Cursos MOOC: factores que disminuyen el abandono en los participantes

Yamba-Yugsi, Marco; Luján‐Mora, Sergio

doi:10.29019/enfoqueute.v8n1.124

Cited by 10 publications

(5 citation statements)

References 6 publications

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“…Major findings in this study are at large consistent with those in previous studies (e.g. Hone & EI Said, 2016; Riyami et al, 2019; Watted & Barak, 2018; Yamba-Yugsi & Lujan-Mora, 2017). The significance of the results is that Learner Retention in MOOC-based learning is subject to various influence factors: Instructor-to-Learner Interaction, Instructor Support, Instructor Feedback, Learner-to-Learner Interaction, Course Content, Course Structure, Information Delivery, Perceived Effectiveness, Quality Resources, Flexibility and Scaffolding for Diversity, Technology, The Focus of Subjects, Pre-Course Information, and Timing.…”

Section: Discussionsupporting

confidence: 93%

“…Numerous factors involving learners, instructors, and technologies have been discussed regarding their influence on MOOC-based learning (Ayub et al, 2017). Collaboration and interactions between learners (Riyami et al, 2019), user profile, the experience of making MOOCs, and the level of satisfaction in the interaction with MOOCs strongly influenced Learner Retention in MOOCs (Yamba-Yugsi & Lujan-Mora, 2017). Three interactions, that is, learner-to-learner interactions, instructor-to-learner interactions, and learner-to-content interactions, were considered important factors that might exert a significant influence on Learner Retention in MOOC-based learning (Bernard et al, 2009).…”

Section: Interactions In Moocsmentioning

confidence: 99%

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Examining Factors That Influence Learner Retention in MOOCs During the COVID-19 Pandemic Time

2023

Sage Open

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Massive Open Online Courses have become a frequent platform for learners to acquire knowledge. This study aims to explore multiple factors influencing learner retention in MOOCs during the COVID-19 pandemic. To address this, we collected quantitative and qualitative data from questionnaires and qualitative data from interviews and then analyzed them through the Partial Least Square–Structural Equation Modeling to test 14 research hypotheses. The proposed research model and research hypotheses are empirically tested with 243 participants across the world. According to the results, support is found for all of the 14 research hypotheses. We confirmed 14 factors influencing learner retention in MOOCs. The result is beneficial for designers and manufacturers of MOOCs to improve the quality of the products and facilitate online or blended learning during this special time. It could also help students improve their learning experiences. Future research could examine influencing factors of learner retention in MOOCs with interdisciplinary cooperation.

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Section: Discussionsupporting

confidence: 93%

Section: Interactions In Moocsmentioning

confidence: 99%

Examining Factors That Influence Learner Retention in MOOCs During the COVID-19 Pandemic Time

2023

Sage Open

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“…The students lack the abilities/skills and prerequisites to follow the course. According to previous studies [27], [28], [29], demonstrating the effect of students' academic skills and abilities and their prior experience on the drop-out rate in MOOCs.…”

Section: Resultsmentioning

confidence: 99%

Intelligent System for Personalised Interventions and Early Drop-out Prediction in MOOCs

Alj¹,

Bouayad²,

Oucamah³

2022

IJACSA

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In this paper, we propose an approach to early detect students at high risk of drop-out in MOOC (Massive Open Online Course); we design personalised interventions to mitigate that risk. We apply Machine Learning (ML) algorithms and data mining techniques to a dataset extracted from XuetangX MOOC learning platforms and sourced from the KDD cup 2015. Since this dataset contains only raw student log activity records, we perform a hybrid feature selection and dimensionality reduction techniques to extract relevant features, and reduce models complexity and computation time. Besides, we built two models based on: Genetic Algorithms (GA) and Deep Learning (DL) with supervised learning methods. The obtained results, according to the accuracy and the AUC (Area Under Curve)-ROC (Reciever Operator Characteristic) metrics, prove the pertinence of the extracted features and encourage the use of the hybrid features selection. They also proved that GA and DL are outperforming the baseline algorithms used in related works. To assess the generalisation of the approach used in this work, The same process is performed to a second benchmark dataset extracted from the university MOOC. Then, a single web application hosted on the university server, produces an individual weekly drop-out probability, using time series data. It also proposes an approach to personalise and prioritise interventions for at-risk students according to the drop-out patterns.

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“…Estos estudios destacaron la importancia de que el aprendizaje, "el cual debe estar centrado en el problema, encuentran que las exposiciones deben ser claras, la accesibilidad y dedicación del instructor son considerados factores relevantes, y también son relevantes el aprendizaje activo y la interacción entre los estudiantes".  Los estudios de Yamba-Yugsi, y Luján-Mora (2017) abordaron varios aspectos, incluida la satisfacción del estudiante, que se midió en función del grado de dificultad percibida y el esfuerzo realizado por los estudiantes para completar el curso. Se encontró que entre el 40% y el 56% de los participantes consideraban tanto la dificultad como el esfuerzo desarrollado estaban en línea a sus expectativas, en realidad es un porcentaje relativamente bajo, y es una de las explicaciones del porqué estos cursos tienen un bajo porcentaje de eficiencia terminal.…”

Section: Investigaciones Sobre Los Moocunclassified

MOOCs en el desarrollo humano de la sociedad del conocimiento

Martínez-Pagola,

León-Olivares,

Enciso-González

et al. 2023

ICBI

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El presente trabajo de investigación documental y reflexión, nace de la inquietud de conocer el impacto que han tenido los MOOC´s “Masive Open Online Course” (Escopeo, 2013) o Cursos Masivos Abiertos y a Distancia en español, dentro del proceso educativo, cultural, de capacitación continua o capacitación para la vida, como elementos no formales educativos o incluso como opciones formales de educación incluyendo títulos, diplomas o certificaciones. Los MOOC´s por tanto, se han convertido de algunos años a la fecha en una opción viable para poder acrecentar la sociedad del conocimiento, en donde convergen plataformas, cursos, contenidos y desarrollos didácticos e instruccionales, algunos mejores que otros, pero que de cualquier manera generan una opción para poder adentrarse en áreas de conocimiento muy acorde a nuestros tiempos, aprovechando todos los beneficios de la sociedad de la información y del conocimiento, en este caso la ubicuidad.

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Cursos MOOC: factores que disminuyen el abandono en los participantes

Cited by 10 publications

References 6 publications

Examining Factors That Influence Learner Retention in MOOCs During the COVID-19 Pandemic Time

Examining Factors That Influence Learner Retention in MOOCs During the COVID-19 Pandemic Time

Intelligent System for Personalised Interventions and Early Drop-out Prediction in MOOCs

MOOCs en el desarrollo humano de la sociedad del conocimiento

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