El efecto de las experiencias previas en el aprendizaje virtual sobre laautoeficacia del estudiante durante el COVID-19: El rol mediadorde la autorregulación.
Palabras clave:
Educación remota, Autoeficacia, Autoregulación, COVID-19, SEMResumen
La pandemia de COVID-19 obligó a muchas instituciones educativas a continuar sus planes de formación desde casa, considerando el uso del aprendizaje remoto de emergencia. La autoeficacia en el aprendizaje virtual es un aspecto fundamental para que los estudiantes rindan como se espera en dichos entornos. Este estudio cuasi-experimental examinó el efecto de las experiencias de aprendizaje virtual en la autoeficacia y evaluó la autorregulación de los estudiantes como mecanismo a través del cual las experiencias previas influyen en la autoeficacia de los estudiantes universitarios (N = 301) durante el confinamiento por la COVID-19. Los resultados mostraron que, antes de comenzar el aprendizaje remoto de emergencia, las experiencias previas se relacionaban positivamente con la autoeficacia, pero esta relación también se producía a través de la autorregulación. Por otra parte, se descubrió que, tras completar el ciclo de aprendizaje remoto de emergencia, solo los estudiantes con mayor autoeficacia eran aquellos que tenían experiencia previa en el aprendizaje virtual y se autorregulaban. Los resultados de este estudio muestran el efecto adverso de la mala preparación de las instituciones educativas en el proceso de aprendizaje de los estudiantes.
Descargas
Referencias
Aldhahi MI, Alqahtani AS, Baattaiah BA, et al (2022). Exploring the relationship between students' learning satisfaction and self-efficacy during the emergency transite to remote learning amid the coronavirus pandemic: A cross-sectional study. Education and Information Technologies, 27(1):1323–1340.
Azis YM, Leatemia M (2021). The effectiveness of e-learning, learning styles, prior knowledge, and internet self efficacy in business mathematics courses. Kreano, Jurnal Matematika Kreatif-Inovatif, 12(2):353–364.
Bandura A, Freeman WH, Lightsey R (1999). Self-efficacy: The exercise of control.
Barnard L, Lan WY, To YM, et al (2009). Measuring self-regulation in online and blended learning environments. The internet and higher education, 12(1):1–6.
Bubou GM, Job GC (2022). Individual innovativeness, self-efficacy and e-learning readiness of students of yenagoa study centre, national open university of nigeria. Journal of Research in Innovative Teaching & Learning, 15(1):2–22.
Chiang FK, Zhang Y, Zhu D, et al (2022). The influence of online stem education camps on students' self-efficacy, computational thinking, and task value. Journal of Science Education and Technology, 31(4):461–472.
Demiroren M, Turan S, Oztuna D (2016). Medical students' self-efficacy in problem-based learning and its relationship with self-regulated learning. Medical education online, 21(1):30049.
Dinh LP, Nguyen TT (2020). Pandemic, social distancing, and social work education: Students' satisfaction with online education in Vietnam. Social Work Education, 39(8):1074–1083.
ECLAC N, UNESCO (2020). Education in times of the covid-19 pandemic. ECLAC.
Escobar GAT, Parra LS (2019). Virtual psychological counseling at the Colombian University Biana: beyond academic performance. Andean Research, 21(38):113–124.
González H (2021). Perception of students and teachers about education Distance and virtual education at a higher education institution. Universidad del Norte URL http://manglar.uninorte.edu.co/handle/10584/10165#page=1.
Hair JF, Black WC, Babin BJ, et al (2013). Multivariate data analysis: Pearson new international edition PDF eBook. Pearson Higher Ed.
Hayat AA, Shateri K, Amini M, et al (2020). Relationships between academics self-efficacy, learning-related emotions, and metacognitive learning strategies with Academic performance in medical students: a structural equation model. BMC medical education, 20(1):1–11.
Hu Lt, Bentler PM (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1):1–55.
Hussein Hakeem Barzani S (2021). Students' perceptions towards online education during covid-19 pandemic: An empirical study. International Journal of Social Sciences & Educational Studies, 8(2):28–38.
Ismail II, Abdelkarim A, Al-Hashel JY (2021). Physicians' attitude towards webinars and online education amid covid-19 pandemic: When less is more. PloS one, 16(4):e0250241.
