Simulating Human Tutor Dialog Moves in AutoTutor
Year: 2003
Type: article
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. AutoTutorâs delivery of dialog moves is organized within a 5-step framework that is unique to normal human tutoring interactions. We assessed AutoTutorâs 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. (http://aied.inf.ed.ac.uk/members01/archive/vol_12/person/full.html)
Institutions: Rhodes College, University of Memphis
Language: French
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2125180619