Modalidades de aprendizaje y rendimiento académico en asignaturas fundamentales de ingeniería en el escenario Covid-19
Resumen
En el contexto de la pandemia por COVID-19, las instituciones de educación superior con modalidad presencial en Ecuador implementan abruptamente la modalidad virtual, por lo que resulta interesante analizar el rendimiento académico de estudiantes de ingeniería en tres tratamientos clave que combinan la modalidad de estudios y el periodo: antes (presencial), durante (virtual) y después de la pandemia (presencial). Para ello se aplica un diseño cuantitativo, transversal y explicativo con estudiantes matriculados entre 2019 y 2024 en Cálculo Diferencial e Integral, Estadística, Física I y Química I. La prueba no paramétrica de Kruskal -Wallis (α = 0.05) en cada asignatura determina diferencias significativas (p < 0.001) con respecto a los tres tratamientos. Las pruebas post hoc Dunn confirman diferencias en las comparaciones de pares de medias, excepto en Estadística entre los periodos antes y después de la pandemia (p = 0.108). En comparaciones unilaterales (Wilcoxon), la modalidad virtual presenta calificaciones promedio más altas que la modalidad presencial. Al retornar a la presencialidad, se incrementan las tasas de reprobación, alcanzando un 55% en Cálculo y un 16% en Estadística. Se evidencia el impacto de la transición de modalidad sobre el rendimiento académico en asignaturas fundamentales para estudiantes de ingeniería.
Descargas
Citas
Aguilera-Hermida, P. (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1. https://doi.org/10.1016/j.ijedro.2020.100011
Alarcon, R., Aquino, J., Bravo, J., & Valdivia, C. (2021). Correlational analysis of incident factors in the academic performance of university higher education students under the context of COVID-19. Proceedings of the 2021 IEEE 1st International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2021. https://doi.org/10.1109/ICALTER54105.2021.9675086
Betthäuser, B. A., Bach-Mortensen, A., & Engzell, P. (2023). A systematic review and meta-analysis of the evidence on learning during the COVID-19 pandemic. Nature Human Behaviour, 7. https://doi.org/10.1038/s41562-022-01506-4
Biemer, P., & Lyberg, L. (2003). Introduction to survey quality (Wiley, Ed.). John Wiley & Sons.
Cardeña, C. (2021). Levene’s Test for Verifying Homoscedasticity Between Groups in Quasi-Experiments in Social Sciences. South Eastern European Journal of Public Health. https://doi.org/10.11576/seejph-4791
Casiano, D., Cueva, E., Zumaeta Barrientos, M. R., & Casiano Inga, C. (2022). Impacto de la covid-19 en el desempeño académico universitario. Un análisis comparativo para la Universidad Nacional Toribio Rodríguez de Mendoza, en Amazonas (UNTRM-A). Actualidades Pedagógicas, 1(77). https://doi.org/https://doi.org/10.19052/ap.vol1.iss77.2
Cheng, Z., Zhang, Z., Xu, Q., Maeda Y, & Gu, P. (2023). A meta-analysis addressing the relationship between self-regulated learning strategies and academic performance in online higher education. J Comput High Educ., 195–224. https://doi.org/10.1007/s12528-023-09390-1
Dinno, A. (2015). Nonparametric pairwise multiple comparisons in independent groups using Dunn’s test. In The Stata Journal (Vol. 15, Number 1). https://doi.org/10.1177/1536867X1501500203
Eshet, Y., Steinberger, P., & Grinautsky, K. (2021). Relationship between statistics anxiety and academic dishonesty: A comparison between learning environments in social sciences. Sustainability (Switzerland), 13(3), 1–18. https://doi.org/10.3390/su13031564
Gafoor, A., & Sarabi, K. &. (2015). Nature of Mathematics that Impacts Difficulties in learning it: A Comparison of Student Perspectives on Learning School Subjects from Kerala.
García-Chitiva, M. (2021). Aprendizaje colaborativo, mediado por internet, en procesos de educación superior. Revista Electrónica Educare, 25(2), 1–19. https://doi.org/10.15359/ree.25-2.23
García-Peñalvo, F. J., Corell, A., Abella-García, V., & Grande, M. (2020). Online assessment in higher education in the time of COVID-19. Education in the Knowledge Society, 21. https://doi.org/10.14201/eks.23013
Garmpis A., Garmpis S., Halkiopoulos C., Panagiotarou A., & Antonopoulou H. (2026). Student Attitudes and Experiences with Distance Learning During COVID-19: A Framework for Hybrid Education. Societies, 1. https://doi.org/https://doi.org/10.3390/soc16010024
Habibzadeh, F. (2024). Data Distribution: Normal or Abnormal? Journal of Korean Medical Science, 39(3). https://doi.org/10.3346/jkms.2024.39.e35
Hammerstein, S., König, C., Dreisörner, T., & Frey, A. (2021). Effects of COVID-19-Related School Closures on Student Achievement-A Systematic Review. In Frontiers in Psychology (Vol. 12). https://doi.org/10.3389/fpsyg.2021.746289
Hernández Arteaga, L., Arias, M., Cárdenas, L., Arias, J., & Hernández, B. (2024). ISRG PUBLISHERS. Journal of Multidisciplinary Studies. https://doi.org/10.5281/zenodo.12706437
Hernández-Sampieri, R., Fernández, C., & Baptista, M. (2018). Metodología de la investigación (McGraw-Hill, Ed.; 7a ed.).
