Elección de carrera: efecto de la interacción entre alumnas y maestras de las áreas Ciencia, Tecnología, Ingeniería Y Matemáticas (CTIM) en Colombia 2015

dc.contributor.advisorEnríquez Sierra, Hernán Daríospa
dc.contributor.advisorBayona Rodríguez, Hernandospa
dc.contributor.authorEspinosa Borda, Briyid Camilaspa
dc.date.accessioned2020-07-15T17:07:51Zspa
dc.date.available2020-07-15T17:07:51Zspa
dc.date.issued2019-12-16spa
dc.description.abstractThe aim of this research is to evaluate the effect of interactions between female students and STEM teachers, over career choice expectations in Colombia. A role model approach is used to explain how motivational factors affect the STEM career choice of women pursuing high school. Data of PISA 2015 for Colombia is used to estimate the likelihood of choosing a STEM career, through a Hierarchical Logit model, controlling by covariates like self-efficacy, teacher bias, school fixed effects and parent’s education. Results show that women’s STEM career choice is not influenced by interaction with a STEM woman teacher throughout the high school. On the other hand, student’s self-efficacy has a positive impact in her career choice expectation. Also, a woman pursuing high school at a private school with vocational program has less likelihood to choose a STEM career than her counterpart at a public school with vocational program.spa
dc.description.abstractEl objetivo de esta investigación es evaluar la incidencia de las interacciones entre estudiantes y docentes femeninas de áreas CTIM (Ciencia, Tecnología, Ingeniería y Matemáticas, STEM por sus siglas en inglés) en las expectativas de elección de carrera universitaria en Colombia. Se utiliza una aproximación de modelos de rol para explicar como factores motivacionales afectan la elección de carreras CTIM de las mujeres que están cursando secundaria. Se emplean los datos PISA de 2015 a nivel nacional para estimar la probabilidad de elegir una carrera CTIM a través de un modelo Logit multinivel, controlando por covariadas como autoeficacia, sesgo docente, efectos fijos de colegio y educación de los padres. Los resultados muestran que contar con una docente femenina de áreas CTIM en el colegio no tiene un efecto estadísticamente significativo sobre la expectativa de elección de una carrera CTIM de las mujeres. En contraste, la autoeficacia de las estudiantes tiene efectos positivos sobre la expectativa de elección de carrera en estas mujeres. Adicional, una mujer que cursa el bachillerato en un colegio privado con programa vocacional tiene menor probabilidad de elegir una carrera CTIM que su contraparte en un colegio público con programa vocacional.spa
dc.description.degreelevelMaestríaspa
dc.format.extent49spa
dc.format.mimetypeapplication/pdfspa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/77774
dc.language.isospaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.departmentEscuela de Economíaspa
dc.publisher.programBogotá - Ciencias Económicas - Maestría en Ciencias Económicasspa
dc.relation.referencesAbadía, L. K., & Bernal, G. (2016). Brechas de género en el rendimiento escolar a lo largo de la distribución de puntajes: evidencia pruebas saber 11°. Vniversitas Económica.spa
dc.relation.referencesAbadía, L. K., & Bernal, G. (2017). A widening gap? a gender-based analysis of performance on the colombian high school exit examination. Revista de economía del Rosario, 5-31.spa
dc.relation.referencesAcevedo, S., Zuluaga, F., & Jaramillo, A. (2008). Determinantes de la demanda de educación superior en Colombia. Revista de economía del Rosario, 121-148.spa
dc.relation.referencesAmaya, J., M.A., D., & Sánchez, M. (2017). Metodología para impulsar el interés en las STEM en niñas de secundaria en el sur de Cali. En E. Serna, Investigación formativa en ingeniería (págs. 100-106). Medellín: Instituto Antioqueño de Investigación.spa
dc.relation.referencesAmerican Psychological Association. (2015). APA dictionary of psychology. Washington: American Psychological Association.spa
dc.relation.referencesAmundson, H. (2017). A Mother's influence: how a mother with an advanced degree impacts various STEM outcomes. University of Colorado.spa
