Abstract
The intelligent tutoring system AutoTutor uses latent semantic analysis to evaluate student answers to the tutor's questions. By comparing a student's answer to a set of expected answers, the system determines how much information is covered and how to continue the tutorial. Despite the success of LSA in tutoring conversations, the system sometimes has difficulties determining at an early stage whether or not an expectation is covered. A new LSA algorithm significantly improves the precision of AutoTutor's natural language understanding and can be applied to other natural language understanding applications.
| Original language | English |
|---|---|
| Title of host publication | IJCAI'03 Proceedings of the 18th International Joint Conference on Artificial Intelligence |
| Place of Publication | San Francisco |
| Publisher | Morgan Kaufman Publishers |
| Pages | 1489-1491 |
| Publication status | Published - 2003 |
| Externally published | Yes |
| Event | 18th International Joint Conference of Artificial Intelligence - Acapulco, Mexico Duration: 9 Aug 2003 → 15 Aug 2003 Conference number: 18 |
Conference
| Conference | 18th International Joint Conference of Artificial Intelligence |
|---|---|
| Abbreviated title | IJCAI'03 |
| Country/Territory | Mexico |
| City | Acapulco |
| Period | 9/08/03 → 15/08/03 |