NotesFAQContact Us
Collection
Advanced
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1146064
Record Type: Journal
Publication Date: 2017-Jul
Pages: 23
Abstractor: As Provided
Reference Count: 30
ISBN: N/A
ISSN: ISSN-1360-2357
Personalized Recommender System for e-Learning Environment
Benhamdi, Soulef; Babouri, Abdesselam; Chiky, Raja
Education and Information Technologies, v22 n4 p1455-1477 Jul 2017
Traditional e-Learning environments are based on static contents considering that all learners are similar, so they are not able to respond to each learner's needs. These systems are less adaptive and once a system that supports a particular strategy has been designed and implemented, it is less likely to change according to student's interactions and preferences. New educational systems should appear to ensure the personalization of learning contents. This work aims to develop a new personalization approach that provides to students the best learning materials according to their preferences, interests, background knowledge, and their memory capacity to store information. A new recommendation approach based on collaborative and content-based filtering is presented: NPR_eL (New multi-Personalized Recommender for e-Learning). This approach was integrated in a learning environment in order to deliver personalized learning material. We demonstrate the effectiveness of our approach through the design, implementation, analysis and evaluation of a personal learning environment.
Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A