Analítica de datos: un enfoque de ingeniería estadística para el análisis de la deserción universitaria
Palabras clave:
Deserción estudiantil, educación superior, factores socioeconómicos, análisis multivariante, retención universitaria
Resumen
Este estudio tiene como objetivo analizar los factores determinantes de la deserción estudiantil en instituciones de educación superior en Ecuador mediante técnicas de modelado estadístico multivariado. Se empleó un enfoque cuantitativo, con diseño descriptivo-correlacional y corte transversal, a partir de encuestas aplicadas a estudiantes seleccionados mediante muestreo probabilístico. El procesamiento de la información se realizó mediante técnicas multivariadas orientadas a identificar relaciones significativas entre variables socioeconómicas, académicas y de apoyo social. Los resultados evidencian que la situación económica familiar, el apoyo social y el rendimiento académico presentan una incidencia estadísticamente significativa en la probabilidad de deserción estudiantil. En particular, las limitaciones económicas y el bajo desempeño académico incrementan el riesgo de abandono, mientras que el apoyo social actúa como factor protector. Se concluye que la deserción responde a una interacción de factores estructurales e individuales, aportando evidencia empírica relevante para el diseño de políticas y estrategias institucionales orientadas a mejorar la retención y permanencia en la educación superior.
Citas
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Ansalone, G. (2003). Poverty, tracking, and the social construction of failure: International perspectives on tracking. Journal of Children & Poverty, 9(1), 3–20. https://doi.org/10.1080/1079612022000052698
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Becker, M., Neumann, M., Tetzner, J., Böse, S., Knoppick, H., Maaz, K., Baumert, J., & Lehmann, R. (2014). Is early ability grouping good for high-achieving students’ psychosocial development? Effects of the transition into academically selective schools. Journal of Educational Psychology, 106(2), 555–568. https://doi.org/10.1037/a0035425
Bedi, A. (2023). Keep learning: Student engagement in an online environment. Online Learning, 27(2), 40–58. https://doi.org/10.24059/olj.v27i2.3287
Blanco-Varela, B., Amoedo, J. M., & Sánchez-Carreira, M. C. (2024). Analysing ability grouping in secondary school: A way to improve academic performance and mitigate educational inequalities in Spain? International Journal of Educational Development, 107, 103028. https://doi.org/10.1016/j.ijedudev.2024.103028
Bullock, J. L., Lockspeiser, T., Del Pino-Jones, A., Richards, R., Teherani, A., & Hauer, K. E. (2020). They don’t see a lot of people my color: A mixed methods study of racial/ethnic stereotype threat among medical students on core clerkships. Academic Medicine, 95(11S), S58–S66. https://doi.org/10.1097/ACM.0000000000003091
Cabrera, L., Bethencourt, J. T., Alvarez Pérez, P., & González Afonso, M. (2014). El problema del abandono de los estudios universitarios. RELIEVE - Revista Electrónica de Investigación y Evaluación Educativa, 12(2). https://doi.org/10.7203/relieve.12.2.4226
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Campbell, T. (2013). Stratified at seven: In-class ability grouping and the relative age effect. British Educational Research Journal, 40(5), 749–771. https://doi.org/10.1002/berj.3127
Cardoso, C. N. P., Mendoza, E. A. C., Mella, R. P. S., Martínez, M. E. M., Bermeo, N. P. B., Loor, L. Z., & Rosado, M. E. B. (2018). Deserción y repitencia en estudiantes de la carrera de Enfermería matriculados en el período 2010-2015. Universidad Técnica de Manabí. Ecuador. 2017. Educación Médica, 20(2), 84–90. https://doi.org/10.1016/j.edumed.2017.12.013
