A traditional-learning time predictive approach for e-learning systems in challenging environments

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A traditional-learning time predictive approach for e-learning systems in challenging environments

Journal Title: EAI Endorsed Transactions on e-Learning - Year 2017, Vol 4, Issue 15

Abstract

The explosion of world-wide-web has offered people a large number of online courses, e-classes and e-schools. Such e-learning applications contain a wide variety of learning materials which can confuse the choices of learner to select. Although the area of recommender systems has made a significant progress over the last several years to address this problem, the issue remained fairly unexplored for challenging environments. This paper proposes an approach to predict traditional-learning times for recommender systems in such environments.

Authors and Affiliations

K. M. Belise

Keywords

challenging environment context e-learning offline learning online learning traditional learning prediction recommender content filtering collaborative filtering

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EP ID EP45995
DOI http://dx.doi.org/10.4108/eai.29-11-2017.153391
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