Abstract
E-learners always finds it is difficult to make a decision about which of learning materials best meet their situation and need to read, whilst instructors are finding it is almost impossible to reorganize different materials corresponding to individuals. Based on the investigation on real learners in the Network Education College of Shanghai Jiaotong University, we found that many learners share common need of learning resources if they have similar learning preferences and status during learning process. This paper proposes a novel E-Learning resource recommendation system based on connecting to similar E-Learners, which can find and reorganize the learners share similar learning status into smaller communities. Furthermore a recommendation platform is developed to enable the learner to share filtered resources.
Supported by National Natural Science Foundation of China under Grant No.60372078.
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Yang, F., Han, P., Shen, R., Hu, Z. (2005). A Novel Resource Recommendation System Based on Connecting to Similar E-Learners. In: Lau, R.W.H., Li, Q., Cheung, R., Liu, W. (eds) Advances in Web-Based Learning – ICWL 2005. ICWL 2005. Lecture Notes in Computer Science, vol 3583. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11528043_12
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DOI: https://doi.org/10.1007/11528043_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27895-5
Online ISBN: 978-3-540-31716-6
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