Abstract
This paper presents automated expert modeling for automated student evaluation, or AEMASE (pronounced “amaze”). This technique grades students by comparing their actions to a model of expert behavior. The expert model is constructed with machine learning techniques, avoiding the costly and time-consuming process of manual knowledge elicitation and expert system implementation. A brief summary of after action review (AAR) and intelligent tutoring systems (ITS) provides background for a prototype AAR application with a learning expert model. A validation experiment confirms that the prototype accurately grades student behavior on a tactical aircraft maneuver application. Finally, several topics for further research are proposed.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Centre, C.A.L.L.: The after action review process, learning more from our training. Army Lessons Learned Centre Dispatches 6(3) (1999)
DeGrosky, M.T.: Improving after action review (aar) practice. In: Eighth International Wildland Fire Safety Summit. (2005)
Meliza, L.: After action review: Methods and tools (2004) (retrieved on December 2, 2005), http://www.hqda.army.mil/ari/news/factsheets.shtml
Jensen, R., Nolan, M., Chen, D.Y.: Automatic causal explanation analysis for combined arms training aar. In: Proceedings of the Industry/Interservice, Training, Simulation and Education Conference (I/ITSEC) (2005)
Cohen, P.A., Kulik, J.A., Kulik, C.C.: Educational outcomes of tutoring: A meta-analysis of findings. American Educational Research Journal 19, 237–248 (1982)
Corbett, A.T.: Cognitive computer tutors: Solving the two- sigma problem. In: Bauer, M., Gmytrasiewicz, P.J., Vassileva, J. (eds.) UM 2001. LNCS, vol. 2109, pp. 137–147. Springer, Heidelberg (2001)
Burns, H., Capps, C.: Foundations of intelligent tutoring systems: An introduction. In: Polson, M.C., Richardson, J.J. (eds.) Foundations of Intelligent Tutoring Systems, pp. 1–18. Lawrence Erlbaum Associates Publishers, Mahwah (1988)
Murray, T.: Authoring intelligent tutoring systems: An analysis of the state of the art. International Journal of Artificial Intelligence in Education 10, 98–129 (1999)
Welch, G., Foxlin, E.: Motion tracking: no silver bullet, but a respectable arsenal. IEEE Computer Graphics and Applications 22(6), 24–38 (2002)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1992)
Srinivasa, N., Ahuja, N.: A topological and temporal correlator network for spatiotemporal pattern learning, recognition and recall. IEEE Transactions on Neural Networks 10(2), 356–371 (1999)
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer, Heidelberg (2001)
Sutton, R., Barto, A.: 3.5 The Markov Property. In: Reinforcement Learning, pp. 61–65. MIT Press, Cambridge (1998)
Kornecki, A., Hilburn, T., Diefenbach, T., Towhidnajad, M.: Intelligent tutoring issues for atc training system. IEEE Transactions on Control Systems Technology 1(3), 204–211 (1993)
Hess, S.M., MacMillan, J., Sefarty, D., Elliot, L.: From cognitive task analysis to simulation: Developing a synthetic team task for awacs weapons directors, Air Force Research Laboratory (1999)
Kohavi, R.: A study of cross-validation and bootstrap for accuracy estimation and model selection. In: IJCAI, pp. 1137–1145 (1995)
Zweig, C.: Receiver-operating characteristic (roc) plots: a fundamental evaluation tool in clinical medicine. Clin. Chem. 39(4), 561–577 (1993)
Ali, K., Langley, P., Maloof, M., Sage, S., Binford, T.: Improving rooftop detection with interactive visual learning. In: Proceedings of the Image Understanding Workshop, pp. 479–492. Morgan Kaufmann, San Francisco (1998)
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
Abbott, R.G. (2006). Automated Expert Modeling for Automated Student Evaluation. 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_1
Download citation
DOI: https://doi.org/10.1007/11774303_1
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)