Adaptive and cooperative model of knowledge management in MOOCs
Resumen: One of the characteristics of Massive Open Online Courses (MOOC) is the heterogeneity of their participants’ profiles and, for the most traditional MOOC model, this is an important cause of the low completion rate. The MOOC model presents two apparent antagonistic concepts, globalization and diversity. MOOCs represent globalization (participants have to be adapted to the course) and their participants represent diversity. The authors of this paper argue that both concepts complement each other; that is, a MOOC can adapt the contents and navigation to the diversity of participants; and in turn the participants themselves can increase and improve the contents of the MOOC, through heterogeneous cooperation, to encourage massive learning. To proof it, this paper presents a new model, called ahMOOC, combining the hybrid-MOOC (hMOOC) and the adaptive MOOC (aMOOC). The hMOOC allows integrating characteristics of xMOOCs (based on formal e-training) with cMOOCs (based on informal and cooperative e-training). The aMOOC offers different learning strategies adapted to different learning objectives, profiles, learning styles, etc. of participants. The ahMOOCs continues having a lower dropout rate (such as hMOOC) than the traditional MOOCs. The qualitative analysis show the capacity of participants, with heterogeneous profiles, to create, in a cooperative and massive way, useful knowledge to improve the course and, later, to apply it in their specific work context. The study also shows that participants have a good perception on the capabilities of the ahMOOC to adapt the learning process to their profiles and preferences.
Idioma: Inglés
DOI: 10.1007/978-3-319-58509-3_22
Año: 2017
Publicado en: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10295 (2017), 273-284
ISSN: 0302-9743

Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2016-80347-R
Tipo y forma: Artículo (PrePrint)
Área (Departamento): Matemática Aplicada (Departamento de Matemática Aplicada)

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Exportado de SIDERAL (2018-06-08-08:26:10)

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