Apoyo docente y paterno en el impulso femenino por carreras STEM. Validación psicométrica de una escala.

Palabras clave: STEM, apoyo paterno, apoyo profesoral, Análisis factorial exploratorio y confirmatorio

Resumen

El papel de los padres y profesores es relevante en el impulso de las mujeres para la selección de carreras STEM. El objetivo del estudio fue la determinación de las propiedades psicométricas de una escala de medición para la estimación de las perspectivas de las estudiantes sobre el apoyo de padres y profesores en el fomento por carreras en ciencia, tecnología, ingeniería o matemáticas en instituciones de educación media superior en zonas rurales. Se desarrolló un análisis factorial exploratorio y confirmatorio, y se estimaron los principales indicadores de fiabilidad y validez. Se concluye que el modelo propuesto cumple con los atributos psicométricos necesarios para ser empleado en el estudio de este fenómeno en el contexto para el cual fue desarrollado.

Citas

Anderson, K. J., & Minke, K. M. (2007). Parent involvement in education: Toward an understanding of parents’ decision making. Journal of Educational Research, 100(5), 311–323. https://doi.org/10.3200/JOER.100.5.311-323

Avendaño Rodríguez, K. C., Magaña Medina, D. E., & Flores Crespo, P. (2020). Influencia familiar en la elección de carreras STEM (Ciencia, tecnología, ingeniería y matemáticas) en estudiantes de bachillerato. Revista de Investigación Educativa, 38(2), 515–531. https://doi.org/10.6018/rie.366311

Avendaño-Rodríguez, K. C., Magaña-Medina, D. E., & Aguilar-Morales, N. (2017). Análisis factorial exploratorio del cuestionario interés por estudios universitarios en áreas STEM (I- STEM). Revista de Análisis Cuantitativo y Estadístico, 4(13), 54–68. https://www.ecorfan.org/bolivia/researchjournals/Analisis_Cuantitativo_y_Estadistico/vol4num13/Revista_de_Analisis_Cuantitativo_y_Estadistico_V4_N13_7.pdf

Bonder, G. (2017). Infancia, Ciencia y Tecnología: un análisis de género desde el entorno familiar, educativo y cultural. Cátedra Regional UNESCO Mujer ciencia y Tecnología en América Latina - FLACSO Argentina con la Asociación Civil Chicos.net y con el apoyo de Disney Latinoamérica. http://www.catunescomujer.org/wp-content/uploads/2017/11/STEM.pdf

Cacciotti, G., Hayton, J. C., Mitchell, J. R., & Giazitzoglu, A. (2016). A reconceptualization of fear of failure in entrepreneurship. Journal of Business Venturing, 31(3), 302–325. https://doi.org/10.1016/j.jbusvent.2016.02.002

Castro, M., Expósito-casas, E., López-Martín, E., & Lizasoain, L. (2015). Parental involvement on student academic achievement : A meta-analysis. Educational Research Review, 14, 33–46. https://doi.org/10.1016/j.edurev.2015.01.002

Cech, E. A., & Blair-Loy, M. (2019). The changing career trajectories of new parents in STEM. Proceedings of the National Academy of Sciences of the United States of America, 116(10), 4182– 4187. https://doi.org/10.1073/pnas.1810862116

Chin, W. W. (1998). The partial least squares approach for structural equation modeling. En G. A. Marcoulides (Ed.), Methodology for business and management. Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates Publishers.

Christensen, R., Knezek, G., & Tyler-Wood, T. (2014). Student perceptions of science, technology, engineering, and mathematics (STEM) content and careers. Computers in Human Behavior, 34, 173–186. https://doi.org/10.1016/j.chb.2014.01.046

Dulce-Salcedo, O. V., Maldonado, D., & Sánchez, F. (2022). Is the proportion of female STEM teachers in secondary education related to women’s enrollment in tertiary education STEM programs? International Journal of Educational Development, 91(September 2019). https://doi.org/10.1016/j.ijedudev.2022.102591

Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399– 412. https://doi.org/10.1111/bjop.12046

El-Emadi, A. A., Said, Z., & Friesen, H. L. (2019). Teaching style differences between male and female science teachers in Qatari schools: Possible impact on student achievement. Eurasia Journal of Mathematics, Science and Technology Education, 15(12). https://doi.org/10.29333/ejmste/109236

Fernández-García, C. M., Torío-López, S., García-Pérez, O., & Inda-Caro, M. (2019). Apoyo parental, creencias de autoeficacia, resultados esperados e intereses STEAM.pdf. Universitas Psychologica, 18(2). https://doi.org/https://doi.org/10.11144/Javeriana.upsy18-2.ps se

