Abstract
A major issue in Intelligent Tutoring Systems is off-task student behavior, especially performance-based gaming, where students systematically exploit tutor behavior in order to advance through a curriculum quickly and easily, with as little active thought directed at the educational content as possible. The goal of this research was to explore the phenomena of off-task gaming behavior within the Assistments system. Machine-learned gaming-detection models were developed to investigate underlying factors related to gaming, and an analysis of gaming within the Assistments system was conducted to compare some of the findings of prior studies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Koedinger, K.R., Anderson, J.R., Hadley, W.H., Mark, M.A.: Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education 8, 30–43 (1997)
Baker, R.S., Corbett, A.T., Koedinger, K.R.: Detecting student misuse of intelligent tutoring systems. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 531–540. Springer, Heidelberg (2004)
Baker, R.S., Corbett, A.T., Koedinger, K.R., Wagner, A.Z.: Off-Task Behavior in the Cognitive Tutor Classroom: When Students Game The System. In: Proceedings of ACM CHI 2004: Computer-Human Interaction (2004)
Razzaq, L., Feng, M., Nuzzo-Jones, G., Heffernan, N.T., et al.: The Assistment Project: Blending Assessment and Assisting. In: Proceedings of the 12th Annual Conference on Artificial Intelligence in Education, Amsterdam (2005)
Nuzzo-Jones, G., Walonoski, J.A., Heffernan, N.T., Livak, T.: The eXtensible Tutor Architecture: A New Foundation for ITS. In: Proceedings of the 12th Annual International Conference on Artificial Intelligence in Education, Amsterdam (2005)
Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
Cendrowska, J.: PRISM: An algorithm for inducing modular rules. International Journal of Man-Machine Studies 27(4), 349–370 (1987)
Quinlan, J.R.: C4. 5: Programs for Machine Learning. The Morgan Kaufmann Series in Machine Learning, San Mateo (1993)
Baker, R.S., Roll, I., Corbett, A.T., Koedinger, K.R.: Do Performance Goals Lead Students to Game the System? In: Proceedings of the 12th International Conference on Artificial Intelligence and Education, Amsterdam (2005)
Feng, M., Heffernan, N.T., Koedinger, K.R.: Addressing the Testing Challenge with a Web-Based E-Assessment System that Tutors as it Assesses. In: Proceedings of WWW 2006, Edinburgh, Scotland (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Walonoski, J.A., Heffernan, N.T. (2006). Detection and Analysis of Off-Task Gaming Behavior in Intelligent Tutoring Systems. In: Ikeda, M., Ashley, K.D., Chan, TW. (eds) Intelligent Tutoring Systems. ITS 2006. Lecture Notes in Computer Science, vol 4053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774303_38
Download citation
DOI: https://doi.org/10.1007/11774303_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35159-7
Online ISBN: 978-3-540-35160-3
eBook Packages: Computer ScienceComputer Science (R0)