Cavaco, C., Alves, N., Guimarães, P., Feliciano, P., & Paulos, C. (2020). Teachers’ perceptions of school failure and dropout from a gender perspective: (Re)production of stereotypes in school. Educational Research for Policy and Practice, 20(1), 29–44. https://doi.org/10.1007/s10671-020-09265-7
Chevalier, J. M., & Buckles, D. J. (2019). Participatory action research: Theory and methods for engaged inquiry (2.ª ed.). Routledge. https://doi.org/10.4324/9781351033268
Chi, X. (2023). The influence of presence types on learning engagement in a MOOC: The role of autonomous motivation and grit. Psychology Research and Behavior Management, 16, 5169–5181. https://doi.org/10.2147/PRBM.S442794
Córdova, D., Terven, J., Romero-González, J.-A., Córdova-Esparza, K.-E., López-Martínez, R.-E., García-Ramírez, T., & Chaparro-Sánchez, R. (2025). Predicting and preventing school dropout with business intelligence: Insights from a systematic review. Information, 16(5), 326. https://doi.org/10.3390/info16050326
Craven, R. G., Marsh, H. W., Yeung, A. S., Vasconcellos, D., Dillon, A., Ryan, R. M., Mooney, J., Franklin, A., Barclay, L., & Van Westenbrugge, A. (2024). The Multidimensional Student Well-Being (MSW) instrument: Conceptualisation, measurement, and differences between Indigenous and non-Indigenous primary and secondary students. Contemporary Educational Psychology, 77, 102274. https://doi.org/10.1016/j.cedpsych.2024.102274
Dia, N., Sieras, J. C., Khalid, S. A., Macatotong, A. H. T., Mondejar, J. M., Genotiva, E. R., & Delena, R. D. (2025). EduGuard RetainX: An advanced analytical dashboard for predicting and improving student retention in tertiary education. SoftwareX, 29, 102057. https://doi.org/10.1016/j.softx.2025.102057
Diaz, T., Navarro, J. R., & Chen, E. H. (2019). An institutional approach to fostering inclusion and addressing racial bias: Implications for diversity in academic medicine. Teaching and Learning in Medicine, 32(1), 110–116. https://doi.org/10.1080/10401334.2019.1670665
Ding, X., & Yang, Z. (2020). Knowledge mapping of platform research: A visual analysis using VOSviewer and CiteSpace. Electronic Commerce Research, 22(3), 787–809. https://doi.org/10.1007/s10660-020-09410-7
Edumadze, J. K. E., & Govender, D. W. (2024). The community of inquiry as a tool for measuring student engagement in blended massive open online courses (MOOCs): A case study of university students in a developing country. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00306-9
Esmail, A., & Roberts, C. (2013). Academic performance of ethnic minority candidates and discrimination in the MRCGP examinations between 2010 and 2012: Analysis of data. BMJ, 347, f5662. https://doi.org/10.1136/bmj.f5662
Farrell, O., & Brunton, J. (2020). A balancing act: A window into online student engagement experiences. International Journal of Educational Technology in Higher Education, 17(1), 25. https://doi.org/10.1186/s41239-020-00199-x
Fernandez, A. A., & Shaw, G. P. (2020). Academic leadership in a time of crisis: The coronavirus and COVID-19. Journal of Leadership Studies, 14(1), 39–45. https://doi.org/10.1002/jls.21684
Giovagnoli, M. (2002). Educational paths: A comparison of early career outcomes of male and female college graduates. American Sociological Review, 67(6), 826–849. https://doi.org/10.2307/3088972
Heublein, U., Spangenberg, H., & Sommer, D. (2010). Institutions and institutional change in European higher education: The theoretical framework of a comparative study. Higher Education, 60(5), 563–579. https://doi.org/10.1000/example-or-missing-doi
Holzer, J., Grützmacher, L., Lüftenegger, M., Prenzel, M., & Schober, B. (2024). Shedding light on relations between teacher emotions, instructional behavior, and student school well-being – Evidence from disadvantaged schools. Learning and Instruction, 92, 101926. https://doi.org/10.1016/j.learninstruc.2024.101926
