Article thumbnail

Social recommender approach for technology-enhanced learning

By Mohammed Tadlaoui, Karim Sehaba, Sébastien George, Azeddine Chikh and Karim Bouamrane

Abstract

(Scimago Q3, ATIEF B)International audienceThe present work fits into the context of recommender systems for educational resources, especially systems that use social information. Based on the research results in the field of recommender systems, social networks and technology-enhanced learning, we defined an educational resource recommendation approach. We rely on social relations between learners to improve recommendation accuracy. Our proposal is based on formal models that generate three types of recommendation, namely recommendation of popular resources, useful resources and recently viewed resources. We developed a learning platform which integrates our recommendation models. I

Topics: educational resources, personalised e-learning, social networks, recommender systems, [INFO.EIAH]Computer Science [cs]/Technology for Human Learning
Publisher: 'Inderscience Publishers'
Year: 2018
DOI identifier: 10.1504/IJLT.2018.091631
OAI identifier: oai:HAL:hal-01798108v1
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.