dc.relation.referencesBachman, B., Hebl, M. L., & Rittmayer, a. (2009). Literature overview: girl's experience in the classroom.spa
dc.relation.referencesBahar, A., & Adiguzel, T. (2016). Analysis of Factors Influencing Interest in STEM Career: Comparison between American and Turkish High School Students with High Ability. Istanbul.spa
dc.relation.referencesBanco Mundial. (2012). Knowledge Economy Index (World Banck): Kapsarc. Obtenido de Kapsarc data portal: https://datasource.kapsarc.org/explore/dataset/knowledge-economy-index-world-bank-2012/export/?refine.indicator=Knowledge+Index&refine.measure=Weighted+by+Populationspa
dc.relation.referencesBeaman, L., Duflo, E., Pande, R., & Topalova, P. (2012). Female Leadership Raises Aspirations and Educational Attainment for Girls: A Policy Experiment in India. Science, 582-586.spa
dc.relation.referencesBeede, D., Julian, T., Langdon, D., McKittrick, G., Khan, B., & Doms, M. E. (2011). Women in STEM: A Gender Gap to Innovation. Economics and Statistics Administration , 4-11.spa
dc.relation.referencesBeezar, B. (1974). Role theory and teacher education. Journal of education, 56(1), 5-21.spa
dc.relation.referencesBenoöõt Rapoport, C. T. (2017). Why Do Boys and Girls Make Different Educational Choices? The Inßuence of Expected Earnings and Test Scores. Economics of Education Review.spa
dc.relation.referencesBlackwell, L. S., Tresnewski, K. H., & Dweck., C. S. (2007). Implicit Theories of Intelligence Predict Achievement Across an Adolescent. Child development, 246-263.spa
dc.relation.referencesBonilla, L., Bottan, N., & Ham, A. (2016). Information policies and higher education choices experimental evidence from Colombia. Bogotá: Banco de la República.spa
dc.relation.referencesCastillo, R., Grazzi, M., & Tacsir, E. (2014). Women in science and technology what does the literature say? Inter American Development Bank.spa
dc.relation.referencesCerinseka, G., Hribara, T., Glodez, N., & Dolinsek, S. (2013). Which are my Future Career Priorities and What Influenced my Choice of Studying Science, Technology, Engineering or Mathematics? Some Insights on Educational Choice—Case of Slovenia. International Journal of Science Education, 2999-3025.spa
dc.relation.referencesCheryan, S., Siy, J., Vichayapai, M., Drury, B., & Kim, S. (2011). Do Female and Male Role Models Who Embody STEM Stereotypes Hinder Women’s Anticipated Success in STEM? Social psycological and personality science, 656-664.spa
dc.relation.referencesCheryan, S., Tabak, J., & Meltzoff, A. (2011). What matters in recruiting? Effects ofprofessor gender and classroom environ- ment on women’s interest in STEM. Manuscript in preparation.spa
dc.relation.referencesCho, I. (2012). The effect of teacher–student gender matching: Evidence from OECD countries. Economics of Education Review, 54-67.spa
dc.relation.referencesCreamer, E. G., & Laughlin, A. (2005). Self-Authorship and Women's Career Decision Making. Journal of College Student Development, 13-27.spa
dc.relation.referencesDasgupta, N. (2011). Ingroup Experts and Peers as Social Vaccines Who Inoculate the Self-Concept: The Stereotype Inoculation Model. Psychological Inquiry, 231-246.spa
dc.relation.referencesDasgupta, N., & Stout, J. (2014). Girls and Women in Science, Technology, Engineering, and Mathematics: STEMing the Tide and Broadening Participation in STEM Careers. Policy Insights from the Behavioral and Brain Sciences, 21-29.spa
dc.relation.referencesde Cohen, C., & Deterding, N. (2009). Widening the net: national estimates of gender disparities in engineering. Journal of engineering education, 211-226.spa
dc.relation.referencesDee, T. (2007). Teachers and the gender gaps in student achievement. Journal of Human Resources, 525-554.spa
dc.relation.referencesDrury, B., Siy, J., & Cheryan, S. (2011). When do female role models benefit women? the importance of differentiating recruitment from retention in STEM. Psychological Inquiry, 265-269.spa
dc.relation.referencesDulce Salcedo, O., Maldonado, D., & Sánchez, F. (2019). ¿Influencian mujeres a otras mujeres? el caso de las docentes en áreas STEM en Bogotá. Documentos de trabajo Escuela de Gobierno Alberto Lleras Camargo.spa
