loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Qing Tang 1 ; Marie-Hélène Abel 1 and Elsa Negre 2

Affiliations: 1 Sorbonne Universités, UTC, CNRS UMR 7253, HEUDIASYC, 60200 Compiègne, France ; 2 Paris-Dauphine University, PSL Research University, CNRS UMR 7243, LAMSADE, 75016 Paris, France

Keyword(s): Online Learning, SoIS, Collaborative Learning Environment, Recommender System, Learner Track.

Abstract: Learning with huge amount of open educational resources is challenging, especially when variety resources come from different System of Information Systems (SoIS). How to help learners obtain appropriate resources efficiently in collaborative learning environment is still a rigorous problem of research. This paper proposes a method to calculate learner’s knowledge competency by tracking and analyzing their behaviors in a collaborative learning environment based on SoIS, and combining other basic learner’s information to build a personalized recommender system to help learners select appropriate educational resources to improve their learning efficiency.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.204.56.97

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Tang, Q.; Abel, M. and Negre, E. (2020). Improve Performance of Recommender System in Collaborative Learning Environment based on Learner Tracks. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KMIS, ISBN 978-989-758-474-9; ISSN 2184-3228, pages 270-277. DOI: 10.5220/0010214702700277

@conference{kmis20,
author={Qing Tang. and Marie{-}Hélène Abel. and Elsa Negre.},
title={Improve Performance of Recommender System in Collaborative Learning Environment based on Learner Tracks},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KMIS,},
year={2020},
pages={270-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010214702700277},
isbn={978-989-758-474-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KMIS,
TI - Improve Performance of Recommender System in Collaborative Learning Environment based on Learner Tracks
SN - 978-989-758-474-9
IS - 2184-3228
AU - Tang, Q.
AU - Abel, M.
AU - Negre, E.
PY - 2020
SP - 270
EP - 277
DO - 10.5220/0010214702700277