Effectiveness of a peer mentoring on university dropout and academic performance
-
1
Universidad Complutense de Madrid
info
-
2
Universidad Nacional de Educación a Distancia
info
ISSN: 1135-755X
Año de publicación: 2024
Volumen: 30
Número: 1
Páginas: 29-37
Tipo: Artículo
Otras publicaciones en: Psicología educativa
Resumen
Se ha propuesto la aplicación de programas de mentoría para reducir la deserción universitaria y aumentar el rendimiento académico. En el artículo analizamos el efecto de la mentoría entre pares sobre el abandono universitario y el rendimiento académico en España. Aplicamos un diseño de grupo de control cuasiexperimental con medida post en una muestra de 3.774 estudiantes (mentorados, n = 1,887; control, n = 1,887). Los mentorados habían participado en un programa de mentoría entre pares. Aplicamos la prueba t de Student, la d de Cohen, el estadístico phi y el chi-cuadrado. Los mentorados presentaban un menor abandono que los controles y un mayor rendimiento académico independientemente del área de conocimiento. Los resultados avalan la implementación de programas de mentoría en las universidades españolas con el objetivo de reducir el abandono universitario y aumentar el rendimiento académico. La investigación proporciona evidencia empírica para la elaboración de teorías en estudios de educación superior, relaciones de desarrollo y programas de integración.
Referencias bibliográficas
- Alban, M., & Mauricio, D. (2019). Predicting university dropout through data mining: A systematic literature. Indian Journal of Science and Technology, 12(4), 1-12. https://doi.org/10.17485/ijst/2019/v12i4/139729
- Aljohani, O. (2016). A comprehensive review of the major studies and theoretical models of student retention in higher education. Higher Education Studies, 6(2), 1-18. https://doi.org/10.5539/hes.v6n2p1
- Alonso-García, M. A. (2021). Proposal of a peer mentoring model in university environments. Revista Electrónica Educare, 25(1), 356-372. https://doi. org/10.15359/ree.25-1.19
- Alonso-García, M. A., Calles, A., & Sánchez-Ávila, C. (2012). Diseño y desarrollo de programas de mentoring en organizaciones. Síntesis.
- Alonso García, M. A., González Ortiz de Zárate, A., Gómez Flechoso, M. A. & Berrocal Berrocal, F. (2023). Influence of the mentor competence on the mentee satisfaction: Mediation and moderation. In J. A. Jaworski (Ed.), Advances in sociology research (pp. 167-186). Nova.
- Avello-Martínez, R. (2022, June 29). ¿Por qué reportar el tamaño del efecto? Comunicar, 137, 1-10. https://doi.org/10.3916/escuela-de-autores-137
- Bardach, L., Lüftenegger, M., Oczlon, S., Spiel, C., & Schober, B. (2020). Contextrelated problems and university students’ dropout intentions—the buffering effect of personal best goals. European Journal of Psychology of Education, 35(2), 477-493. https://doi.org/10.1007/s10212-019- 00433-9
- Behr, A., Giese, M., & Theune, K. (2020). Early prediction of university dropouts–a random forest approach. Jahrbücher für Nationalökonomie und Statistik, 240(6), 743-789. https://doi.org/10.1515/jbnst-2019-0006
- Bernardo, A., Esteban, M., Fernández, E., Cervero, A., Tuero, E., & Solano, P. (2016). Comparison of personal, social and academic variables related to university drop-out and persistence. Frontiers in Psychology, 7, Article 1610. https://doi.org/10.3389/fpsyg.2016.01610
- Cannistrà, M., Masci, C., Ieva, F., Agasisti, T., & Paganoni, A. M. (2021). Early predicting dropout of university students: An application of innovative multilevel machine learning and statistical techniques. Studies in Higher Education, 47(9), 1935-1956. https://doi.org/10.1080/03075079 .2021.2018415
- Cárdenas, J. M., & Arancibia, H. (2014). Potencia estadística y cálculo del tamaño del efecto en G* Power: complementos a las pruebas de significación estadística y su aplicación en psicología. Salud & Sociedad, 5(2), 210-224. https://doi.org/10.22199/S07187475.2014.0002.00006
- Casanova, J. R., Cervero Fernández-Castañón, A., Núñez Pérez, J. C., Almeida, L. S., & Bernardo Gutiérrez, A. B. (2018). Factors that determine the persistence and dropout of university students. Psicothema, 3(4), 408- 414. https://doi.org/10.7334/psicothema2018.155
