What Makes Human Explanations Effective?

Johanna D. Moore

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publication Proceedings of the fifteenth annual meeting of the Cognitive Science Society
PublisherLawrence Erlbaum Associates
Pages131–136
Number of pages7
ISBN (Print)0-8058-1487-6
Publication statusPublished - Jun 1993

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