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Author:

Feng, Xiuzhen (Feng, Xiuzhen.) | Xie, Haoran (Xie, Haoran.) | Peng, Yang (Peng, Yang.) | Chen, Wei (Chen, Wei.) | Sun, Huamei (Sun, Huamei.)

Indexed by:

EI Scopus

Abstract:

With the explosion of knowledge nowadays, it is urgent for people to learn new things quickly and effectively. To meet such a requirement, how we can find a suitable path for learning has become a crucial issue. Meanwhile, in our daily life, it is important and necessary for people from various backgrounds to achieve a certain task (eg. survey, report, business plan, etc.) collaboratively in the form of the group. For these group-based task, it often requires members to learn new knowledge by using e-learning system. In this paper, we focus on addressing the problem on discovering an appropriate study path to facilitate a group of people rather than a single person for effective learning under e-learning environment. Furthermore, we propose a group model to capture the expertise of each member. Based on this model, a groupized learning path discovering (GLPD) algorithm is proposed in order to help a group of learners to grasp new knowledge effectively and efficiently. Finally, we conduct a practical experiment whose result verifies the soundness of our approach. © 2011 Springer-Verlag.

Keyword:

E-learning Learning systems Computer aided instruction

Author Community:

  • [ 1 ] [Feng, Xiuzhen]Economics and Management School, Beijing University of Technology, Beijing, China
  • [ 2 ] [Xie, Haoran]Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong
  • [ 3 ] [Peng, Yang]Department of Computing, Hong Kong Polytechnic University, Hong Kong, Hong Kong
  • [ 4 ] [Chen, Wei]School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
  • [ 5 ] [Sun, Huamei]School of Management, Harbin Institute of Technology, Harbin, China

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Source :

ISSN: 0302-9743

Year: 2011

Volume: 6537 LNCS

Page: 301-310

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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