Intelligent Learning System Based on Tutoring Agent and VR Training Agent (TAVTA)
PROCEEDINGS
Joung S. Sung, Baekseok College, Korea (South) ; Doo H. Lim, University of Tennessee, United States
EdMedia + Innovate Learning, in Montreal, Canada ISBN 978-1-880094-56-3 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Abstract
This paper describes the Intelligent Learning System (ILS) comprising a set of two main agents: Tutoring Agent and VR Training Agent (TAVTA). The two agents have knowledge base (KB) providing elicited tutoring, training history, and knowledge to retrieve elements from a problem solving KB. The Tutoring Agent is composed of several sub agents that provide interactive and cooperative functions within the learning system. The agent deduces correct answers to test questions and provide intelligent feedbacks and hints to the learner. The VR Training Agent includes diagnosis module responsible for diagnosing learners' practice process. In a synchronous mode Training Agent controls audio, video, and, chatting functions of an on-line question and answer session.
Citation
Sung, J.S. & Lim, D.H. (2005). Intelligent Learning System Based on Tutoring Agent and VR Training Agent (TAVTA). In P. Kommers & G. Richards (Eds.), Proceedings of ED-MEDIA 2005--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 1415-1420). Montreal, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved March 28, 2024 from https://www.learntechlib.org/primary/p/20277/.
© 2005 Association for the Advancement of Computing in Education (AACE)
Keywords
References
View References & Citations Map- Aleven, V., McLaren, B.M., Roll, I., and Koedinger, K. (2004). Toward Tutoring Help Seeking: Applying Cognitive Modeling to Meta-Cognitive Skills. Proc. Of Intelligent Tutoring Systems (ITS), 2004.
- Gaby, N., & Dietrich, Z. (1996). Intelligent Methods to Evaluate Solutions of Interactive Calculation Exercises and ModelBased Experiments in Logistics Education. Proceedings of ED-MEDIA, Educational Multimedia and Hypermedia,1996, pp. 521-526.
- Henda, C., & Mohamed, J. (2004). PERSO: Towards an adaptive e-Learning System. International Journal of Interactive Learning Research, 2004, 15(4), p p 433-447.
- Mitrovic, A., & Ohlsson, S. (1999). Evaluation of Constraint-based tutor for a database language. International Journal on AIED, 1999, 10(3-4), pp. 238-256.
- Ritter, S. (1997). Communication, Cooperation, and Competition among Multiple Tutor Agents, In B. Boulay& R. Mizoguchi (Eds.) Artificial Intelligence in Education (pp. 31-38), IOS Press.
- Teresita, L., & Raymund, S. (2003). Learner Agents as Student Modeling: Design and Analysis, 2003, IEEE International Conference on Advanced Learning Technologies.
- Yiying, Z., Lei G., & Nicolas, D. (2000). AGILE: An Architecture for Agent-Based Collaboration and Interactive Virtual Environments.
These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.
Suggest Corrections to References