Ivanec, T. (2022). The Lack of Academic Social Interactions and Students’ Learning Difficulties during COVID-19 Faculty Lockdowns in Croatia: The Mediating Role of the Perceived Sense of Life Disruption Caused by the Pandemic and the Adjustment to Online Studying. Social Sciences, 11(2). https://doi.org/10.3390/socsci11020042
Juarros-Basterretxea, J., Aonso-Diego, G., Postigo, Á., Montes-Álvarez, P., Menéndez-Aller, Á., & García-Cueto, E. (2024). Post-Hoc Tests in One-Way ANOVA: The Case for Normal Distribution. Methodology, 20(2), 84–99. https://doi.org/10.5964/meth.11721
Kim, Y., & Cribbie, R. (2018). ANOVA and the variance homogeneity assumption: Exploring a better gatekeeper. British Journal of Mathematical and Statistical Psychology, 71(1), 1–12. https://doi.org/10.1111/bmsp.12103
Madanchian, M., & Taherdoost, H. (2025). The impact of artificial intelligence on research efficiency. Results in Engineering, 26, 104743. https://doi.org/10.1016/j.rineng.2025.104743
Marinoni, G., Van’t Land, H., & Jensen, T. (2020). The Impact of COVID-19 on Higher Education Around the World: IAU Global Survey Report. 2020. https://www.iau-aiu.net/IAU-Global-Survey-Report-The-Impact-of-COVID-19-on-Higher-Education
Maryati, I. (2024). Statistical Literacy Ability of Students through Virtual Learning Environment Based on Moodle-Learning Management System. International Journal of Information and Education Technology, 14(1), 99–106. https://doi.org/10.18178/ijiet.2024.14.1.2029
McHugh, M. (2013). The Chi-square test of independence. Biochemia Medica, (3), 143–149. https://doi.org/10.11613/bm.2013.018
Montgomery, D. (2001). Diseño y análisis de experimentos (Limusa Wiley, Ed.; 2nd ed.).
Montgomery, D., & Runger, G. (2011). Applied Statistics and Probability for Engineers (Inc. John Wiley & Sons, Ed.; 5ta. Ed.).
Myles Hollander, Douglas Wolfe, & Eric Chicken. (2014). Nonparametric Statistical Methods (). Wiley. • Páginas relevantes: Capítulo 6 (pp. 241–250) (Wiley Series in Probability and Statistics, Ed.; 3rd ed.).
Ortega, F. (2024). Digital Transformation of Higher Education During the Pandemic: Impact on Academic Management and Educational Quality. Nexus Científico, 2, 1–11. https://orcid.org/0009-0004-1329-763X
Razak, M. R., Ismail, N. Z., & Zainal Abidin, S. R. (2025). LEARNING STATISTICS COURSES IN HIGHER EDUCATION: A SYSTEMATIC REVIEW. International Journal of Education, Psychology and Counseling, 10(58), 506–526. https://doi.org/10.35631/IJEPC.1058034
Rodríguez, A., Garcia, J., & Castrillón, M. (2021). La transformación digital, un desafío inmediato ocasionado por la pandemia de Covid-19 para las entidades del sector de educación superior. Revista Boletín Redipe, 10(6). https://doi.org/10.36260/rbr.v10i6.1328
Romero, M., Romeu, T., Guitert, M., & Baztán, P. (2022). La transformación digital en la educación superior: el caso de la UOC. RIED-Revista Iberoamericana de Educación a Distancia, 26(1). https://doi.org/10.5944/ried.26.1.33998
Rubio, M., Palacios, A., Cabero, J., & Fernández, M. V. (2025). Digital Teaching Competence Regarding Foreign Languages and Learning Modes at Official Language Schools in Andalusia (Spain). Societies, 15(4), 99. https://doi.org/10.3390/soc15040099
Schraeder, M., Pyzdrowski, L., & Miller, D. (2019). The Impact of Prior Exposure to Calculus. American Journal of Educational Research, 7(3), 237–243. https://doi.org/10.12691/education-7-3-8
UNESCO. (2020). COVID-19 educational disruption and response. https://www.unesco.org/en/articles/covid-19-educational-disruption-and-response
Valdivia, E. M., Garay Martínez, L. E., Cárdenas, C. M., & Venegas Ruiz, B. (24 C.E.). PERFORMANCE OF ENGINEERING STUDENTS. Revista Electrónica ANFEI Digital. https://doi.org/https://doi.org/10.63136/read162024968pp370
Virella, P., & Cobb, C. (2021). Leveraging the Crisis for Equity and Access in the Long Term: A Brief Research Report. Frontiers in Education, 6. https://doi.org/10.3389/feduc.2021.618051
Xu, L., Duan, P., Padua, S. A., & Li, C. (2022). The impact of self-regulated learning strategies on academic performance for online learning during COVID-19. Frontiers in Psychology, 13(1047680). https://doi.org/10.3389/fpsyg.2022.1047680
Zhao, Y. (2021). The changes we need: Education post COVID-19. Journal of Educational Change, 22(1), 3–12. https://doi.org/https://doi.org/10.1007/s10833-021-09417-3
Derechos de autor 2026 Patricia Eulalia Guevara Vallejo , Emma Claudina Guevara Vallejo, Nury Gabriela Ortiz , Zuñiga Godoy Raquel Jemima, Mena López Vanessa Mariela
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
.png)
.png)
1.png)
