article

AutoTutor: A simulation of a human tutor

Authors:

Arthur C Graesser,

Katja Wiemer-Hastings,

Peter Wiemer-Hastings,

Roger KreuzAuthors Info & Claims

Cognitive Systems Research, Volume 1, Issue 1

Pages 35 - 51

https://doi.org/10.1016/S1389-0417(99)00005-4

Published: 01 December 1999 Publication History

Abstract

AutoTutor is a computer tutor that simulates the discourse patterns and pedagogical strategies of a typical human tutor. AutoTutor is designed to assist college students in learning the fundamentals of hardware, operating systems, and the Internet in an introductory computer literacy course. Most tutors in school systems are not highly trained in tutoring techniques and have only a modest expertise on the tutoring topic, but they are surprisingly effective in producing learning gains in students. We have dissected the discourse and pedagogical strategies these unskilled tutors exhibit by analyzing approximately 100 hours of naturalistic tutoring sessions. These mechanisms are implemented in AutoTutor. AutoTutor presents questions and problems from a curriculum script, attempts to comprehend learner contributions that are entered by keyboard, formulates dialog moves that are sensitive to the learner's contributions (such as short feedback, pumps, prompts, elaborations, corrections, and hints), and delivers the dialog moves with a talking head. AutoTutor has seven modules: a curriculum script, language extraction, speech act classification, latent semantic analysis, topic selection, dialog move generation, and a talking head.

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Index Terms

AutoTutor: A simulation of a human tutor
1. Applied computing
  1. Education
2. Hardware
  1. Power and energy
    1. Power estimation and optimization
      1. Platform power issues

Index terms have been assigned to the content through auto-classification.

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cover image Cognitive Systems Research

Cognitive Systems Research Volume 1, Issue 1

December, 1999

59 pages

ISSN:1389-0417

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Copyright © Elsevier Science B.V. © 1999.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 1999

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https://dl.acm.org/doi/10.1145/3613904.3642867
Jell LList CKipp M(2023)Towards Automated Interactive Tutoring - Focussing on Misconceptions and Adaptive Level-Specific FeedbackProceedings of the 5th European Conference on Software Engineering Education10.1145/3593663.3593692(226-235)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3593663.3593692
Putnikovic MJovanovic J(2023)Embeddings for Automatic Short Answer Grading: A Scoping ReviewIEEE Transactions on Learning Technologies10.1109/TLT.2023.325307116:2(219-231)Online publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1109/TLT.2023.3253071
Albornoz-De Luise RArevalillo-Herráez MArnau D(2023)On Using Conversational Frameworks to Support Natural Language Interaction in Intelligent Tutoring SystemsIEEE Transactions on Learning Technologies10.1109/TLT.2023.324512116:5(722-735)Online publication date: 1-Oct-2023
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