dc.relation.referencesFairfield, H. M. (2013). Girls Lead in Science Exam, but Not in the United States - Interactive Graphic. New York Times. Recuperado el 25 de Octubre de 2017, de http://www.nytimes.com/interactive/2013/02/04/science/girls-lead-in-science-exam-but-not-in-the-united-states.html?emc=eta1spa
dc.relation.referencesFernandez, Schaaper, & Bello. (2016). What drives the gender gap in STEM? The SAGA Science, Technology and Innovation Gender Objectives List (STI GOL) as a new approach to linking indicators to STI policies. En 21st International Conference on Science and Technology Indicators-STI 2016. Book of Proceedings.spa
dc.relation.referencesFlanagan, D. P., & Dixon, S. G. (2014). The Cattell‐Horn‐Carroll Theory of Cognitive Abilities. Encyclopedia of Special Education.spa
dc.relation.referencesFouad, N., & Santana, M. (2017). SCCT and underrepresented populations in STEM fields: moving the needle. Journal of Career Assessment, 24-39.spa
dc.relation.referencesGibson, D. (2004). Role models in career development: New directions for theory and research. Journal of Vocational Behavior, 65(1), 134-156.spa
dc.relation.referencesGottfredson, L. (1997). Mainstream science on intelligence: an editorial with 52 signatories, history, and bibliography. Intelligence, 13-23.spa
dc.relation.referencesGreene, W. H. (2012). Dicrete choice. En W. H. Greene, Econometric analysis (págs. 681-759). New York: Pearson Education.spa
dc.relation.referencesHagit, M., Niva, W., Dov, D., & Yehudit Judy, D. (2016). Career Choice of Undergraduate Engineering Students. Procedia- Social and Behavioral Sciences, 222-228.spa
dc.relation.referencesHedeker, D. (2008). Multilevel models for ordinal and nominal variables. En J. De Leeuw, & E. Meijer, Handbook of multilevel analysis (págs. 237-275). New York: Springer.spa
dc.relation.referencesHenriksen, E., Dillon, J., & Ryder, J. (2015). Understanding student participation and choice in science and technology education. Springer.spa
dc.relation.referencesHerbert, J., & Stipek, D. (2005). The emergence of gender difference in children’s perceptions of their academic competence. Journal of Applied Developmental Psychology, 276-295.spa
dc.relation.referencesHernández Zapata, L. B. (2016). DETERMINANTES DE ELECCIÓN DE CARRERAS STEM DE LOS ESTUDIANTES DE EDUCACIÓN PÚBLICA DEL MUNICIPIO DE DOSQUEBRADAS. Pereira: EAFIT.spa
dc.relation.referencesHeyder, A., Steinmayr, R., & Kessels, U. (2019). Do teachers' beliefs about math aptitude and brillance explain gender differences in children's math ability self-concept? Front. Educ, 4. doi:10.3389/feduc.2019.00034spa
dc.relation.referencesIspas, D., & Borman, W. (2015). Personnel Selection, Psychology of. International Encyclopedia of Social and Behavioral Sciences.spa
dc.relation.referencesIspas, D., Iliescu, D., Ilie, A., & Johnson, R. (2010). Examining the criterion related validity of the general mental ability measure for adults: a two sample investigation. International Journal of Selection and Assessment, 224-227.spa
dc.relation.referencesJacobs, J., Ahmad, S., & Sax, L. (2016). Planning a career in engineering: parental effects on sons and daughters. Social sciences.spa
dc.relation.referencesJudge, G., Carter, R., Griffiths, W., Lütkepohl, H., & Lee, T.-C. (1988). Introduction to the theory and practice of econometrics. Wiley.spa
dc.relation.referencesKahn, S., & Ginther, D. (2017). Women and STEM. NBER Working Paper No. w23525.spa
dc.relation.referencesKell, H., Lubinski, D., Benbow, C., & Steiger, J. (2013). Creativity and technical innovation: Spatial ability’s unique role. Psychological Science, 1831-1836.spa
dc.relation.referencesLegewie, J., & DiPetre, T. (2014). The high school environment and the gender gap in science and engineering. Sociology of Education, 259-280.spa
dc.relation.referencesLent, R., Brown, S., & Hackett, G. (2002). Social cognitive career theory. En D. B. Associates, Career choice and development (Fourth ed., pág. 556). San Francisco: Wiley Company.spa
