Abstract
If computer-based instructional systems are to reap the benefits of natural language interaction,they must be endowed with the properties that make human natural language interaction so effective. In this paper, I describe several features that distinguish human tutorial explanations from those produced by today's computer-based tutors. I argue that in order to build systems capable of structuring explanations naturally and appropriately interpreting and generating context-sensitive utterances, it is necessary to model and reason about the plans the speakers in a discourse are attempting to carry out. I then present a plan-based approach to natural language generation, and provide examples from several implemented systems that illustrate how the approach enables systems to participate effectively in natural language dialogues with their users.
| Original language | English |
|---|---|
| Pages (from-to) | 181-214 |
| Number of pages | 34 |
| Journal | Journal of Artificial Intelligence in Education |
| Volume | 7 |
| Issue number | 2 |
| Publication status | Published - 1 Nov 1996 |