Abstract:

Since 2011, the MOOC tendency still be the most discussed and attractive online learning innovation over the world. On the large of these five years many researches were done around this recent e-learning generation including case studies, surveys, synthesis and models. In fact several issues are discussed such as: MOOC design as course and platform, assessments strategies and methods, the learner’s motivation and engagement, etc. In this paper, we suggest a conceptual model for MOOC content design focusing on the course objectives definition and specification so that the course can meet gradually more and more learners’ requirements and expectations over the world. This is from one side, from another side we aim with the proposed design to give the MOOC user to the possibility to be directed to the part of the course (by proposing him an adapted path) according to his objectives, that can already integrated to the MOOC or by suggesting them to the MOOC designers who can update the given MOOC knowledge. In this way, we will have novelty in interaction that gives a dynamic to the MOOC where users and designers learn from each other to get in the end a worldwide discipline capitalization about the disciplinary handled by the MOOC. This model is supported by a disciplinary domain ontology that represents the MOOC content Meta data. This domain ontology gives knowledge where the course objectives defined with their respective connections or semantic links to different other concepts such as: evaluation units, pedagogical resources (documents, podcasts, simulation …). Our proposition gives the possibility to represent a MOOC so that it will be possible to easily process automated assessment or formative evaluation and deduce constructive feedbacks that can enhance learners’ motivation. By adopting this model, the MOOC knowledge can be constantly updated by two main processes taking advantages from the openness of the system. Firstly, by capturing expertise of professionals in the given era, they can suggest other professional objectives and real case studies. Secondly, by expert teachers, they can suggest other pedagogical objectives and redundant errors and obstacles met by their students. Connected to the concepts associated with them, the errors can serve as a mean of assessment of learners who are sanctioned by a grade and a list of non mastered concepts. In another hand, in addition of consulting the courses to whom are interested, the proposed model includes objectives’ retrieval process, which assists the users when looking for their own objectives among of the existing ones on the system.

Keywords:

Knowledge capitalization, Massive Open Online Courses (MOOC), MOOC design, formative assesment.