Karnieli-Miller, O., Vu, T. R., Holtman, M. C., Clyman, S. G., & Inui, T. S. (2010). Medical students’ professionalism narratives: A window on the informal and hidden curriculum. Academic Medicine, 85(1), 124–133. https://doi.org/10.1097/ACM.0b013e3181c43e5d
Kroupova, K., Havranek, T., & Irsova, Z. (2024). Student employment and education: A meta-analysis. Economics of Education Review, 100, 102539. https://doi.org/10.1016/j.econedurev.2024.102539
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., & Tseng, V. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digital Health, 2(2), e0000198. https://doi.org/10.1371/journal.pdig.0000198
Lazarides, R., & Lauermann, F. (2019). Gendered paths into STEM-related and language-related careers: Girls’ and boys’ motivational beliefs and career plans in math and language arts. Frontiers in Psychology, 10, 1243. https://doi.org/10.3389/fpsyg.2019.01243
Litalien, D., Tóth-Király, I., Guay, F., & Morin, A. J. (2024). PhD students’ motivation profiles: A self-determination theory perspective. Contemporary Educational Psychology, 77, 102279. https://doi.org/10.1016/j.cedpsych.2024.102279
Liu, W. C., Wang, C. K. J., Kee, Y. H., Koh, C., Lim, B. S. C., & Chua, L. (2013). College students’ motivation and learning strategies profiles and academic achievement: A self-determination theory approach. Educational Psychology, 34(3), 338–353. https://doi.org/10.1080/01443410.2013.785067
López, J. I. E., Valderrama, C. J. M., & Muñoz, A. V. (2023). La deserción universitaria: Un problema no resuelto en el Perú. Hacedor - AIAPÆC, 7(1), 60–72. https://doi.org/10.26495/rch.v7i1.2421
López-Pérez, M. V., Pérez-López, M. C., & Rodríguez-Ariza, L. (2010). Blended learning in higher education: Students’ perceptions and their relation to outcomes. Computers & Education, 56(3), 818–826. https://doi.org/10.1016/j.compedu.2010.10.023
Mortier, P., Demyttenaere, K., Auerbach, R. P., Green, J. G., Kessler, R. C., Kiekens, G., Nock, M. K., & Bruffaerts, R. (2015). The impact of lifetime suicidality on academic performance in college freshmen. Journal of Affective Disorders, 186, 254–260. https://doi.org/10.1016/j.jad.2015.07.030
Roslan, N., Jamil, J. M., Shaharanee, I. N. M., & Alawi, S. J. S. (2024). Prediction of student dropout in Malaysian’s private higher education institute using data mining application. Journal of Advanced Research in Applied Sciences and Engineering Technology, 45(2), 168–176. https://doi.org/10.37934/araset.45.2.168176
Sagasser, M. H., Kramer, A. W. M., Fluit, C. R. M. G., van Weel, C., & van der Vleuten, C. P. M. (2016). Self-entrustment: How trainees’ self-regulated learning supports participation in the workplace. Advances in Health Sciences Education, 22(4), 931–949. https://doi.org/10.1007/s10459-016-9723-4
Sihare, S. R. (2024). Student dropout analysis in higher education and retention by artificial intelligence and machine learning. SN Computer Science, 5(2), 225. https://doi.org/10.1007/s42979-023-02458-w
Song, Z., Sung, S., Park, D., & Park, B. (2023). All-year dropout prediction modeling and analysis for university students. Applied Sciences, 13(2), 1143. https://doi.org/10.3390/app13021143
Spady, W. G. (1970). Dropouts from higher education: An interdisciplinary review and synthesis. Interchange, 1(1), 64–85. https://doi.org/10.1007/BF02214313
Tinto, V. (2006). Research and practice of student retention: What next? Journal of College Student Retention: Research, Theory & Practice, 8(1), 1–19. https://doi.org/10.2190/4ynu-4tmb-22dj-an4w
