2023
DOI: 10.3390/su15032136
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E-Learning Web-Apps Use Acceptance: A Way to Guide Perceived Learning Outcomes in Blended Learning

Abstract: This study empirically examines the effects of the acceptance of e-learning Web-apps by student on the learning outcomes achieved with their use. With this objective, two theoretically recognized purposes for use these apps were tested in a blended learning model, as a way to change the traditional face-to-face classrooms activities (apps we called ICTf) and as a virtual evaluation platform in learning (ICTv apps). The data was collected through online surveys from university students of a blended Master’ degr… Show more

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Cited by 2 publications
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“…Esta situación sin precedentes impulsó un cambio significativo hacia métodos de enseñanza a distancia en la educación superior, con un impacto particular en disciplinas técnicas como la ingeniería. El b-learning, que combina la enseñanza presencial con recursos en línea, ha surgido como una respuesta prometedora a estos desafíos, ofreciendo flexibilidad y acceso continuo al material didáctico (Apaza, 2022;Feria, et al, 2023;Marín, et al, 2023;Lagos, et al, 2020;Núñez, et al, 2019;López, et al, 2019).…”
Section: Introductionunclassified
“…Esta situación sin precedentes impulsó un cambio significativo hacia métodos de enseñanza a distancia en la educación superior, con un impacto particular en disciplinas técnicas como la ingeniería. El b-learning, que combina la enseñanza presencial con recursos en línea, ha surgido como una respuesta prometedora a estos desafíos, ofreciendo flexibilidad y acceso continuo al material didáctico (Apaza, 2022;Feria, et al, 2023;Marín, et al, 2023;Lagos, et al, 2020;Núñez, et al, 2019;López, et al, 2019).…”
Section: Introductionunclassified
“…Factors influencing student achievement in online learning include course structure, student engagement, instructor presence, and student satisfaction (Kim & Kim, 2021). Additionally, the acceptance of e-learning Web-apps plays a crucial role in enhancing learning outcomes, with ICTv acceptance significantly impacting student performance (Marín-Vinuesa & Rojas-García, 2023). Moreover, the adoption of elearning post-COVID-19 has led to the development of machine learning models to predict student performance during online classes, with features like activity type and timing statistics being key predictors (Segbenya et al, 2022).…”
Section: Introductionmentioning
confidence: 99%