Apoyo parental, creencias de autoeficacia, resultados esperados e intereses en Ciencia, Tecnología, Ingeniería y Matemáticas (STEM)
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Nuestro objetivo en este trabajo es analizar el influjo de las expectativas parentales y estereotipos de género en las creencias de autoeficacia, resultados e intereses de los alumnos. La muestra se encuentra constituida por 2364 estudiantes en el último año de la Educación Secundaria Obligatoria en España. Para el análisis de los datos se han combinado análisis descriptivos, comparación de medias y modelos de ecuaciones estructurales. Los resultados indican que los chicos perciben más apoyo parental que las chicas en tecnología e informática. En relación a los estereotipos de género, los chicos los perciben más, tanto en tecnología como en informática y ciencias. En nuestra muestra ni el apoyo parental ni los estereotipos de género tienen una influencia directa en los resultados e intereses. Sin embargo, las creencias de autoeficacia sí la tienen.
Vocational choices, gender, perceived parental support, STEM subjects, lower secondary educationelecciones vocacionales, género, apoyo parental, asignaturas STEM, educaci´ón secundaria obligatoria
Bleeker, M. M., & Jacobs, J. (2004). Achievement in math and science: do mothers’ beliefs matter 12 years later? Journal of Educational Psychology, 96(1), 97-109. https://doi.org/10.1037/0022-0663.96.1.97
Britner, G., & Pajares, F. (2001). Self-efficacy beliefs, motivation, race, and gender in middle school science. Journal of Women and Minorities in Science and Engineering, 7(4), 269–283. https://doi.org/10.1615/JWomenMinorScienEng.v7.i4.10
Britner, S. L., & Pajares, F. (2006). Sources of Science Self-Efficacy Beliefs of Middle School Students. Journal of Research in Science Teaching, 43(5), 485-499. https://doi.org/10.1002/tea.20131
Buday, S. K., Stake, J., & Peterson, Z. (2012). Gender and the choice of a science career: the impact of social support and possible selves. Sex Roles: A Journal of Research, 66(3-4), 197-209. https://doi.org/10.1007/sl1199-011-0015-4
Byars-Winston, A., & Fouad, N. A. (2008). Math and science social cognitive variables in college students. Contributions of contextual factors in predicting goals. Journal of Career Assessment, 16(4), 425-440. https://doi.org/10.1177/1069072708318901
Clegg, S., & Trayhurn, D. (1999). Gender and computing: not the same old problem. British Educational Research Journal, 26(1), 75-89. https://doi.org/10.1080/014119200109525
Dietrich, J., & Kracke, B. (2009). Career – specific parental behaviors in adolescents’ development. Journal of Vocational Behavior, 75(2), 109-119. https://doi.org/10.1016/j.jvb.2009.03.005
Duffy, R. D., Douglass, R. P., Autin, K. L., & Allan, B. A. (2014). Examining predictors and outcomes of a career calling among undergraduate students. Journal of Vocational Behavior, 85(3), 309-318. https://doi.org/10.1016/j.jvb.2014.08.009
EACEA/Eurydice. (2010). Gender Differences in Educational Outcomes: Study on the Measures Taken and the Current Situation in Europe. Brussels: Eurydice. Retrieved from http://eacea.ec.europa.eu/education/eurydice/documents/thematic_reports/120EN.pdf
EACEA/Eurydice. (2012). Developing Key Competences at School in Europe: Challenges and Opportunities for Policy. Eurydice Report. Luxembourg: Publications Office of the European Union. Retrieved from http://eacea.ec.europa.eu/education/eurydice/documents/thematic_reports/145EN.pdf
Erwin, L., & Maurutto, P. (1998). Beyond access: considering gender deficits in science education. Gender and Education, 10(1), 51-69. https://doi.org/10.1080/09540259821096
Fouad, N. A., & Smith, P. L. (1996). A test of a social cognitive model for middle school students: math and science. Journal of Counseling Psychology, 43(3), 338-346. https://doi.org//10.1037/0022-0167.43.3.338
Fouad, F., Smith, P. L., & Enochs, I. (1997). Reliability and validity evidence for the middle school self-efficacy scale. Measurement and Evaluation in Counseling and Development, 30(1), 17-31. https://doi.org/10.1037/t20421-000
Fouad, N., Kantamneni, N., Smothers, M., Chen, Y., Fitzpatrick, M., & Terry, S. (2008). Asian American career development: a qualitative analysis. Journal of Vocational Behavior, 72(1), 43-59. https://doi.org/10.1016/j.jvb.2007.10.002
