Recommendation System model integrated with Active Methodologies, EDM, and Learning Analytics for dropout mitigation in Distance Education ; Un modelo de Sistema de Recomendación integrado con Metodologías Activas, EDM y Learning Analytics para la reducción del abandono en Educación a Distancia ; Um modelo de Sistema de Recomendação integrado a Metodologias Ativas, MDE e Learning Analytics para a mitigação de evasão em EaD

Distance Education enabled educational practices based on digital platforms. Despite its wide adoption, the high dropout rates are a reason for concern for teachers and institutional managers. There are initiatives to mitigate this situation, such as Educational Data Mining (EDM), Learning Analytics (LA), and the use of Recommendation Systems (RS). Although effective in specific aspects, these techniques lack mechanisms for students' motivation and pedagogical intervention by teachers, as they do not present methodological proposals to encourage learning. Therefore, this article describes an RS model that shows a differential integration of the pedagogical approach of Active Methodologies with the support of Educational Data Mining and Learning Analytics techniques to identify students with dropout risks and enhance permanence. For this, a prototype was implemented, and a case study was carried out with professors from two universities to assess functionality and acceptance. According to the TAM Model, more than 87% of teachers agree with the ease of use, and 77% agree that RS can be helpful in students' teaching and learning process. Therefore, the model contributes to teaching practices, encourages collaborative learning, and favors monitoring this process and the activities developed by the students. ; La Educación a Distancia posibilitó prácticas educativas basadas en plataformas digitales. A pesar de su amplia adopción, las altas tasas de abandono son un motivo de preocupación para los maestros y gerentes institucionales. Existen iniciativas para mitigar esta situación, como Educational Data Mining (EDM), Learning Analytics (LA) y el uso de Sistemas de Recomendación (SR). Si bien son efectivas en aspectos específicos, estas técnicas carecen de mecanismos para la motivación de los estudiantes y la intervención pedagógica de los docentes, ya que no presentan propuestas metodológicas para incentivar el aprendizaje. Por tanto, este artículo describe un modelo de SR que presenta como diferencial la integración ...