Making Computer Tutors More Like Humans

Johanna D. Moore

Research output: Contribution to journalArticlepeer-review


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 languageEnglish
Pages (from-to)181-214
Number of pages34
JournalJournal of Artificial Intelligence in Education
Issue number2
Publication statusPublished - 1 Nov 1996

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