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Direct linkMa, Xueying; Ye, Lu – International Journal of Mobile and Blended Learning, 2018
This article describes how e-learning recommender systems nowadays have applied different kinds of techniques to recommend personalized learning content for users based on their preference, goals, interests and background information. However, the cold-start problem which exists in traditional recommendation algorithms are still left over in…
Descriptors: Electronic Learning, Individualized Instruction, Occupational Aspiration, Intelligent Tutoring Systems
