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.
Original language | English |
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Title of host publication | Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) |
Publisher | Springer Verlag |
Pages | 512-521 |
Number of pages | 10 |
ISBN (Print) | 9783540440383, 9783540456834 |
DOIs | |
Publication status | Published - 2002 |
Event | Pacific Rim International Conference on Artificial Intelligence [PRICAI] - Duration: 1 Jan 2002 → … |
Conference
Conference | Pacific Rim International Conference on Artificial Intelligence [PRICAI] |
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Period | 1/01/02 → … |
ASJC Scopus subject areas
- General Computer Science
- Theoretical Computer Science