- Collins, A., Lewis, I., Stracke, E., & Vanderheide, R. (2014). Talking career across disciplines: Peer group mentoring for women academics. International Journal of Evidence Based Coaching and Mentoring, 12(1), 92-108. https://search.informit.org/doi/10.3316/informit.781886556076792
- Conde, Á., Deaño, M., Pinto, A. A., Iglesias-Sarmiento, V., Alfonso, S., GarcíaSeñorán, M., Limia, S., & Tellado, F. (2017). Expectativas académicas y planificación. Claves para la interpretación del fracaso y el abandono académico. International Journal of Developmental and Educational Psychology, 1(1), 167-176. https://doi.org/10.17060/ijodaep.2017. n1.v1.909
- Constate-Amores, A., Martínez, E. F., Asencio, E. N., & Fernández-Mellizo, M. (2021). Factores asociados al abandono universitario. Educación XX1, 24(1), 17-44. https://doi.org/10.5944/educXX1.26889
- Corredor-García, M., & Bailey-Moreno, J. (2020). Motivación y concepciones que alumnos de educación básica atribuyen a su rendimiento académico en matemáticas. Revista Fuentes, 22(1), 127-141. https://doi. org/10.12795/revistafuentes.2020.v22.i1.10
- Crisp, G., & Cruz, I. (2009). Mentoring college students: A critical review of the literature between 1990 and 2007. Research in Higher Education, 50(6), 525-545. https://doi.org/10.1007/s11162-009-9130-2
- Demetriou, C., & Schmitz-Seiborski, A. (2011). Integration, motivation, strengths and optimism: Retention theories past, present and future. In R. Hayes (Ed.), Proceedings of the 7th National Symposium on Student Retention (pp. 300-312). The University of Oklahoma.
- Egege, S., & Kutieleh, S. (2015). Peer mentors as a transition strategy at university: Why mentoring needs to have boundaries. Australian Journal of Education, 59(3), 265-277. https://doi. org/10.1177/0004944115604697
- European Commission. (2022, June 10). European Credit Transfer and Accumulation System (ECTS). European Commission. https:// education.ec.europa.eu/education-levels/higher-education/highereducation-initiatives/inclusive-and-connected-higher-education/ european-credit-transfer-and-accumulation-system
- European Education Area. (2022, June 27). Strategic framework. European Commission. https://education.ec.europa.eu/about-eea/strategicframework
- European Union. (2022). Spain. European Union. https://european-union. europa.eu/principles-countries-history/country-profiles/spain_es
- Fernández-García, A. J., Preciado, J. C., Melchor, F., Rodriguez-Echeverria, R., Conejero, J. M., & Sánchez-Figueroa, F. (2021). A real-life machine learning experience for predicting university dropout at different stages using academic data. IEEE Access, 9, 133076-133090. https:// doi.org/10.1109/ACCESS.2021.3115851
- Fernández-Mellizo, M. (2022). Análisis del abandono de los estudiantes de grado en las universidades presenciales en España. Programa Editorial del Ministerio de Universidades. https://www.universidades.gob.es/ stfls/universidades/ministerio/ficheros/14_Informe_abandono_para_ maquetar.pdf
- Flores, V., Heras, S., & Julian, V. (2022). Comparison of predictive models with balanced classes using the SMOTE method for the forecast of student dropout in higher education. Electronics, 11(3), 1-16. https:// doi.org/10.3390/electronics11030457
- Fouarge, D., & Heß, P. (2023). Preference-choice mismatch and university dropout. Labour Economics, 83, Article 102405. https://doi. org/10.1016/j.labeco.2023.102405
- Frey, B. (2018). The SAGE encyclopedia of educational research, measurement, and evaluation (vols. 1-4). SAGE Publications, Inc. https://doi.org/10.4135/9781506326139
- Gairín, J., Triado, X. M., Feixas, M., Figuera, P., Aparicio-Chueca, P., & Torrado, M. (2014). Student dropout rates in Catalan universities: Profile and motives for disengagement. Quality in Higher Education, 20(2), 165- 182. https://doi.org/10.1080/13538322.2014.925230
- Gershenfeld, S. (2014). A review of undergraduate mentoring programs. Review of Educational Research, 84(3), 365-391. https://doi. org/10.3102/0034654313520512
- González-Benito, A., López-Martín, E., Expósito-Casas, E., & MorenoGonzález, E. (2021). Motivación académica y autoeficacia percibida y su relación con el rendimiento académico en los estudiantes universitarios de la enseñanza a distancia. RELIEVE Revista Electrónica de Investigación y Evaluación Educativa 27(2), 1-15. https://doi.org/10.30827/relieve.v27i2.21909
