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Mapping of Learning Style with Learning Object Metadata for Addressing Cold-Start Problem in E-Learning Recommender Systems
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Joy, Jeevamol; Renumol, V. G. – International Journal of Learning Technology, 2021
In the e-learning domain, content recommender systems had evolved to recommend relevant learning contents based on the learner preferences. One of the significant drawbacks of content recommenders in the e-learning domain is the new user cold-start problem. The objective of this study is to propose a recommendation model for addressing the…
Descriptors: Cognitive Style, Electronic Learning, Metadata, Integrated Learning Systems