Article

Intelligent user interface design for teachable agent systems

Authors:

B. Bodenheimer,

J. BransfordAuthors Info & Claims

IUI '03: Proceedings of the 8th international conference on Intelligent user interfaces

Pages 26 - 33

https://doi.org/10.1145/604045.604054

Published: 12 January 2003 Publication History

Abstract

This paper describes the interface components for a system called Bettys Brain, an intelligent agent we have developed for studying the learning by teaching paradigm. Our previous studies have shown that students gain better understanding of domain knowledge when they prepare to teach others versus when they prepare to take an exam. This finding has motivated us to develop computer agents that students teach using concept map representations with a visual interface. Betty is intelligent not because she learns on her own, but because she can apply qualitative-reasoning techniques to answer questions that are directly related to what she has been taught through the concept map. We evaluate the agents interfaces in terms of how well they support learning activities, using examples of their use by fifth grade students in an extensive study that we performed in a Nashville public school. A critical analysis of the outcome of our studies has led us to propose the next generation interfaces in a multi-agent paradigm that should be more effective in promoting constructivist learning and self-regulation in the learning by teaching framework

References

[1]

Bargh, J.A. and Schul, Y. On the cognitive benefits of teaching. Journal of Educational Psychology, 72 (5). 593--604.

[2]

Baylor, A. and Ryu, J. Effects of image and animation on agent persona. Journal of Educational Computing Research.

[3]

Biswas, G., Schwartz, D., Bransford, J. and The Teachable Agents Group at Vanderbilt University. Technology Support for Complex Problem Solving: From SAD Environments to AI. in Forbus and Feltovich eds. Smart Machines in Education, AAAI Press, Menlo Park, CA, 2001, 71--98.

Digital Library

[4]

Chi, M.T.H., Siler, S.A., Jeong, H., Yamauchi, T. and Hausmann, R.G. Learning from Human Tutoring. Cognitive Science, 25 (4). 471--533.

[5]

Cole, R., Massaro, D.W., Rundle, B., Shobaki, K., Wouters, J., Cohen, M., Beskow, J., Stone, P., Connors, P., Tarachow, A. and Solcher, D., New tools for interactive speech and language training: Using animated conversational agents in the classrooms of profoundly deaf children. in Proceedings of ESCA/SOCRATES Workshop on Method and Tool Innovations for Speech Science Education, (April 1999).

[6]

Graesser, A., Wiemer-Hastings, K., Wiemer-Hastings, P. and Kreuz, R. Autotutor: A simulation of a human tutor. Journal of Cognitive Systems Research, 1. 35--51.

Digital Library

[7]

Graesser, A.C., Person, N. and Magliano, J. Collaborative dialog patterns in naturalistic one-on-one tutoring. Applied Cognitive Psychologist, 9. 359--387.

[8]

Johnson, W.L., Rickel, J.W. and Lester, J.C. Animated pedagogical agents: Face-to-face interaction in interactive learning environmen. International Journal of Artificial Intelligence in Education, 11. 47--78.

[9]

Leelawong, K., Davis, J., Vye, N., Biswas, G., Schwartz, D., Belynne, K., Klatzberger, T. and Bransford, J., The Effects of Feedback in Supporting Learning by Teaching in a Teachable Agent Environment. in The Fifth International Conference of the Learning Sciences, (Seattle, Washington, 2002).

[10]

Leelawong, K., Wang, Y., Biswas, G., Vye, N. and Bransford, J., Qualitative reasoning techniques to support learning by teaching: The Teachable Agents project. in The Fifteenth International Workshop on Qualitative Reasoning, (San Antonio, Texas, 2001), AAAI Press, 109--116.

[11]

National Research Council How People Learn. National Academy Press, Washington, D.C., 2000.

[12]

Novak, J.D. Concept Mapping as a tool for improving science teaching and learning. in Treagust, D.F., Duit, R. and Fraser, B.J. eds. Improving Teaching and Learning in Science and Mathematics, Teachers College Press, London, 1996, 32--43.

[13]

Reeves, B. and Nass, C. The Media Equation: How people treat computers, televisons and new media like real people and places. Cambridge University Press, Cambridge, 1996.

Digital Library

[14]

Schwartz, D.L. and Bransford, J.D. A Time for Telling. Cognition and Instruction, 16 (4). 475--522.

[15]

Stoyanov, S. and Kommers, P. Agent-Support for Problem Solving Through Concept-Mapping. Journal of Interactive Learning Research, 10 (3/4). 401-442.