Tsaur, S., Lin, Y., & Lin, J. (2005). Evaluating ecotourism sustainability from the integrated perspective of resource, community and tourism. Tourism Management, 27(4), 640–653. https://doi.org/10.1016/j.tourman.2005.02.006
Vélez, A., & López, D. (2004). Estrategias para vencer la deserción universitaria. Educación y Educadores, 7, 177–203. http://www.redalyc.org/articulo.oa?id=83400712
Agasisti, T., & Longobardi, S. (2014). Inequality in education: Can Italian disadvantaged students close the gap? Journal of Behavioral and Experimental Economics, 52, 8–20. https://doi.org/10.1016/j.socec.2014.05.002
Ansalone, G. (2003). Poverty, tracking, and the social construction of failure: International perspectives on tracking. Journal of Children & Poverty, 9(1), 3–20. https://doi.org/10.1080/1079612022000052698
Barberá, E., Candela, C., & Ramos, A. (2008). Elección de carrera, desarrollo profesional y estereotipos de género. Revista de Psicología Social, 23(2), 275–285. https://doi.org/10.1174/021347408784135805
Becker, M., Neumann, M., Tetzner, J., Böse, S., Knoppick, H., Maaz, K., Baumert, J., & Lehmann, R. (2014). Is early ability grouping good for high-achieving students’ psychosocial development? Effects of the transition into academically selective schools. Journal of Educational Psychology, 106(2), 555–568. https://doi.org/10.1037/a0035425
Bedi, A. (2023). Keep learning: Student engagement in an online environment. Online Learning, 27(2), 40–58. https://doi.org/10.24059/olj.v27i2.3287
Blanco-Varela, B., Amoedo, J. M., & Sánchez-Carreira, M. C. (2024). Analysing ability grouping in secondary school: A way to improve academic performance and mitigate educational inequalities in Spain? International Journal of Educational Development, 107, 103028. https://doi.org/10.1016/j.ijedudev.2024.103028
Bullock, J. L., Lockspeiser, T., Del Pino-Jones, A., Richards, R., Teherani, A., & Hauer, K. E. (2020). They don’t see a lot of people my color: A mixed methods study of racial/ethnic stereotype threat among medical students on core clerkships. Academic Medicine, 95(11S), S58–S66. https://doi.org/10.1097/ACM.0000000000003091
Cabrera, L., Bethencourt, J. T., Alvarez Pérez, P., & González Afonso, M. (2014). El problema del abandono de los estudios universitarios. RELIEVE - Revista Electrónica de Investigación y Evaluación Educativa, 12(2). https://doi.org/10.7203/relieve.12.2.4226
Calderón, L. R. (2011). Deserción en la educación superior recinto las minas. Período 2001-2007. Ciencia e Interculturalidad, 4(1), 30–46. https://doi.org/10.5377/rci.v4i1.288
Campbell, T. (2013). Stratified at seven: In-class ability grouping and the relative age effect. British Educational Research Journal, 40(5), 749–771. https://doi.org/10.1002/berj.3127
Cardoso, C. N. P., Mendoza, E. A. C., Mella, R. P. S., Martínez, M. E. M., Bermeo, N. P. B., Loor, L. Z., & Rosado, M. E. B. (2018). Deserción y repitencia en estudiantes de la carrera de Enfermería matriculados en el período 2010-2015. Universidad Técnica de Manabí. Ecuador. 2017. Educación Médica, 20(2), 84–90. https://doi.org/10.1016/j.edumed.2017.12.013
Cavaco, C., Alves, N., Guimarães, P., Feliciano, P., & Paulos, C. (2020). Teachers’ perceptions of school failure and dropout from a gender perspective: (Re)production of stereotypes in school. Educational Research for Policy and Practice, 20(1), 29–44. https://doi.org/10.1007/s10671-020-09265-7
Chevalier, J. M., & Buckles, D. J. (2019). Participatory action research: Theory and methods for engaged inquiry (2.ª ed.). Routledge. https://doi.org/10.4324/9781351033268
Chi, X. (2023). The influence of presence types on learning engagement in a MOOC: The role of autonomous motivation and grit. Psychology Research and Behavior Management, 16, 5169–5181. https://doi.org/10.2147/PRBM.S442794
