Simulating Human Tutor Dialog Moves in AutoTutor

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)
Type de document :
Article dans une revue
International Journal of Artificial Intelligence in Education (IJAIED), 2003, 12, pp.23-39
Liste complète des métadonnées

Littérature citée [34 références]  Voir  Masquer  Télécharger

https://telearn.archives-ouvertes.fr/hal-00197320
Contributeur : Jerome Zeiliger <>
Soumis le : vendredi 14 décembre 2007 - 14:59:18
Dernière modification le : vendredi 27 mars 2015 - 14:57:27
Document(s) archivé(s) le : lundi 12 avril 2010 - 07:46:19

Fichier

person01.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00197320, version 1

Collections

Citation

Natalie K. Person, Arthur C. Graesser, Roger J. Kreuz, Victoria Pomeroy. Simulating Human Tutor Dialog Moves in AutoTutor. International Journal of Artificial Intelligence in Education (IJAIED), 2003, 12, pp.23-39. 〈hal-00197320〉

Partager

Métriques

Consultations de la notice

337

Téléchargements de fichiers

367