- González-Ramírez, T., & Pedraza-Navarro, I. (2017). Variables sociofamiliares asociadas al abandono de los estudios universitarios. Educatio Siglo XXI, 35(2), 365-388. https://doi.org/10.6018/j/298651
- Jacobi, M. (1991). Mentoring and undergraduate academic success: A literature review. Review of Educational Research, 61(4), 505-532. https://doi.org/3102/00346543061004505
- Jiménez-Caballero, J. L., Camuñez, J. A., González-Rodríguez, M. R., & Fuentes, P. (2014). Factores determinantes del rendimiento académico universitario en el Espacio Europeo de Educación Superior. Innovar, 25(58), 159-176. https://doi.org/10.15446/innovar.v25n58.52440
- Khoo, S., Zhao, J., Walker, A., Kirkman, J., & Spehar, B. (2019). Transitions and choices: Graduate student mentoring for psychology honours students. Student Success 10, 147-154. https://doi.org/10.5204/ssj. v10i1.648
- La Moncloa. (2022). La inversión pública en educación alcanza su máximo histórico con 55.265,8 millones en 2020. La Moncloa. https://cutt. ly/9KFN8cn
- Leidenfrost, B., Strassnig, B., Schtz, M., Carbon, C. C., & Schabmann, A. (2014). The impact of peer mentoring on mentee academic performance: Is any mentoring style better than no mentoring at all? International Journal of Teaching and Learning in Higher Education, 26(1), 102-111. https://files.eric.ed.gov/fulltext/EJ1043041.pdf
- León, B. (2008). Atención plena y rendimiento académico en estudiantes de enseñanza secundaria. European Journal of Education and Psychology, 1(3), 17-26. https://doi.org/10.30552/ejep.v1i3.11
- Maluenda-Albornoz, J., Infante-Villagrán, V., Galve-González, C., FloresOyarzo, G., & Berríos-Riquelme, J. (2022). Early and dynamic socioacademic variables related to dropout intention: A predictive model made during the pandemic. Sustainability, 14(2), Article 831. https:// doi.org/10.3390/su14020831
- McMurtry, A. (2020). Relief for the exhausted post-positivist: New epistemological choices transcend positivism, relativism, and even post-positivism. Canadian Medical Education Journal, 11(6), Article e197. https://doi.org/10.36834/cmej.71217
- Mestan, K. (2016). Why students drop out of the bachelor of arts. Higher Education Research & Development, 35(5), 983-996. https://doi.org/10 .1080/07294360.2016.1139548
- Mortagy, Y., Boghikian-Whitby, S., & Helou, I. (2018). An analytical investigation of the characteristics of the dropout students in higher education. Issues in Informing Science and Information Technology, 15, 249-278. https://doi.org/10.28945/3999
- Olaya, P. C., Giraldo, A. J. L., & Carpintero, Á. A. T. (2016, November). ¿Cuánto cuesta la deserción estudiantil? Sistema de cálculo de costos monetarios del abandono estudiantil (Sissemae). Congresos CLABES VI. Quito, Ecuador. https://core.ac.uk/download/pdf/234020946.pdf
- Opazo, D., Moreno, S., Álvarez-Miranda, E., & Pereira, J. (2021). Analysis of first-year university student dropout through machine learning models: A comparison between universities. Mathematics, 9(20), Article 2599. https://doi.org/10.3390/math9202599
- Ortiz-Lozano, J. M., Rua-Vieites, A., Bilbao-Calabuig, P., & Casadesús-Fa, M. (2018). University student retention: Best time and data to identify undergraduate students at risk of dropout. Innovations in Education and Teaching International, 57(1), 74-85. https://doi.org/10.1080/147 03297.2018.1502090
- Oxford. (2020, August 05). Academic achievement. Oxford Bibliographies. https://doi.org/ 10.1093/OBO/9780199756810-0108
- Palacios, C. A., Reyes-Suárez, J. A., Bearzotti, L. A., Leiva, V., & Marchant, C. (2021). Knowledge discovery for higher education student retention based on data mining: Machine learning algorithms and case study in Chile. Entropy, 23(4), Article 485. https://doi.org/10.3390/e23040485
- Prieto, J. M. (2020). Una revisión sistemática sobre gamificación, motivación y aprendizaje en universitarios. Teoría De La Educación; Revista Interuniversitaria, 32(1), 73-99. https://doi.org/10.14201/teri.20625
- Saleem, S., & Ayedh, A. (2013). Student drop-out trends at Sultan Qaboos University and Kuwait University: 2000-2011. College Student Journal, 47(3), 499-506.
