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.
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Feng, X., Xie, H., Peng, Y., Chen, W., Sun, H. (2011). Groupized Learning Path Discovery Based on Member Profile. In: Luo, X., Cao, Y., Yang, B., Liu, J., Ye, F. (eds) New Horizons in Web-Based Learning - ICWL 2010 Workshops. ICWL 2010. Lecture Notes in Computer Science, vol 6537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20539-2_32
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DOI: https://doi.org/10.1007/978-3-642-20539-2_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20538-5
Online ISBN: 978-3-642-20539-2
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