Gaskin, J., James, M., and Lim, J. (2019). Master Validity Tool, [AMOS Plugin]. http://statwiki.kolobkreations.com/

Goreth, S., & Vollmer, C. (2023). Gender does not make the difference: interest in STEM by gender is fully mediated by technical socialization and degree program. International Journal of Technology and Design Education, 33(4), 1675–1697. https://doi.org/10.1007/s10798-022-09772-z

Gülhan, F. (2023). Parental Involvement in STEM Education: A Systematic Literature Review. European Journal of STEM Education, 8(1), 1–15. https://doi.org/10.20897/ejsteme/13506

Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Hernández-Mena, V., Magaña-Medina, D. E., & Avendaño, K. C. (2018). STEM disciplines: Detonating for national and regional economic development. Journal-International Economy, 2(3), 19–29. http://www.rinoe.org/taiwan/Journal_International_Economy/vol2num3/Journal_International_Economy_V2_N3_3.pdf

Hite, R. L., & Spott, J. L. (2022). Improving Parents’ and Teachers’ Perceptions of Girls’ STEM Activities and Interests Before and After an Informal STEM Intervention. The Journal of STEM Outreach, 5(1). https://doi.org/10.15695/jstem/v5i1.01

Hoferichter, F., & Raufelder, D. (2019). Mothers and Fathers—Who Matters for STEM Performance? Gender-Specific Associations Between STEM Performance, Parental Pressure, and Support During Adolescence. Frontiers in Education, 4(March), 1–10. https://doi.org/10.3389/feduc.2019.00014

Hoyle, R. H. (2023). Handbook of structural equation modeling. Guilford press. https://www.guilford.com/books/Handbook-of-Structural-Equation-Modeling/Rick-Hoyle/9781462544646

Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

IBM (2017). SPSS Statistics (Versión 25) [Computer software].

IBM (2019). SPSS Amos (Versión 26) [Computer software].

Instituto Nacional de Estadística y Geografía [INEGI]. (2023). Marco geoestadístico - Catálogo único de claves de áreas geoestadísticas estatales, municipales y localidades. Sistema de Consultas. https://www.inegi.org.mx/app/ageeml/

JASP Team (2023). JASP (Version 0.18.1) [Computer software].

Jiménez-León, R., Magaña-Medina, D. E., & Aquino-Zúñiga, S. P. (2021). Gestión de tendencias STEM en educación superior y su impacto en la industria 4.0. Journal of the Academy, 5, 99–121. https://doi.org/10.47058/joa5.7

Kantamneni, N., McCain, M. R. C., Shada, N., Hellwege, M. A., & Tate, J. (2018). Contextual Factors in the Career Development of Prospective First-Generation College Students: An Application of Social Cognitive Career Theory. Journal of Career Assessment, 26(1), 183–196. https://doi.org/10.1177/1069072716680048

King, M. F., & Bruner, G. C. (2000). Social Desirability Bias : A Neglected Aspect of Validity Testing Social Desirability Bias : A Neglected Aspect of Validity Testing. Psychology & Marketing, 17(2), 79–103. https://doi.org/10.1002/(SICI)1520-6793(200002)17

Lai, K. (2020). Fit difference between nonnested models given categorical data: measures and estimation. Structural Equation Modeling: A Multidisciplinary Journal, 1-23. https://doi.org/10.1080/10705511.2020.1763802

Ledesma, R. (2008). Introducción al Bootstrap. Tutorials in Quantitative Methods for Psychology, 4(2), 51–60. https://doi.org/10.20982/tqmp.04.2.p051

Lent, R. W., & Brown, S. D. (1994). Toward a Unifying Social Cognitive Theory of Career and Academic Interest, Choice, and Performance. Journal of Vocational Behavior, 45, 79–122. https://doi.org/0001-8791/94

Littlewood, H. F., & Bernal, E. R. (2014). Mi primer modelamiento de ecuaciones estructurales, (2da ed.). Autor.

