Abstract
Most of the intelligent tutoring system (ITS) is used to deliver knowledge and train skills based on the expert model. According to the theories of leaning, learning by teaching method is more efficient for enhancing motivation to learn and cognitive ability than learning by listening or learning by reading. For the purpose of developing an adaptive intelligent agent to enhance the motivation to learn, the new type of teachable agent were designed and implemented, the KORI (KORea university Intelligent agent), in which the user plays a role of a tutor by teaching the agent using a concept map, posing questions, and providing feedbacks. KORI consists of four independent modules: teach module, Q&A module, test module, and resource module. In teach module, the KORI’s knowledge is structured and organized through the concept map and the KORI makes new knowledge from the inference engine. In Q&A module, the KORI can provide answers to the users’ questions through an interactive window. It is expected that providing the user with the active role of teaching the agent enhance the motivation to learn and the positive attitude toward the subject matter as well as cognition.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Bargh, J.A., Schul, Y.: On the cognitive benefits of teaching. Journal of Educational Psychology 72, 593–604 (1980)
Chi, M.T.H., Siler, S.A., Jeong, H., Yamauchi, T., Hausmann, R.G.: Learning from human tutoring. Cognitive Science 25(4), 471–533 (2001)
Graesser, A.C., Person, N., Magliano, J.: Collaborative dialog patterns in naturalistic one-on-one tutoring. Applied Cognitive Psychologist 9, 359–387 (1995)
Biswas, G., Schwartz, D., Bransford, J., TAG-V: Technology support for complex problem solving: From SAD environments to AI. In: Forbus, Feltovich (eds.) Smart Machines in Education, pp. 71–98. AAAI Press, Menlo Park (2001)
Kim, S., Kim, W.S., Yoon, M.S., So, Y.H., Kwon, E.J., Choi, J.S., Kim, M.S., Lee, M.J., Park, T.J.: Understanding and Designing Teachable Agent. Journal of Korea Cognitive Science 14(3), 13–21 (2003)
Brophy, S., Biswas, G., Kaltzberger, T., Bransford, J., Schwartz, D.: Teachable agent: Combining insights from learning Theory and Computer Science, Vandervielt, LTC (1999)
Novak, J.D.: Concept mapping as a tool for improving science teaching and learning. In: Treagust, D.F., Duit, R., Fraser, B.J. (eds.) Improving Teachable and Learning in Sceince and Mathematics, pp. 32–43. Teachers College Press, London (1996)
Stoyanov, S., Kommers, P.: Agent-support for problem solving through conceptmapping. Journal of Interative Learning Research 10(3/4), 401–442 (1999)
Kim, S., Kwon, E.J., Yoon, M.S., So, Y.H., Kim, W.S., Lee, S.: The effects of types of concept map and science self-efficacy on interest and comprehension: A comparison of 4th and 5th graders. Korean Journal of Educational Psychology 18(4), 17–31 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kim, Si. et al. (2005). Design and Implementation of the KORI: Intelligent Teachable Agent and Its Application to Education. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424925_8
Download citation
DOI: https://doi.org/10.1007/11424925_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25863-6
Online ISBN: 978-3-540-32309-9
eBook Packages: Computer ScienceComputer Science (R0)