Intelligent tutoring systems with conversational dialogue

Arthur C. Graesser, Kurt VanLehn, Carolyn P. Rosé, Pamela W. Jordan, Derek Harter

Research output: Contribution to journalArticlepeer-review

279 Scopus citations


Many of the intelligent tutoring systems that have been developed during the last 20 years have proven to be quite successful, particularly in the domains of mathematics, science, and technology. They produce significant learning gains beyond classroom environments. They are capable of engaging most students' attention and interest for hours. We have been working on a new generation of intelligent tutoring systems that hold mixed-initiative conversational dialogues with the learner. The tutoring systems present challenging problems and questions to the learner, the learner types in answers in English, and there is a lengthy multiturn dialogue as complete solutions or answers evolve. This article presents the tutoring systems that we have been developing. AUTO TUTOR is a conversational agent, with a taking head, that helps college students learn about computer literacy. ANDES, ATLAS, and WHY2 help adults learn about physics. Instead of being mere information-delivery systems, our systems help students actively construct knowledge through conversations.

Original languageEnglish (US)
Pages (from-to)39-51
Number of pages13
JournalAI Magazine
Issue number4
StatePublished - Dec 2001
Externally publishedYes

ASJC Scopus subject areas

  • Artificial Intelligence


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