The Role of Initiative in Tutorial Dialogue

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 [markcl jmoorelzinn] @inf . ed. ac .uk Abstract This work is the first systematic inves- tigation of initiative in human-human tutorial dialogue. We studied initia- tive management in two dialogue strate- gies: didactic tutoring and Socratic tu- toring. We hypothesized that didactic tutoring would be mostly tutor-initiative while Socratic tutoring would be mixed- initiative, and that more student initia- tive would lead to more learning (i.e., task success for the tutor). Surpris- ingly, students had initiative more of the time in the didactic dialogues (21% of the turns) than in the Socratic dia- logues (10% of the turns), and there was no direct relationship between student initiative and learning. However, So- cratic 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 tuto- rial dialogue systems are largely system-initiative; only the system asks questions, and for each ques- tion, system designers build a database of poten- tial correct and incorrect answers, and a set of re- sponses to deal with the incorrect answers. There has been a similar trend in the spoken di- alogue 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 intel- ligent mixed-initiative dialogue system (MIMIC) outperformed a comparable system-initiative di- alogue system in terms of user satisfaction and task efficiency. MIMIC could back off to system- initiative mode when necessary but otherwise op- erate in mixed-initiative mode. The cognitive science literature indicates that such a breakthrough is also needed in the tutor- ing community. The current system-initiative ap- proaches conflict with arguments that it is the highly collaborative nature of human-human tutor- ing dialogue that leads to learning (Merrill et al., 1992a; Fox, 1993; Graesser et al., 1995). Through this dialogue, tutors can intervene to ensure that errors are detected and repaired and that students can work around impasses (Merrill et al., 1992b). Previous research has also shown that students must be allowed to construct knowledge them- selves to learn most effectively (Chi et al., 1989; Chi et al., 1994; VanLehn et al., 1998). The con- sensus from these studies is that experienced tutors maintain a delicate balance allowing students to do as much of the work as possible and to maintain a feeling of control, while providing students with enough guidance to keep them from becoming too frustrated or …

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