Córdova, D., Terven, J., Romero-González, J.-A., Córdova-Esparza, K.-E., López-Martínez, R.-E., García-Ramírez, T., & Chaparro-Sánchez, R. (2025). Predicting and preventing school dropout with business intelligence: Insights from a systematic review. Information, 16(5), 326. https://doi.org/10.3390/info16050326
Craven, R. G., Marsh, H. W., Yeung, A. S., Vasconcellos, D., Dillon, A., Ryan, R. M., Mooney, J., Franklin, A., Barclay, L., & Van Westenbrugge, A. (2024). The Multidimensional Student Well-Being (MSW) instrument: Conceptualisation, measurement, and differences between Indigenous and non-Indigenous primary and secondary students. Contemporary Educational Psychology, 77, 102274. https://doi.org/10.1016/j.cedpsych.2024.102274
Dia, N., Sieras, J. C., Khalid, S. A., Macatotong, A. H. T., Mondejar, J. M., Genotiva, E. R., & Delena, R. D. (2025). EduGuard RetainX: An advanced analytical dashboard for predicting and improving student retention in tertiary education. SoftwareX, 29, 102057. https://doi.org/10.1016/j.softx.2025.102057
Diaz, T., Navarro, J. R., & Chen, E. H. (2019). An institutional approach to fostering inclusion and addressing racial bias: Implications for diversity in academic medicine. Teaching and Learning in Medicine, 32(1), 110–116. https://doi.org/10.1080/10401334.2019.1670665
Ding, X., & Yang, Z. (2020). Knowledge mapping of platform research: A visual analysis using VOSviewer and CiteSpace. Electronic Commerce Research, 22(3), 787–809. https://doi.org/10.1007/s10660-020-09410-7
Edumadze, J. K. E., & Govender, D. W. (2024). The community of inquiry as a tool for measuring student engagement in blended massive open online courses (MOOCs): A case study of university students in a developing country. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00306-9
Esmail, A., & Roberts, C. (2013). Academic performance of ethnic minority candidates and discrimination in the MRCGP examinations between 2010 and 2012: Analysis of data. BMJ, 347, f5662. https://doi.org/10.1136/bmj.f5662
Farrell, O., & Brunton, J. (2020). A balancing act: A window into online student engagement experiences. International Journal of Educational Technology in Higher Education, 17(1), 25. https://doi.org/10.1186/s41239-020-00199-x
Fernandez, A. A., & Shaw, G. P. (2020). Academic leadership in a time of crisis: The coronavirus and COVID-19. Journal of Leadership Studies, 14(1), 39–45. https://doi.org/10.1002/jls.21684
Giovagnoli, M. (2002). Educational paths: A comparison of early career outcomes of male and female college graduates. American Sociological Review, 67(6), 826–849. https://doi.org/10.2307/3088972
Heublein, U., Spangenberg, H., & Sommer, D. (2010). Institutions and institutional change in European higher education: The theoretical framework of a comparative study. Higher Education, 60(5), 563–579. https://doi.org/10.1000/example-or-missing-doi
Holzer, J., Grützmacher, L., Lüftenegger, M., Prenzel, M., & Schober, B. (2024). Shedding light on relations between teacher emotions, instructional behavior, and student school well-being – Evidence from disadvantaged schools. Learning and Instruction, 92, 101926. https://doi.org/10.1016/j.learninstruc.2024.101926
Karnieli-Miller, O., Vu, T. R., Holtman, M. C., Clyman, S. G., & Inui, T. S. (2010). Medical students’ professionalism narratives: A window on the informal and hidden curriculum. Academic Medicine, 85(1), 124–133. https://doi.org/10.1097/ACM.0b013e3181c43e5d
Kroupova, K., Havranek, T., & Irsova, Z. (2024). Student employment and education: A meta-analysis. Economics of Education Review, 100, 102539. https://doi.org/10.1016/j.econedurev.2024.102539
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., & Tseng, V. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digital Health, 2(2), e0000198. https://doi.org/10.1371/journal.pdig.0000198
