Abstract
Online discussion board has become increasingly popular in higher ed-ucation. As a step towards analyzing the role that students and instructors play during the discussion process and assessing students' learning from discussions, we model different types of contributions made by instructors and students with a dialogue-state model. By analyzing frequent Q&A discussion patterns, we have developed a graphic model of dialogue states that captures the information role that each message plays, and used the model in analyzing student discussions. We present several viable approaches including CRF, SVM, and decision tree for the state classification. Using the state information, we analyze information exchange patterns and resolvedness of the discussion. Such analyses can give us a new insight on how students interact in online discussions and kind of assistance needed by the students.
Original language | English |
---|---|
Pages (from-to) | 15-24 |
Number of pages | 10 |
Journal | CEUR Workshop Proceedings |
Volume | 1009 |
State | Published - 2013 |
Event | Workshops at the 16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, United States Duration: 9 Jul 2013 → 13 Jul 2013 |
Keywords
- CRF
- Dialogue transition
- Online discussions
- Speech act