Fouad, N. A., Hackett, G., Smith, P. L., Kantamneni, N., Fitzpatrick, M., Haag, S., & Spencer, D. (2010). Barriers and supports for continuing in mathematics and science: Gender and educational level differences. Journal of Vocational Behavior, 77, 361–373. https://doi.org/10.1016/j.jvb.2010.06.004
Fredricks, J. A., & Eccles, J. S. (2002). Children’s competence and value beliefs from childhood through adolescence: growth trajectories in two male-sex-typed domains. Developmental Psychology, 38(4), 519-533. https://doi.org/10.1037/0012-1649.38.4.519
Gniewosz, B., Eccles, J., & Noack, P. (2015). Early adolescents' development of academic self-concept and intrinsic task value: The role of contextual feedback. Journal of Research on Adolescence, 25(3), 459-473. https://doi.org/10.1111/jora.12140
Gunderson, E.A.; Ramirez, G., Levine, S., & Beilock, S. (2012). The role of parents and teachers in the development of gender-related math attitudes. Sex Roles, 66(3-4), 153-166. https://doi.org/10.1007/s11199-011-9996-2
Hanna, G. (1994). Cross-cultural gender differences in mathematics education. International Journal of Educational Research, 21(4), 417-426. https://doi.org/10.1016/S0883-0355(06)80030-3
Hyde, J., Lindberg, S. M., Linn, M., Ellis, A., & Williams, C. (2008). Gender similarities characterize math performance. Science, 321(5888), 494-496. https://doi.org/10.1126/science.1160364
Hoyle, R. (1995). Structural equation modeling. Concepts, Issues and Applications. London: Sage.
Inda, M., Rodríguez, C., & Peña, J. V. (2013). Gender differences in applying social cognitive career theory in engineering students. Journal of Vocational Behavior, 83(3), 346-365. https://doi.org/10.1016/j.jvb.2013.06.010
Inda-Caro, M., Rodríguez-Menéndez, C., & Peña-Calvo, J. V. (2016). Spanish High School Students’ interests in Technology: applying Social Cognitive Career Theory. Journal of Career Development, 43(4), 291-307. https://doi.org/10.1177/0894845315599253
Jacobs, J. E. (1991). Influence of gender stereotypes on parent and child mathematics attitudes. Journal of Educational Psychology, 83(4), 518-527. https://doi.org/10.1037/0022-0663.83.4.518
Jacobs, J.E., Chhin, C.S. & Bleeker, M.M. (2006). Enduring links: parent’s expectations and their young adult children’s gender-typed occupational choices. Educational Research and Evaluation, 12(4), 395-407. doi: 10.1080/13803610600765851
Jacobs, J. E., Davis-Kean, P., Bleeker, M., Eccles, J. S. & Malanchuk, O. (2005). “I can, but I don’t want to”. The impact of parents, interests and activities on gender differences in math. In A. M. Gallagher & J. C. Kaufmank. (Eds.), Gender differences in mathematics. An integrative psychological approach (pp. 246-263). New York, NY: Cambridge University Press.
Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28, 563-575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
Lent, R. W., Brown, S. D., Schmidt, J., Brenner, B., Lyons, H., & Treistman, D. (2003). Relation of contextual supports and barriers to choice behavior in engineering majors: test of alternative social cognitive models. Journal of Counseling Psychology, 50(4), 458-465. https://doi.org/10.1037/0022-0167.50.4.458
Lent, R.W., Brown, S.D., Sheu, H., Schmidt, J., Brenner, B. R., Gloster, C.S., Wilkins, G., … Treistman, D. (2005). Social cognitive predictors of academic interests and goals in engineering: utility for women and students at historically black universities. Journal of Counseling Psychology, 52(1), 84-92. https://doi.org/10.1037/0022-0167.52.1.84
Lent, R. W., Sheu, H, Miller, M., Cusick, M., Penn, L., & Truong, N. (2018). Predictors of science, technology, engineering, and mathematics choice options: a meta-analytic path analysis of the social-cognitive choice model by gender and race/ethnicity. Journal of Counseling Psychology, 65(1), 17-35. https://doi.org/10.1037/cou0000243
Lindley, L. D. (2005). Perceived barriers to career development in the context of social cognitive career theory. Journal of Career Assessment, 13(3), 271-287. https://doi.org/10.1177/1069072705274953
Linver, M. R., & Davis-Kean, P. E. (2005). The slippery slope: what predicts math grades in middle and high school? New Directions for Child and Adolescent Development, 110, 49-64. https://doi.org/10.1002/cd.149
