Abstract
Group learning is an effective and efficient way to promote greater academic success. However, almost all group-learning systems stress collaborative learning activity itself, with few focused on how groups should be formed. In this paper, we present a novel group forming technique based on students’ browsing behaviors with the help of a curriculum knowledge base. To achieve this, a data clustering technique was adopted. Before clustering, new features are constructed based on an arithmetic-composition-based feature construction technique. Preliminary results have shown that the new features can well represent the problem space and thus make the group forming outcomes more convincing.
The work was conducted while the author was still with Department of Computing, Hong Kong Polytechnic University, Hong Kong.
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Tang, T.Y., Chan, K.C. (2002). Feature Construction for Student Group Forming Based on Their Browsing Behaviors in an E-learning System. In: Ishizuka, M., Sattar, A. (eds) PRICAI 2002: Trends in Artificial Intelligence. PRICAI 2002. Lecture Notes in Computer Science(), vol 2417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45683-X_55
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DOI: https://doi.org/10.1007/3-540-45683-X_55
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