Learning in the openness: the lost way of the MOOC

At the end of the 2000´s, MOOCs broke into the educational field with the promise of learning with features more suited to the demands of our times. Their connectivist genesis provided a provocative expectation regarding the potential of collaboration, sharing, reuse, and free access, as factors of a possible transformation of the current educational system, which has been characterized by being rigid and reluctant to change. Given the relevance and growing participation of MOOC in education, there is a strong interest in understanding both their functioning and structure so that they can be considered as relevant educational options for a networked society. In this sense, a mixed study was conducted on 225 MOOCs based on the four categories that make up their denomination. The results of the study show that the contributions of MOOCs as generators of shared and collaborative learning experiences as proposed in their origins are not reflected in the reality of their current offering

Design of a Personalized Massive Open Online Course Platform

Focusing on the massive open online course (MOOC) platform, the purpose of this study is to realize personalized adaptive learning according to the needs and abilities of each learner. To this end, the author created a personalized adaptive learning behaviour analysis model, and designed a personalized MOOC platform based on the model. Through the analysis of learning behaviours on the MOOC platform, the model digs deep into the pattern of learning behaviours, and lays the basis for personalized intervention in the learning process. The comparison ex-periments show that our prediction method is more accurate than the other predic-tion algorithms. This research sheds new light on the design of learner-specific MOOC platform

Design of a Personalized Massive Open Online Course Platform

Focusing on the massive open online course (MOOC) platform, the purpose of this study is to realize personalized adaptive learning according to the needs and abilities of each learner. To this end, the author created a personalized adaptive learning behaviour analysis model, and designed a personalized MOOC platform based on the model. Through the analysis of learning behaviours on the MOOC platform, the model digs deep into the pattern of learning behaviours, and lays the basis for personalized intervention in the learning process. The comparison ex-periments show that our prediction method is more accurate than the other predic-tion algorithms. This research sheds new light on the design of learner-specific MOOC platform