Jurisevic M, Lavrih L, Lisic A, et al (2021). Higher education students' experience of emergency remote teaching during the covid-19 pandemic in relation to self-regulation and positivity. CEPS Journal, 11(Special Issue):241–262.
Molina Guti´errez TdJ, Lizcano Chapeta CJ, Alvarez Hernandez SdR, et al (2021). Student crisis in a pandemic. How do university students value the virtual education? Conrado, 17(80):283–294.
Patricio GH, Olmedo Moreno EM (2017). Academic self-efficacy and performance school: a methodological and correlational study in schoolchildren. University of Grenade.
Peechapol C, Na-Songkhla J, Sujiva S, et al (2018). An exploration of factors influencing Self-efficacy in online learning: A systematic review. International Journal of Emerging Technologies in Learning (Online), 13(9):64.
R Core Team (2022). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, URL https://www.R-project.org/.
Rahmawati RN (2019). Self-efficacy and use of e-learning: A theoretical review technology acceptance model (tam). American Journal of Humanities and Social Sciences Research, 3(5):41–55.
Ricardo C, Vieira C (2023). Beliefs and conceptions of higher education teachers in remote teaching in the context of covid-19. RIED Ibero-American Journal of Distance Education, 26(1):17–37.
Roddy C, Amiet DL, Chung J, et al (2017). Applying best practice online learning, teaching, and support to intensive online environments: An integrative review. In: Frontiers in education, Frontiers Media SA, p 59.
Rosario P, Lourenco A, Paiva O, et al (2012). Prediction of mathematics achievement: effect of personal, socioeducational and contextual variables. Psychothema, 24(2):289–295.
Rosseel Y (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2):1–36. https://doi.org/10.18637/jss.v048.i02.
Ruiz MA, Pardo A, San Martín R (2010). Structural equation models. Papers of the psychologist, 31(1):34–45.
Shih HJ (2019). L2 anxiety, self-regulatory strategies, self-efficacy, intended effort and academic achievement: A structural equation modeling approach. International Education Studies, 12(3):24–35.
Sun JCY, Rueda R (2012). Situational interest, computer self-efficacy and self-regulation: Their impact on student engagement in distance education. British journal of educational technology, 43(2):191–204.
van Buuren S, Groothuis-Oudshoorn K (2011). mice: Multivariate imputation by chained equations in r. Journal of Statistical Software, 45(3):1–67. https://doi.org/10.18637/jss.v045.i03.
Wang CH, Shannon DM, Ross ME (2013). Students' characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, 34(3):302–323.
Wilde N, Hsu A (2019). The influence of general self-efficacy on the interpretation of vicarious experience information within online learning. International Journal of Educational Technology in Higher Education, 16(1):1–20.
Xia Y, Yang Y (2019). Rmsea, cfi, and tli in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. behavior Research Methods, 51:409–428.
Zhang Z (2016). Multiple imputation with multivariate imputation by chained equation (mice)package. Annals of translational medicine, 4(2).
Zhao Y, Lei J, Lai BYC, et al (2005). What makes the difference? a practical analysis of research on the effectiveness of distance education. Teachers College Record, 107(8):1836–1884.
Zhou N, Fischer C, Rodriguez F, et al (2020). Exploring how rolling in an online organic chemistry preparation course relates to students' self-efficacy. Journal of Computing in Higher Education, 32:505–528.
Zimmerman WA, Kulikowich JM (2016). Online learning self-efficacy in students with and without online learning experience. American Journal of Distance Education, 30(3):180–191.
Descargas
Publicado
Número
Sección
Licencia
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Nexus (MIR) es una revista de acceso abierto (Open Access). Todo su contenido se distribuye bajo los términos de la licencia Creative Commons Atribución-NoComercial 4.0 Internacional (CC BY-NC 4.0).
Esta licencia permite a terceros distribuir, remezclar, adaptar y ampliar su obra de manera no comercial, siempre que se dé el crédito correspondiente al autor original y a la revista, y se proporcione un enlace a la licencia. Usted puede consultar la versión completa de la licencia en: https://creativecommons.org/licenses/by-nc/4.0/deed.es