dc.relation.referencesLondoño, E. (2015). Interacciones de género estudiante-profesor, deserción y rendimiento académico en Colombia. Bogotá: Universidad del Rosario.spa
dc.relation.referencesMacKenzie, D., Nichols, J., Royle, A., Pollock, K., Bailey, L., & Hines, J. (2018). Fundamental principals of statistical inference. En D. MacKenzie, J. Nichols, A. Royle, K. Pollock, L. Bailey, & J. Hines, Ocuppancy estimation and modelling (págs. 71-111). Academic Press.spa
dc.relation.referencesMartin, V., Hurn, S., & Harris, D. (2012). Properties of maximum likelihood estimators. En V. Martin, S. Hurn, & D. Harris, Econometric modelling with time series specification, estimation and testing (págs. 33-86). Cambridge University Press.spa
dc.relation.referencesMartin, W., Moakler, J., & Mikyong, M. K. (2014). College Major Choice in STEM: Revisiting Confidence and Demographic Factors. The Career Development Quarterly, 128-143.spa
dc.relation.referencesMinisterio de Educación Nacional. (2014). Sistema Nacional de Indicadores Educativos Para Los Niveles de Preescolar, Básica y Media en Colombia. Bogotá: Ministerio de Educación Nacional.spa
dc.relation.referencesMinisterio de Educación Nacional. (Junio de 2019). Tasa de transito inmediato. Información nacional de educación superior 2010-2018 . Bogotá.spa
dc.relation.referencesMinisterio de Educación Nacional. (s.f.). Observatorio laboral para la educación: Graduados por núcleo básico de conocimiento. Obtenido de Observatorio laboral para la educación: http://bi.mineducacion.gov.co:8080/o3web/viewdesktop.jsp?cmnd=open&source=Perfil+Graduados%2FGraduados+por+N%FAcleo+B%E1sico+de+Conocimientospa
dc.relation.referencesMinisterio de Educación Nacional; ICFES. (2017). Informe Nacional de Resultados Colombia en PISA 2015. Bogotá D.C.: ICFES.spa
dc.relation.referencesMoakler, M. W., & Kim, M. M. (2014). College Major Choice in STEM: Revisiting Confidence and Demographic Factors. The Career Development Quarterly, 128-142.spa
dc.relation.referencesMorgenroth, T., & Ryan, M. (2015). The motivational theory of role modeling: how role models influence role aspirant's goals. Review of General Psychology, 465-483.spa
dc.relation.referencesNix, S., Perez-Felkner, L., & Kirby, T. (2015). Perceived mathematical ability under challenge: a longitudinal perspective on sex segregation among STEM degree fields. Frontiers in Psychology.spa
dc.relation.referencesNugent, G., Barker, B., Welch, G., Grandgenett, N., Wu, C., & Nelson, C. (2015). A Model of Factors Contributing to STEM Learning and Career Orientation. International Journal of Science Education , 1067-1088 .spa
dc.relation.referencesOECD. (2009). Replicate weights. En OECD, PISA Datan analysis manual:SAS. OECD.spa
dc.relation.referencesOECD. (2016). PISA 2015 Results excellence and equity in education .spa
dc.relation.referencesOECD. (2017). Education indicators in focus. OECD.spa
dc.relation.referencesOECD. (2017). Scaling procedures and construct validation of context questionnaire data.spa
dc.relation.referencesOECD; World Bank. (2012). Reviews of National Policies for Education: Tertiary Eduation in Colombia 2012. OECD Publishing.spa
dc.relation.referencesOnes, D., Dilchert, S., & Viswesvaran, C. (2012). Oxford Handbook of Personnel Assessment and Selection. New York: Oxford Universityspa
dc.relation.referencesPacheco, V. (2016). La ingenieria del futuro es un juego de niñas.spa
dc.relation.referencesParedes, V. (2014). A teacher like me or a student like me? role model versus teacher bias effect. Economics of education, 38-49.spa
dc.relation.referencesPark, G., Lubinski, D., & Benbow, C. (2007). Contrasting intellectual patterns predict creativity in the arts and sciences: Tracking intellectually precocious youth over 25 years. Psychological Science, 948-952.spa
dc.relation.referencesRomero, J. (2010). El éxito económico de los costeños en Bogotá: migración interna y capital humano. Documentos de trabajo sobre economía regional.spa
dc.relation.referencesRothwell, J. (2014). Still searching: job vacancies and STEM skills. Nueva York: Metropolitan policy program Brookings.spa
