Feature Construction for Student Group Forming Based on Their Browsing Behaviors in an E-learning System

Authors:
Tiffany Ya Tang;Keith C. C. Chan
Affiliations:
-;-
Venue:
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Year:
2002

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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.