Proceedings of the 2nd International Conference on Teaching and Computational Science

Study on Learning Resources Recommendation Based on Tasks in Team Collaboration

Authors
Lin Gong, Jian Xie, Yang Liu, Xiaodan Zhang
Corresponding Author
Lin Gong
Available Online May 2014.
DOI
10.2991/ictcs-14.2014.19How to use a DOI?
Keywords
learning resources; knowledge recommendation; team collaboration; knowledge modeling
Abstract

Nowadays, learning team has become an important foundation for modern work. In a team, how to recommend learning resources to the appropriate team member according to the task requirements is a key factor of success. This paper firstly reviewed related methods and concepts in knowledge modeling and learning recommendation. Then, it constructed a model for teamwork tasks, knowledge and team members. Based on knowledge background and experience of team members in the project, it recommended learning resources to the members according to the assigned tasks. Finally, the prototype system was built for practical validation.

Copyright
© 2014, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Teaching and Computational Science
Series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
978-94-62520-21-9
ISSN
1951-6851
DOI
10.2991/ictcs-14.2014.19How to use a DOI?
Copyright
© 2014, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lin Gong
AU  - Jian Xie
AU  - Yang Liu
AU  - Xiaodan Zhang
PY  - 2014/05
DA  - 2014/05
TI  - Study on Learning Resources Recommendation Based on Tasks in Team Collaboration
BT  - Proceedings of the 2nd International Conference on Teaching and Computational Science
PB  - Atlantis Press
SP  - 75
EP  - 79
SN  - 1951-6851
UR  - https://doi.org/10.2991/ictcs-14.2014.19
DO  - 10.2991/ictcs-14.2014.19
ID  - Gong2014/05
ER  -