Generating Tutorial Feedback with Affect

Johanna Moore, Kaska Porayska-Pomsta, Sebastian Varges

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

Abstract

Studies aimed at understanding what makes human tutoring effective have noted that the type of indirect guidance that characterizes human tutorial dialogue is a key factor. In this paper, we describe an approach that brings together sociolingusitic research on the basis of linguistic choice with natural language generation technology to systematically produce tutorial feedback appropriate to the given situation.
Original languageEnglish
Title of host publicationProceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference
PublisherAAAI Press
Pages923-928
Number of pages6
ISBN (Print)1-57735-201-7
Publication statusPublished - 2004

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