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. To identify these properties we replaced the natural language component of an existing Intelligent Tutoring System ITS with a human tutor and gathered protocols of students interacting with the human tutor We then compared the human tutors responses to those that would have been produced by the ITS In this paper I describe two critical features that distinguish human tutorial explanations from those of their computational counterparts
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the fifteenth annual meeting of the Cognitive Science Society |
| Publisher | Lawrence Erlbaum Associates |
| Pages | 131–136 |
| Number of pages | 7 |
| ISBN (Print) | 0-8058-1487-6 |
| Publication status | Published - Jun 1993 |