Digital Library

Cited By

Vidmanov DAlfimtsev A(2024)Intelligent Analysis of the User Interface of Mobile Applications to Search for Functions and Services2024 6th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)10.1109/REEPE60449.2024.10479774(1-5)Online publication date: 29-Feb-2024
https://doi.org/10.1109/REEPE60449.2024.10479774
Bringula RBasa RDela Cruz CRodrigo M(2015)Effects of Prior Knowledge in Mathematics on Learner-Interface Interactions in a Learning-by-Teaching Intelligent Tutoring SystemJournal of Educational Computing Research10.1177/073563311562221354:4(462-482)Online publication date: 24-Dec-2015
https://doi.org/10.1177/0735633115622213
Jimenez FKanoh M(2013)Robot That Can Promote Learning by Observing in Collaborative LearningProceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics10.1109/SMC.2013.394(2304-2309)Online publication date: 13-Oct-2013
https://dl.acm.org/doi/10.1109/SMC.2013.394
Show More Cited By

Recommendations

Designing Learning by Teaching Agents: The Betty's Brain System

The idea that teaching others is a powerful way to learn is intuitively compelling and supported in the research literature. We have developed computer-based, domain-independent Teachable Agents that students can teach using a visual representation. The ...
What and How You Explain Matters: Inquisitive Teachable Agent Scaffolds Knowledge-Building for Tutor Learning
Artificial Intelligence in Education
Abstract
Students learn by teaching a teachable agent, a phenomenon called tutor learning. Literature suggests that tutor learning happens when students (who tutor the teachable agent) actively reflect on their knowledge when responding to the teachable ...
Intelligent user interface design for teachable agent systems
IUI '03: Proceedings of the 8th international conference on Intelligent user interfaces

Bettys Brain [1] is a learning-by-teaching environment where students "teach" Betty by constructing a concept map that models relations between domain concepts. The relations can be causal, hierarchical, and property links between the entities that ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

IUI '03: Proceedings of the 8th international conference on Intelligent user interfaces

January 2003

344 pages

ISBN:1581135866

DOI:10.1145/604045

Conference Chair:
David Leake
Indiana University
,
Program Chairs:
Lewis Johnson
USC/Information Sciences Institute
,
Elisabeth Andre
University of Augsburg

Copyright © 2003 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 January 2003

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

IUI03

Sponsor:

IUI03: Eighth International Conference on Intelligent User Interfaces

January 12 - 15, 2003

Florida, Miami, USA

Acceptance Rates

Overall Acceptance Rate 746 of 2,811 submissions, 27%

Upcoming Conference

IUI '25

Sponsor:
sigai
sigai

30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

Cagliari , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
1,334
Total Downloads

Downloads (Last 12 months)13
Downloads (Last 6 weeks)2

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Vidmanov DAlfimtsev A(2024)Intelligent Analysis of the User Interface of Mobile Applications to Search for Functions and Services2024 6th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)10.1109/REEPE60449.2024.10479774(1-5)Online publication date: 29-Feb-2024
https://doi.org/10.1109/REEPE60449.2024.10479774
Bringula RBasa RDela Cruz CRodrigo M(2015)Effects of Prior Knowledge in Mathematics on Learner-Interface Interactions in a Learning-by-Teaching Intelligent Tutoring SystemJournal of Educational Computing Research10.1177/073563311562221354:4(462-482)Online publication date: 24-Dec-2015
https://doi.org/10.1177/0735633115622213
Jimenez FKanoh M(2013)Robot That Can Promote Learning by Observing in Collaborative LearningProceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics10.1109/SMC.2013.394(2304-2309)Online publication date: 13-Oct-2013
https://dl.acm.org/doi/10.1109/SMC.2013.394
Leelawong KBiswas G(2008)Designing Learning by Teaching Agents: The Betty's Brain SystemInternational Journal of Artificial Intelligence in Education10.5555/1454278.145428018:3(181-208)Online publication date: 1-Aug-2008
https://dl.acm.org/doi/10.5555/1454278.1454280
AlRegib GHayes MMoore EWilliams D(2008)Technology and Tools to Enhance Distributed Engineering EducationProceedings of the IEEE10.1109/JPROC.2008.92161096:6(951-969)Online publication date: Jun-2008
https://doi.org/10.1109/JPROC.2008.921610
Ushida H(2006)Social behavior model for human-machine collaboration systemsProceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases10.5555/1364262.1364282(100-105)Online publication date: 15-Feb-2006
https://dl.acm.org/doi/10.5555/1364262.1364282
Williams BBelynne KBodenheimer B(2005)An evaluation of animation in a pedagogical agentACM SIGGRAPH 2005 Posters10.1145/1186954.1187052(86-es)Online publication date: 31-Jul-2005
https://dl.acm.org/doi/10.1145/1186954.1187052
Hartman KBlair Kvan der Veer GGale C(2005)The unless switchCHI '05 Extended Abstracts on Human Factors in Computing Systems10.1145/1056808.1056936(1439-1442)Online publication date: 2-Apr-2005
https://dl.acm.org/doi/10.1145/1056808.1056936
Rosé CTorrey C(2005)Interactivity and expectationProceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction10.1007/11555261_28(323-336)Online publication date: 12-Sep-2005
https://dl.acm.org/doi/10.1007/11555261_28
Davis JLeelawong KBelynne KBiswas GVye NBodenheimer RBransford JLeake DJohnson LAndre E(2003)Intelligent user interface design for teachable agent systemsProceedings of the 8th international conference on Intelligent user interfaces10.1145/604045.604113(320-320)Online publication date: 12-Jan-2003
https://dl.acm.org/doi/10.1145/604045.604113

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents