Adaptive MOOCs: A Framework for Adaptive Course based on Intended Learning Outcomes

Increasing attention is being paid to the open learning environments (i.e., Massive Open Online Courses MOOCs) which offer so many courses in different domains by a number of the top universities around the world. Furthermore, users with different background and experience are able to browse and follow different online courses. However, richness of such courses could be also a weakness point. For instance, giving opportunity to different learners to be able to explore a huge number of courses may run the risk of overwhelming them. Furthermore, they may not be able to get the required benefit out of some followed courses as the course level is not suitable for the learners or the courses’ contents do not match intended learning outcomes (ILOs). This is considered as a motivation in academic discussions on e-learning domain to support learners with adaptive online MOOCs. This research work is aimed at supporting learners with suitable learning resources in MOOCs by investigating the possibility of providing suitable learning resources and arrange them in a way that match learner’s profile. In particular, this work elaborates on the principles used for delivering adaptive courses based on intended learning outcomes and it proposes a conceptual framework to achieve adaptation process. As a future step, a pilot evaluation will be conducted to test and verify the effectiveness of the proposed framework in term of learner’s satisfaction and dropout rate.
Publication Reference
Ewais, A., Samra, D.A. (2017). Adaptive MOOCs: A Framework for Adaptive Course based on Intended Learning Outcomes. In Proceeding of the 2nd International Conference on Knowledge Engineering and Applications (ICKEA 2017), IEEE, p.204-209

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