A proposed framework for an adaptive learning of Massive Open Online Courses (MOOCs)

2016 
The use of Massive Open Online Courses (MOOCs) system has increased significantly in the recent years. Among the pioneers of the MOOCs is the Massachusetts Institute of Technology (MIT). The latest development, that of the Internet (including very recently the mobile Internet), has similarly been adopted by many existing higher education providers but has also supported the emergence of a new model dubbed a massive open online course (MOOCs), the term coined in 2008 to describe an open online course to be offered by the University of Manitoba in Canada. A range of both topics and platforms have since emerged and the term was described as "the educational buzzword of 2012" by Daniel (2012) reflecting widespread interest in the concept. MOOCs attract many learners from all over the world, so there is a need to enhance the MOOCs to meet the individual needs. This paper investigates the MOOCs system by reviewing the available literatures and suggesting a proposed framework, which considered a list of recommendation of instructional material using the learner's profile and experience. In this suggested framework, we customize what best requirements and list of recommendations we gain by the learner experience with the system that will be authorized by the teacher assistants and accepted by the professor "Authors". We also utilized the adaptability (UCD); approach which calls for placing the learner at the center of the design process during learners' interactions with the MOOCs system. Moreover, the framework can present the user with a suggested learning requirements to meet the appropriate learning objectives based on their current preferences and experience. As the learner progresses, further recommendations can be made with appropriate resources to enhance and develop the learner's understanding of the previous topics. The framework is open for learners to be evaluated by adapting the existing MOOCs at their institutions, allowing comparison of a variety of aspects including choice of learning path, and learner satisfaction.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    12
    References
    10
    Citations
    NaN
    KQI
    []