Impact of Online Learning Strategies on Academic Engagement in Peruvian University Students: Moderating Role of Emotional Exhaustion Levels.
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| Title: | Impact of Online Learning Strategies on Academic Engagement in Peruvian University Students: Moderating Role of Emotional Exhaustion Levels. |
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| Authors: | Concha-Huarcaya, Manuel A.1, Serpa-Barrientos, Antonio2, Vivas-Rivas, Leidy Johana1, Saintila, Jacksaint3 jacksaintsaintila@gmail.com |
| Source: | Electronic Journal of Research in Educational Psychology. Dec2025, Vol. 23 Issue 67, p506-526. 22p. |
| Subject Terms: | *Student engagement, *Psychological burnout, *College students, *Psychology of students, *Online education, Prediction models, Gender differences (Sociology) |
| Abstract (English): | Introduction. In the current scientific literature, there is limited knowledge about the moderating role that emotional exhaustion (EE) plays in the dynamics between online learning strategies (LS) and academic engagement (AE) of university students. The aim of this research was to evaluate the moderating role of emotional exhaustion levels in the relationship between online learning strategies and AE in Peruvian university students. Method. A predictive transversal design study was carried out, aimed at evaluating the moderating function. A total of 520 students were evaluated (389 females = 74.8%; 131 males = 25.2%; age range = 18-40). Results. It is evident that the variables are related and that EE levels would be playing a moderating role in the relationship between online learning strategies and academic engagement, especially those categorized as low and average emotional exhaustion levels (EElow = .196, p < .01, 95 % CI [ 0.078, 0.313]; EEaverage = .112, p < .01, 95 % CI [ 0.033, 0.191]). It is also observed that in the group of women, the levels of emotional exhaustion show a statistically significant moderation effect (XWwomen = .031, p < .05, 95% CI [-0.229, -0.011]). In contrast, in the group of men, a level of statistical significance is not reached (XWmen = -0.059, p > .05). Conclusion. Levels of emotional exhaustion appear to have a more conditioning effect on the relationship between online learning strategies and academic engagement in women compared to men. [ABSTRACT FROM AUTHOR] |
| Abstract (Spanish): | Introducción. En la literatura científica actual, existe un conocimiento limitado sobre el papel moderador que desempeña el agotamiento emocional (AE) en la dinámica entre las estrategias de aprendizaje en línea (EAL) y el compromiso académico (CA) de los estudiantes universitarios. Objetivo. El objetivo de esta investigación consistió en evaluar la función moderadora de los niveles de AE en la relación entre las EAL y CA en estudiantes universitarios peruanos. Método. El total de estudiantes evaluados fue 520 (389 mujeres = 74,8 %; 131 hombres = 25,2; rango de edad = 18-40); el tipo de investigación fue empírico de estrategia asociativa con diseño explicativo, orientado a evaluar la función moderadora. Resultados. Los resultados permiten sugerir que estas variables están relacionadas y que los niveles de cansancio emocional estarían desempeñando un papel importante como moderador en la relación entre las estrategias de aprendizaje en línea y compromiso académico, en especial los categorizados como nivel bajo y promedio de agotamiento emocional (CABajo = .196, p < .01, IC 95 % [ 0.078, 0.313]; CApromedio = .112, p < .01, IC 95 % [ 0.033, 0.191]). También se observa que, en el grupo de mujeres, los niveles de cansancio emocional muestran un efecto de moderación estadísticamente significativo (XWmujeres = .031, p < .05, IC 95 % [ -0.229, -0.011]). En contraste, en el grupo de hombres, no se alcanza un nivel de significancia estadística (XWhombres = -0.059, p > .05). Conclusión. En conclusión, los niveles de cansancio emocional parecen tener un efecto más condicionante en la relación entre las estrategias de aprendizaje en línea y el compromiso académico de las mujeres en comparación con los hombres. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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