- Sánchez-Santamaría, J., Boroel-Cervantes, B.I., López-Garrido, F. M., & Hortigüela-Alcalá, D. (2021). Motivation and evaluation in education from the sustainability perspective: A review of the scientific literature. Sustainability, 13(7), 1-19. https://doi.org/10.3390/su13074047
- Sandoval-Palis, I., Naranjo, D., Vidal, J., & Gilar-Corbi, R. (2020). Early dropout prediction model: A case study of university levelling course students. Sustainability, 12(22), Article 9314. https://doi.org/10.3390/ su12229314
- Schnettler, T., Bobe, J., Scheunemann, A., Fries, S., & Grunschel, C. (2020). Is it still worth it? Applying expectancy-value theory to investigate the intraindividual motivational process of forming intentions to drop out from university. Motivation and Emotion, 44(4), 491-507. https://doi. org/10.1007/s11031-020-09822-w
- Shauran, B., Jain, R., & Jain, N. (2021). Impact of mentoring on academic success of students in similar and cross-gender mentoring relationships. International Journal of Indian Culture and Business Management, 24(1), 63-80. https://doi.org/10.1504/IJICBM.2021.117924
- Siri, A. (2015). Predicting students’ dropout at university using artificial neural networks. Italian Journal of Sociology of Education, 7(2), 225-247. http://ijse.padovauniversitypress.it/system/files/papers/2015_2_9.pdf
- Sneyers, E., & De Witte, K. (2018). Interventions in higher education and their effect on student success: A meta-analysis. Educational Review, 70(2), 208-228. https://doi.org/10.1080/00131911.2017.1300874
- Solís, M., Moreira, T., Gonzalez, R., Fernandez, T., & Hernandez, M. (2018, July). Perspectives to predict dropout in university students with machine learning. 2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI), 1-6. https://doi.org/10.1109/ IWOBI.2018.8464191
- Stewart, M. (2012). The Spanish language today. Routledge. Suhlmann, M., Sassenberg, K., Nagengast, B., & Trautwein, U. (2018). Belonging mediates the effects of student university fit on well-being, motivation, and drop-out intention. Social Psychology, 49(1), 16-28. https://doi.org/10.1027/1864-9335/a000325
- Universidad Complutense de Madrid (UCM, 2022). Distribución del estudiantado de la UCM según género. Universidad Complutense de Madrid. https://www.ucm.es/unidaddeigualdad/distribucion-deestudiantes-de-la-ucm-segun-generoUNESCO Institute of Statistics. (2021). Government expenditure on education, total (% of GDP). The World Bank. https://data.worldbank. org/indicator/SE.XPD.TOTL.GD.ZS
- Venegas-Muggli, J. I., Cifuentes-Donald, C., Rozas-Retamal, M., & González-Clares, M. J. (2021). Determining factors of labour market outcomes for recently graduated, underrepresented college students. Australian Journal of Career Development, 30(2), 150-162. https://doi. org/10.1177/1038416221101201
- Woo, H. R. (2017). Exploratory study examining the joint impacts of mentoring and managerial coaching on organizational commitment. Sustainability, 9(2), Article 181. https://doi.org/10.3390/su9020181