dc.relation.referencesSahin, A., Ekmekci, A., & Waxman, H. (2017). The relationships among high school STEM learning experiences, expectations, and mathematics and science efficacy and the likelihood of majoring in STEM in college. International Journal of Science Education, 1549-1572.spa
dc.relation.referencesSansone, D. (2017). Why Does Teacher Gender Matter? Economics of Education Review.spa
dc.relation.referencesSnijders, T., & Berkhof, J. (2008). Diagnostic checks for multilevel models. En J. Leeuw, E. Meijer, & H. Goldstein, Handbook of multilevel analysis (págs. 77-141). New York: Springer.spa
dc.relation.referencesSonnert, G. (2009). Parents Who Influence Their Children to Become Scientists: Effects of Gender and Parental Education. Social Studies of Science, 927-941.spa
dc.relation.referencesStout, J., Dasgupta, N., Hunsinger, M., & McManus, M. (2011). STEMing the tide: using ingroup experts to inoculate women's self-concept in science, technology, engineering, and mathematics (STEM). Journal of Personality and Social Psychology, 255-270.spa
dc.relation.referencesTacsir, E., Grazzi, M., & Castillo, R. (2014). Women in Science and Technology: What Does the Literature Say? Washington D.C.: BID.spa
dc.relation.referencesThomson, S., De Bortoli, L., & Underwood, C. (2017). PISA 2015: Reporting Australia's results. Australian Council for Educational Research.spa
dc.relation.referencesUNESCO. (2013). ISCED Fields of Education and Training 2013 (ISCED-F 2013). Paris: UNESCO.spa
dc.relation.referencesUNESCO Institute for Statistics. (2019). Researchers by field of R&D and sex (FTE and HC): UNESCO Institute for Statistics Sustainable Development Goals. Obtenido de UNESCO: Institute for Statistics Sustainable Development Goals: http://data.uis.unesco.org/index.aspx?queryid=118&export#spa
dc.relation.referencesValla, J., & Ceci, S. (2014). Breadth-based models of women’s underrepresentation in STEM fields: An integrative commentary on Schmidt (2011) and Nye et al. (2012). Perspectives on Psychological Science, 219-224.spa
dc.relation.referencesVázquez-Alonso, Á., & Manassero-Mas, M.-A. (2016). La voz de los estudiantes de primer año en seis países: evaluación de sus experiencias en estudios superiores científico-técnicos. Ciênc. Educ, 391-411.spa
dc.relation.referencesWang, M., & Degol, J. (2014). Motivational pathways to STEM career choices: using expectancy - value perspective to understand individual and gender differences in STEM fields. Developmental Review, 304-340.spa
dc.relation.referencesWang, M., & Degol, J. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): current knowledge, implications for practice, policy, and future directions. Educational psycology review, 119-140.spa
dc.relation.referencesWang, M., Eccles, J., & Kenny, S. (2013). Not lack of ability but more choice: individual and gender differences in STEM career choice . Psychological Science, 770-775.spa
dc.relation.referencesWang, M.-T., Ye, F., & Degol, J. L. (2016). Who Chooses STEM Careers? Using A Relative Cognitive Strength and Interest Model to Predict Careers in Science, Technology, Engineering, and Mathematics. Journal Youth Adolescence.spa
dc.relation.referencesZubieta, J. (2006). Women in Latin American Science and Technology: A Window Of Opportunity. En OECD, Women in Scientific Careers: Unleashing the Potential. Paris: OECD.spa
dc.rightsDerechos reservados - Universidad Nacional de Colombiaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial 4.0 Internacionalspa
dc.rights.spaAcceso abiertospa
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/spa
dc.subject.ddc370 - Educaciónspa
dc.subject.ddc370 - Educación::378 - Educación superior (Educación terciaria)spa
dc.subject.proposalModelos de rolspa
dc.subject.proposalrole modelseng
dc.subject.proposalElección de carreraspa
dc.subject.proposalcareer choiceeng
dc.subject.proposalCTIMspa
dc.subject.proposalSTEMeng
dc.subject.proposalSTEMspa
dc.subject.proposalgendereng
dc.subject.proposalSexospa
dc.titleElección de carrera: efecto de la interacción entre alumnas y maestras de las áreas Ciencia, Tecnología, Ingeniería Y Matemáticas (CTIM) en Colombia 2015spa
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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