International Journal of Artificial Intelligence in Education (2001), 12, 23-39

Simulating Human Tutor Dialog Moves in AutoTutor

Natalie K. Person, Department of Psychology, Rhodes College, 2000 N. Parkway, Memphis, TN 38112
Person@rhodes.edu

Arthur C. Graesser, Roger J. Kreuz, Victoria Pomeroy, and the Tutoring Research Group Department of Psychology, University of Memphis, Memphis, TN 38152
a-graesser@memphis.edu, kreuzrj@memphis.edu, vpomeroy@memphis.edu

Abstract. This purpose of this paper is to show how prevalent features of successful human tutoring interactions can be integrated into a pedagogical agent, AutoTutor. AutoTutor is a fully automated computer tutor that responds to learner input by simulating the dialog moves of effective, normal human tutors. AutoTutor's delivery of dialog moves is organized within a 5-step framework that is unique to normal human tutoring interactions. We assessed AutoTutor's performance as an effective tutor and conversational partner during tutoring sessions with virtual students of varying ability levels. Results from three evaluation cycles indicate the following: (1) AutoTutor is capable of delivering pedagogically effective dialog moves that mimic the dialog move choices of human tutors, and (2) AutoTutor is a reasonably effective conversational partner.

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