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

Belise, K. M. (2017) A traditional-learning time predictive approach for e-learning systems in challenging environments. EAI Endorsed Transactions on e-Learning, 4 (15): 4. ISSN 2032-9253

[img]
Preview
Text (PDF)
eai.29-11-2017.153391.pdf - Published Version
Available under License Creative Commons Attribution No Derivatives.

Download (739kB) | Preview

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.

Item Type: Article
Uncontrolled Keywords: challenging environment, context, e-learning, offline learning, online learning, traditional learning, prediction, recommender, content filtering, collaborative filtering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor I.
Date Deposited: 17 Sep 2020 08:56
Last Modified: 17 Sep 2020 08:56
URI: https://eprints.eudl.eu/id/eprint/397

Actions (login required)

View Item View Item