Far East Journal of Experimental and Theoretical Artificial Intelligence
Volume 1, Issue 2, Pages 87 - 125
(May 2008)
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EXTRACTING INFORMATION FROM NATURAL LANGUAGE INPUT TO AN INTELLIGENT TUTORING SYSTEM
Michael S. Glass (USA) and Martha W. Evens (USA)
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Abstract:
We have constructed a new module to process student natural language input to CIRCSIM-Tutor, an intelligent tutoring system designed to help medical students learn to solve problems involving the negative feedback process that regulates blood pressure in the human body. CIRCSIM-Tutor spends most of its time engaging the student in a natural language-based dialogue. The new input understander uses an information extraction approach that is robust enough to handle free-form student input. We describe an evaluation of CIRCSIM-Tutor by forty-two students at Rush Medical College, with particular emphasis on the performance of the input understander. |
| Keywords and phrases: natural language understanding, intelligent tutoring system, information extraction, finite state parsing. |
| Communicated by Shun-Feng Su |
| Number of Downloads: 382 | Number of Views: 367 |
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