Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo khoa học: "The Role of Initiative in Tutorial Dialogue"

This work is the first systematic investigation of initiative in human-human tutorial dialogue. We studied initiative management in two dialogue strategies: didactic tutoring and Socratic tutoring. We hypothesized that didactic tutoring would be mostly tutor-initiative while Socratic tutoring would be mixedinitiative, and that more student initiative would lead to more learning (i.e., task success for the tutor). Surprisingly, students had initiative more of the time in the didactic dialogues (21% of the turns) than in the Socratic dialogues (10% of the turns), and there was no direct relationship between student initiative and learning. . | The Role of Initiative in Tutorial Dialogue Mark G. Core and Johanna D. Moore and Claus Zinn School of Informatics University of Edinburgh 2 Buccleuch Place Edinburgh EH8 9LW UK markcị jmoore zinn @inf . ed .ac.uk Abstract This work is the first systematic investigation of initiative in human-human tutorial dialogue. We studied initiative management in two dialogue strategies didactic tutoring and Socratic tutoring. We hypothesized that didactic tutoring would be mostly tutor-initiative while Socratic tutoring would be mixed-initiative and that more student initiative would lead to more learning i.e. task success for the tutor . Surprisingly students had initiative more of the time in the didactic dialogues 21 of the turns than in the Socratic dialogues 10 of the turns and there was no direct relationship between student initiative and learning. However Socratic dialogues were more interactive than didactic dialogues as measured by percentage of tutor utterances that were questions and percentage of words in the dialogue uttered by the student and interactivity had a positive correlation with learning. 1 Introduction Tutorial dialogue systems face the unique problem that users students often do not know the answers to questions asked by the system and may produce wrong answers that are not in the system s domain model. Because of these difficulties current tutorial dialogue systems are largely system-initiative only the system asks questions and for each question system designers build a database of poten tial correct and incorrect answers and a set of responses to deal with the incorrect answers. There has been a similar trend in the spoken dialogue systems community. The problem in this case is poor speech recognition performance and the solution is for the system to ask questions with a limited set of answers. However Chu-Carroll and Nickerson 2000 showed that a suitably intelligent mixed-initiative dialogue system MIMIC outperformed a comparable .