Title

Tutorial dialogue modes in a large corpus of online tutoring transcripts

Abstract

Building on previous work in this area, we provide a description and justification for a new way of identifying modes and mode switches in tutorial dialogues, part of a coding scheme involving 16 modes and 125 distinct dialogue acts. We also present preliminary results from an analysis of 1,438 human-annotated transcripts, consisting of more than 90,000 turns. Among other findings, this analysis shows subtle differences in the “mode architecture” of successful vs. less successful sessions, as judged by expert tutors.

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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