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.
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||7th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2002|
|Period||18/08/02 → 22/08/02|
- Theoretical Computer Science
- Computer Science(all)