/10.2307/2525901
Graham, S. (1994). Motivation in African Americans. Review of Educational Research, 64(1), 55. https://doi.org/10.2307/1170746
Heywood, H. B. (1931). On finite sequences of real numbers. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 134(824), 486–501. https://doi.org/10.1098/rspa.1931.0209
Hoofs, H., van de Schoot, R., Jansen, N. W. H., & Kant, Ij. (2017). Evaluating Model Fit in Bayesian Confirmatory Factor Analysis with Large Samples: Simulation Study Introducing the BRMSEA. Educational and Psychological Measurement, 78(4), 537–568. https://doi.org/10.1177/0013164417709314
Hoyle, R. H. (Ed.). (2012). Handbook of structural equation modeling. The Guilford Press.
Kaplan, D. & Depaoli, S. (2012). Bayesian Structural Equation Modeling. En R. H. Doyle (Ed.), Handbook of Structural Equation Modeling (pp. 650–673).
Lent, R. W., Lopez, F. G., & Bieschke, K. J. (1991). Mathematics self-efficacy: Sources and relation to science-based career choice. Journal of Counseling Psychology, 38(4), 424–430. https://doi.org/10.1037/0022-0167.38.4.424
Lunn, D., Jackson, C., Best, N., Thomas, A., & Spiegelhalter, D. (2012). The BUGS Book. Chapman and Hall/CRC. https://doi.org/10.1201/b13613
Mena Castillo, J. P. (2015). Desarrollo en la prueba nacional de bachillerato de Matemática: Una necesidad. Cuadernos de Investigación y Formación en Educación Matemática, 10 (13), 53-66.
Merkle, E. C., & Rosseel, Y. (2018). Blavaan: Bayesian Structural Equation Models via Parameter Expansion. Journal of Statistical Software, 85(4). https://doi.org/10.18637/jss.v085.i04
Meyer, D. L. (1966). Bayesian Statistics. Review of Educational Research, 36(5), 503–516. https://doi.org/10.2307/1169478
Montero-Rojas, E., Castelain, T., Moreira, T. E., Alfaro-Rojas, L., Cerdas-Núñez, D., García-Segura, A., & Roldán-Villalobos, M. G. (2013). Evidencias iniciales de validez de criterio de los resultados de una Prueba de razonamiento con figuras para la selección de estudiantes indígenas para la Universidad de Costa Rica y el Instituto Tecnológico de Costa Rica. Revista Educación, 37(2), 103-117. https://revistas.ucr.ac.cr/index.php/educacion/article/view/12928
Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., Bar-Anan, Y., Bergh, R., Cai, H., Gonsalkorale, K., Kesebir, S., Maliszewski, N., Neto, F., Olli, E., Park, J., Schnabel, K., Shiomura, K., Tulbure, B. T., Wiers, R. W., … Greenwald, A. G. (2009). National differences in gender–science stereotypes predict national sex differences in science and math achievement. Proceedings of the National Academy of Sciences, 106(26), 10593–10597. https://doi.org/10.1073/pnas.0809921106
Plummer, M., Stukalov, A., Denwood, M. (2022). Rjags: Bayesian Graphical Models using MCMC_. R package version 4-13, https://CRAN.R-project.org/package=rjags
R Core Team. (2022a). Foreign: Read data stored by ‘minitab’, ‘s’, ‘SAS’, ‘SPSS’, ‘stata’, ‘systat’, ‘weka’, ‘dBase’, ... https://CRAN.R-project.org/package=foreign
R Core Team. (2022b). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Raftery, A. E. & Lewis, S. M. (1992). [Practical Markov Chain Monte Carlo]: Comment: One Long Run with Diagnostics: Implementation Strategies for Markov Chain Monte Carlo. Statistical Science, 7(4). https://doi.org/10.1214/ss/1177011143
Rojas Pedregosa, P. & Moreno Díaz, R. (2016). Sexismo hostil y benevolente en adolescentes. Una aproximación étnico-cultural. Revista Iberoamericana de Educación, 72(1). https://doi.org/10.35362/rie72126
Rossi, S., Xenidou‐Dervou, I., Simsek, E., Artemenko, C., Daroczy, G., Nuerk, H., & Cipora, K. (2022). Mathematics–gender stereotype endorsement influences mathematics anxiety, self‐concept, and performance differently in men and women. Annals of the New York Academy of Sciences, 1513(1), 121–139. https://doi.org/10.1111/nyas.14779
RStudio Team. (2022). RStudio: Integrated Development Environment for R. http://www.rstudio.com/
Rubin, D. B. (1984). Bayesianly Justifiable and Relevant Frequency Calculations for the Applied Statistician. The Annals of Statistics, 12(4), 1151–1172. https://doi.org/10.1214/aos/1176346785
Schunk, D. H. (1989). Self-efficacy and achievement behaviors. Educational Psychology Review, 1(3), 173–208. https://doi.org/10.1007/BF01320134
Smith-Castro, V. (comp.) (2014). Compendio de Instrumentos de Medición IIP-2014. Serie Cuadernos Metodológicos. Instituto de Investigaciones Psicológicas.
Smith-Castro, V., Montero-Rojas, E., Moreira-Mora, T. E., & Zamora-Araya, J. A. (2019). Expected and unexpected effects of sexism on women’s mathematics performance. Revista Interamericana De Psicología/Interamerican Journal of Psychology, 53(1), 28–44. https://doi.org/10.30849/rip/ijp.v53i1.905
Stawski, R. S., Almeida, D. M., Lachman, M. E., Tun, P. A., & Rosnick, C. B. (2010). Fluid cognitive ability is associated with greater exposure and smaller reactions to daily stressors. Psychology and aging, 25(2), 330–342. https://doi.org/10.1037/a0018246
Waring, E., Quinn, M., McNamara, A., Arino de la Rubia, E., Zhu, H., & Ellis, S. (2022). Skimr: Compact and flexible summaries of data. https://CRAN.R-project.org/package=skimr
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., . . . Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Zamora-Araya, J. A. (2020). Impacts of attitudes, social development, mother’s educational level and self efficacy on academic achievement in mathematics. Uniciencia, 34(1), 74–87. https://doi.org/10.15359/ru.34-1.5
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
1. Authors guarantee the journal the right to be the first publication of the work as licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
2. Authors can set separate additional agreements for non-exclusive distribution of the version of the work published in the journal (eg, place it in an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
3. The authors have declared to hold all permissions to use the resources they provided in the paper (images, tables, among others) and assume full responsibility for damages to third parties.
4. The opinions expressed in the paper are the exclusive responsibility of the authors and do not necessarily represent the opinion of the editors or the Universidad Nacional.
Uniciencia Journal and all its productions are under Creative Commons Atribución-NoComercial-SinDerivadas 4.0 Unported.
There is neither fee for access nor Article Processing Charge (APC)
