Abstract
The success of MOOC (massive open online courses) is rapidly increasing. Most educational institutions are highly interested in these online platforms, which embrace intellectual and educational objectives and provide various opportunities for lifelong learning. However, many limitations, such as learners' diversity, lack of motivation, affected learners' outcomes, which unfortunately raised the dropout rate. Thus, multiple solutions were afforded on MOOC platforms to tackle these common problems. This paper suggests a model outline of a customizable system Context-Driven Massive Open Online Courses that could be implemented in any learning environment, and that goes hand in hand with learners' context to boost their motivation towards learning, and to help identify their learning needs. The paper introduces CD-MOOC following a learner-based approach by employing two types of users' data; long-term and short-term data assembled form learners' online traces when interacting on the platform. The data help users design their own learning path based on their context and preferences.
Highlights
Knowledge acquisition outside schools has been a major dilemma before the emergence of online courses which introduced a new paradigm of learning
This paper aims at setting up a model for personalizing educational content on an online learning platform considering learners’ context in order to reduce the dropout rate by instigating learners’ motivation
The CD-massive open online course (MOOC) model implementation opted for using web technologies; the work was developed under the WAMPSERVER environment
Summary
Knowledge acquisition outside schools has been a major dilemma before the emergence of online courses which introduced a new paradigm of learning. Even though correspondence courses have existed since 1800s for students who didn’t have the chance to attend university (Kentnor, 2015), they were never as effective as online learning. A massive open online course (MOOC) is an online learning environment offering an open access to all network users often for free or with lower cost (McAuley et al, 2010). MOOC includes a large group of learners with different backgrounds: level of understanding, age, learning habits and so on, where there exist no variation of online teaching methods behind the screen. Online content must be designed and adapted according to the educational background of each learner, as an adaptable learning system improves the online. Personalisation in learning systems can help increase students’ motivation as it can provide an independent learning experience based on learners interests, preferences, backgrounds and abilities
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