Marbá, A., & Solsona, N. (2012). Identificación e interpretación y las posibles desigualdades formativas en ciencias de chicos y chicas en la educación obligatoria y el bachillerato [Identification and interpretation of possible differences in science education between boys and girls in compulsory secondary education and upper secondary education]. Cultura y educación, 24(3), 289-303. https://doi.org/10.1174/113564012802845659
Ministerio de Educación y Formación Profesional de España. (2019). Scientix. Retrieved from http://educalab.es/proyectos/scientix
Navarro, R., Flores, L., & Worthington, R. (2007). Mexican American middle school students’ goal intentions in mathematics and science: a test of social cognitive career theory. Journal of Counseling Psychology, 54(3), 320-335. https://doi.org/10.1037/0022-0167.54.3.320
Noack, P., Kracke, B., Gniewosz, B., & Dietrich, J. (2010). Parental and school effects on students’ occupational exploration: a longitudinal and multilevel analysis. Journal of Vocational Behavior, 77(1), 50-57. https://doi.org/10.1016/j.jvb.2010.02.006
Peña-Calvo, J. V., Inda-Caro, M., Rodríguez-Menéndez, C., & Fernández-García, C. M. (2016). Perceived supports and barriers for career development for second-year STEM students. Journal of Engineering Education, 105(2), 341-365. https://doi.org/10.1002/jee.20115
Räty, H., & Kasanen, K. (2007). Gendered views of ability in parents’ perceptions of their children’s academic competencies. Sex Roles, 56(1-2), 117-124. https://doi.org/10.1007/s11199-006-9153-5
Rodríguez-Menéndez, M. C., Torío-López, S., & Fernández-García, C.M. (2006). El impacto del género en las elecciones académicas de los estudiantes que finalizan la ESO. Revista Española de Orientación y Psicopedagogía, 17(2), 239–260. https://doi.org/10.5944/reop.vol.17.num.2.2006.11351
Sáinz, M., & Eccles, J. (2012). Self – concept of computer and math ability: gender implications across time and within ICT studies. Journal of Vocational Behavior, 80(2), 486-499. https://doi.org/10.1016/j.jvb.2011.08.005
Sáinz, M., Palmén, R., & García-Cuesta, S. (2012). Parental and secondary school teachers' perceptions of ICT and their role in the choice of studies. Sex Roles, 66(3-4), 235-249. https://doi.org/10.1007/s11199-011-0055-9.
Scott, A. B., & Mallinckrodt, B. (2005). Parental emotional support, science self-efficacy, and choice of science major in undergraduate women. The Career Development Quarterly, 53(3), 263-273. https://doi.org/10.1002/j.2161-0045.2005.tb00995.x
Simpkins, S., Davis-Kean, P., & Eccles, J. (2005). Parents’ socializing behaviour and children’s participation in math, science and computer out-of-school activities. Applied Developmental Science, 9(1), 14-30. https://doi.org/10.1207/s1532480xads0901_3
Tennenbaum, H., & Leaper, C. (2003). Parent-child conversations about science: the socialization of gender inequities? Developmental Psychology, 39(1), 34-47. https://doi.org/10.1037/0012-1649.39.1.34
Tiedemann, J. (2000). Parent’s gender stereotypes and teacher’s beliefs as predictors of children’s concept of their mathematical ability in elementary school. Journal of Educational Psychology, 92(1), 144-151. https://doi.org/10.1037/0022-0663.92.1.144
Vázquez, A., & Manassero, M. A. (2009). Patrones actitudinales de la vocación científica y tecnológica en chicas y chicos de Secundaria [Attitudinal patterns of scientific and technological talent in girls and boys in Secondary Education]. Revista Iberoamericana de Educación, 50(4), 1-12. https://doi.org/10.35362/rie5041879
Watt, H.; Eccles, J., & Durik, A. (2006). The leaky mathematics pipeline for girls. A motivational analysis of high school enrolments in Australia and the USA. Equal Opportunities International, 25(8), 642-659. https://doi.org/10.1108/02610150610719119
Wigfield, A., Eccles, J., Yoon, K., Harold, R., Arbreton, A., Freedman-Doan, C., & Blumenfeld, P. (1997). Change in children’s competence beliefs and subjective task values across the elementary school years: a 3-Year study. Journal of Educational Psychology, 89(3), 451-469. https://doi.org/10.1037/0022-0663.89.3.451
Zeldin, A. L., Britner, S. L., & Pajares, F. (2008). A comparative study of the self-efficacy beliefs of successful men and women in mathematics, science and technology careers. Journal of Research in Science Teaching, 45(9), 1036-1058. https://doi.org/10.1002/tea.20195
Zeldin, A. L., & Pajares, F. (2000). Against the odds: self-efficacy beliefs of women in mathematical, scientific and technological careers. American Educational Research Journal, 37(1), 215-246. https://doi.org/10.3102/0002831203700121