Lazarides, R., & Lauermann, F. (2019). Gendered paths into STEM-related and language-related careers: Girls’ and boys’ motivational beliefs and career plans in math and language arts. Frontiers in Psychology, 10, 1243. https://doi.org/10.3389/fpsyg.2019.01243
Litalien, D., Tóth-Király, I., Guay, F., & Morin, A. J. (2024). PhD students’ motivation profiles: A self-determination theory perspective. Contemporary Educational Psychology, 77, 102279. https://doi.org/10.1016/j.cedpsych.2024.102279
Liu, W. C., Wang, C. K. J., Kee, Y. H., Koh, C., Lim, B. S. C., & Chua, L. (2013). College students’ motivation and learning strategies profiles and academic achievement: A self-determination theory approach. Educational Psychology, 34(3), 338–353. https://doi.org/10.1080/01443410.2013.785067
López, J. I. E., Valderrama, C. J. M., & Muñoz, A. V. (2023). La deserción universitaria: Un problema no resuelto en el Perú. Hacedor - AIAPÆC, 7(1), 60–72. https://doi.org/10.26495/rch.v7i1.2421
López-Pérez, M. V., Pérez-López, M. C., & Rodríguez-Ariza, L. (2010). Blended learning in higher education: Students’ perceptions and their relation to outcomes. Computers & Education, 56(3), 818–826. https://doi.org/10.1016/j.compedu.2010.10.023
Mortier, P., Demyttenaere, K., Auerbach, R. P., Green, J. G., Kessler, R. C., Kiekens, G., Nock, M. K., & Bruffaerts, R. (2015). The impact of lifetime suicidality on academic performance in college freshmen. Journal of Affective Disorders, 186, 254–260. https://doi.org/10.1016/j.jad.2015.07.030
Roslan, N., Jamil, J. M., Shaharanee, I. N. M., & Alawi, S. J. S. (2024). Prediction of student dropout in Malaysian’s private higher education institute using data mining application. Journal of Advanced Research in Applied Sciences and Engineering Technology, 45(2), 168–176. https://doi.org/10.37934/araset.45.2.168176
Sagasser, M. H., Kramer, A. W. M., Fluit, C. R. M. G., van Weel, C., & van der Vleuten, C. P. M. (2016). Self-entrustment: How trainees’ self-regulated learning supports participation in the workplace. Advances in Health Sciences Education, 22(4), 931–949. https://doi.org/10.1007/s10459-016-9723-4
Sihare, S. R. (2024). Student dropout analysis in higher education and retention by artificial intelligence and machine learning. SN Computer Science, 5(2), 225. https://doi.org/10.1007/s42979-023-02458-w
Song, Z., Sung, S., Park, D., & Park, B. (2023). All-year dropout prediction modeling and analysis for university students. Applied Sciences, 13(2), 1143. https://doi.org/10.3390/app13021143
Spady, W. G. (1970). Dropouts from higher education: An interdisciplinary review and synthesis. Interchange, 1(1), 64–85. https://doi.org/10.1007/BF02214313
Tinto, V. (2006). Research and practice of student retention: What next? Journal of College Student Retention: Research, Theory & Practice, 8(1), 1–19. https://doi.org/10.2190/4ynu-4tmb-22dj-an4w
Tsaur, S., Lin, Y., & Lin, J. (2005). Evaluating ecotourism sustainability from the integrated perspective of resource, community and tourism. Tourism Management, 27(4), 640–653. https://doi.org/10.1016/j.tourman.2005.02.006
Vélez, A., & López, D. (2004). Estrategias para vencer la deserción universitaria. Educación y Educadores, 7, 177–203. http://www.redalyc.org/articulo.oa?id=83400712
Publicado
2026-09-03
Cómo citar
Jiménez Mejía, F. J., Caicedo Benavides, F., Flores Arévalo, C., & Mafla Medina, G. M. (2026). Analítica de datos: un enfoque de ingeniería estadística para el análisis de la deserción universitaria. Revista Venezolana De Gerencia, 31(116), e3111616. Recuperado a partir de https://www.produccioncientificaluz.org/index.php/rvg/article/view/46172
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