Abandonment indicators in MOOC contexts, a pedagogical approach from the literature.
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Keywords:
MOOC, experiences, analytics, prediction, literature review
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Abstract
The dropout rate at MOOC (Massive Open Online Courses), is a problem considered to be important from the very moment of its expansion, similar to the dropout rate in more traditional forms of distance education. However, precisely because of the massive nature of the data offered by the digital platforms on which the MOOCs are implemented, the experiences which attempt to find answers to the problem of dropout in so-called learning analytics are beginning to be frequent, although in general they leave us with little or no information about the theoretical and educational foundations on which these solutions are based. This study aims to provide an approach to the problem of dropout in MOOCs from a pedagogical perspective that will enable us to find out which factors and indicators related to dropout are detected in the scientific literature related to MOOCs. To this end, a triple literature review is proposed in a sequential and complementary format, exploring the specific literature on MOOC, the literature on the use of learning analytics in MOOC to implement improvements and the specific literature on dropout in Distance Education. As a result, a list of indicators related to dropout in MOOC is provided, based on the specialised literature, which can be used as key factors to influence the design of courses in the future, or as elements to be used in approaches to the use of the analyses of those courses.
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- Universidad de Murcia
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