Magaña, D., Vázquez, J. M., & Aguilar, N. (2013). Desarrollo de una escala para medir el interés en la formación Temprana en Investigación. Una muestra en estudiantes universitarios. XVII Congreso Internacional en Ciencias Administrativas, 1–30. https://docs.google.com/viewerng/viewer?url=http://gitmexico.com/acacia/busqueda/pdf/456.pdf

Montgomery, C., & Fernández-Cárdenas, J. M. (2018). Teaching STEM education through dialogue and transformative learning: global significance and local interactions in Mexico and the UK. Journal of Education for Teaching, 44(1), 2–13. https://doi.org/10.1080/02607476.2018.1422606

Sanders, M. (2009). STEM, STEM Education, STEM mania. The Technology Teacher, 68(4), 20– 27. https://vtechworks.lib.vt.edu/bitstream/handle/10919/51616/STEMmania.pdf?sequence=1&isAllowed=y

Sattari, N., & Sandefur, R. L. (2019). Gender in academic STEM: A focus on men faculty. Gender, Work and Organization, 26(2), 158–179. https://doi.org/10.1111/gwao.12249

Saw, G. & Agger, C. (2021). STEM pathways of rural and small-town students: Opportunities to learn, aspirations, preparation, and college enrollment. Educational Researcher, 50(9), 595-606. https://doi.org/10.3102/0013189X211027528

Sheldon, S. B. (2002). Parents’ Social Networks and Beliefs as Predictors of Parent Involvement. The Elementary School Journal, 102(4), 301–316. https://doi.org/10.1086/499705

Shin, S., Ha, M., & Lee, J.-K. (2016). The Development and Validation of Instrument for Measuring High School Students’ STEM Career Motivation. Journal of The Korean Association For Science Education, 36(1), 75–86. https://doi.org/10.14697/jkase.2016.36.1.0075

Stewart-Williams, S., & Halsey, L. G. (2021). Men, women, and STEM: Why the differences and what should be done? European Journal of Personality, 35(1), 3–39. https://doi.org/10.1177/0890207020962326

UNESCO. (2017). Cracking the code: Girls’ and women’s education in science, technology, engineering, and mathematics (STEM). United Nations Educational Sicentific, and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000253479

United Nations General Assembly. (2015). Transforming our world: the 2030 agenda for sustainable development. En United Nations Department of Economic and Social Affairs. United Nations. https://doi.org/10.1080/02513625.2015.1038080

Urrutia, M., Barrio, S., Gutiérrez, M., & Mayorga, M. (2015). Métodos óptimos para determinar validez de contenido. Revista Cubana de Educación Medica Superior, 28(3), 547–558. http://scielo.sld.cu/pdf/ems/v28n3/ems14314.pdf

Valdés-Cuervo, A. A., García-Vázquez, F., Torres-Acuña, G. M., Urías-Murrieta, M., & Grijalva- Quiñonez, C. S. (2019). Medición en Investigación Educativa con Apoyo del SPSS y el AMOS. Instituto Tecnológico de Sonora.

Vázquez, E. (2021). Influencias de las habilidades sociales, la autoeficacia y estereotipos de género en el interés por elección de carreras CTIM. (Tesis Doctoral). Universidad Juárez Autónoma de Tabasco.

Ventura-León, J. L., & Caycho-Rodríguez, T. (2017). El coeficiente Omega: un método alternativo para la estimación de la confiabilidad. Revista Latinoamericana en Ciencias Sociales, Niñez y Juventud, 15(1), 625–627. https://doi.org/10.11600/1692715x.13110020813

West, S., Wu, W., Mc Neish, D., & Savord, A. (2023). Model fit structural equation modeling. In R. H. Hoyle (Eds.). Handbook of structural equation modeling (pp. 184-205). Guilford press. https://www.guilford.com/books/Handbook-of-Structural-Equation-Modeling/Rick-Hoyle/9781462544646

Williams, B., & Onsman, A., & Brown, T. (2010). Exploratory factor analysis: a five-step guide for novices. Primary of Emergency Health Care, 8(3), 1–13. https://doi.org/https://doi.org/10.33151/ajp.8.3.93

Yong, A. G., & Pearce, S. (2013). A Beginner’ s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79–94. https://doi.org/10.20982/tqmp.09.2.p079

Zhou, L., Chhikara, A., Oudghiri, S., Osei-Tutu, A. A. Z., & Dwomoh, R. K. (2023). Teachers’ Perceptions on Women in STEM: Breaking the Stereotypes. Journal of STEM Teacher Education, 58(1). https://doi.org/10.61403/2158-6594.1492

Zucker, T. A., Montroy, J., Master, A., Assel, M., McCallum, C., & Yeomans-Maldonado, G. (2021). Expectancy-value theory & preschool parental involvement in informal STEM learning. Journal of Applied Developmental Psychology. https://doi.org/10.1016/j.appdev.2021.101320

Publicado
2024-01-01