Inspectable Bayesian student modelling servers in multi-agent tutoring systems

International Journal of Human Computer Studies

Volumn 61, Issue 4, 2004, Pages 535-563

  Zapata Rivera, Juan Diego ^a   Greer, Jim ^a  

^a UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SUPPORTED COOPERATIVE WORK; DATABASE SYSTEMS; EDUCATION; HUMAN COMPUTER INTERACTION; INTERACTIVE COMPUTER SYSTEMS; JAVA PROGRAMMING LANGUAGE; SERVERS; STUDENTS;

BAYESIAN INFERENCE; INFORMATION SHARING; MULTI-AGENT TUTORING SYSTEMS;

MULTI AGENT SYSTEMS;

EID: 4344624984     PISSN: 10715819     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijhcs.2003.12.017     Document Type: Article

References (45)

1. Agarwal P., Solheim J., Winter M., Zapata J.D. JTS. a java tutoring system:2000;Aries Lab Technical Report, University of Saskatchewan.
2. Brajnik, R.J., Tasso, C., 1992. A flexible tool for developing user modeling applications with non-monotonic reasoning capabilities. Proceedings of the third International Workshop on User Modeling, Dagstuhl, Germany, pp. 42-66.
3. Bull, S., Shurville, S., 1999. Cooperative writer modelling: facilitating reader-based writing with scrawl, In: Proceedings of the workshop 'Open, Interactive, and other Overt Approaches to Learner Modelling' at AIED'99.
4. Collins J.A., Greer J.E., Huang S.X. Adaptive assessment using granularity hierarchies and Bayesian nets. Frason C., Gauthier G., Lesgold A. Proceedings of the Third International Conference on Intelligent Tutoring Systems ITS'96. 1996;569-577 Springer, Berlin.
5. Conati, C., VanLehn, K., 1996. POLA: a student modeling framework for probabilistic on-line assessment of problem solving performance. In: Proceedings of the Fifth International Conference on User Modeling, Kailua-Kona, HI.
6. Conati C., Gertner A.S., VanLehn K. Using Bayesian networks to manage uncertainty in student modeling. In User Modeling and User-Adapted Interaction. 12:2002;371-417.
7. Cozman, F., 1998. JavaBayes Bayesian networks in Java. Available on-line: http://www.cs.cmu.edu/~Javabayes/.
8. Dimitrova, V., Self, J., Brna, P., 1999. STyLE-OLM - an interactive diagnosis tool in a terminology learning environment. In: Proceedings of the workshop 'Open, Interactive, and other Overt Approaches to Learner Modelling' at AIED'99.
9. Finin T. GUMS - a general user modeling shell. Kobsa A., Wahlster W. User Modeling in Dialog Systems. 1989;411-430 Springer, Berlin, Heidelberg.
10. Finin T., Labrou Y., Mayfield J. KQML as an agent communication language. Bradshaw J. 'Software Agents'. 1997;MIT Press, Cambridge.
11. Fink J. Implications from transaction management for adaptive and user modelling systems. Proceedings of the Seventh User Modelling Conference UM'99. 1999;191-200 Springer, Wien, New York.
12. Gertner A., VanLehn K. Andes. a coached problem solving environment for physics Gauthier G., Frasson C., VanLehn K. Proceedings of the Fifth International Conference on Intelligent Tutoring Systems. 2000;133-142 Springer, Berlin.
13. Greer, J., McCalla, G., 1989. A Computational Framework for Granularity and its Application to Educational Diagnosis. IJCAI, Detroit, pp. 477-482.
14. Greer, J., Zapata, J.D., Ong-Scutchings, C., Cooke, J.E., 1999. Visualization of Bayesian learner models. In: Proceedings of the workshop 'Open, Interactive, and other Overt Approaches to Learner Modelling' at AIED'99. pp. 6-10.
15. Huang X., McCalla G., Greer J., Neufeld E. Revising deductive knowledge and stereotypical knowledge in a student model. User Modeling and User-Adapted Interaction. 1(1):1991;87-116.
16. Jameson A. Numerical uncertainty management in user and student modeling. an overview of systems and issues User Modeling and User-Adaptive Interaction (Special Issue on Numerical Uncertainty Management in User and Student Modeling). 5(3):1996;193-251.
17. Kay J. The UM toolkit for cooperative user modeling. User Modeling and User-Adaptive Interaction (Special Issue on User Modeling Shell Systems). 4(3):1995;149-196.
18. Kay, J., 1998. A scrutable user modelling shell for user-adapted interaction. Ph.D. Thesis, Basser Department of Computer Science, University of Sydney, Sydney, Australia.
19. Kobsa A. Generic user modeling systems. User Modeling and User Adapted Interaction. 11:2001;49-63.
20. Kobsa A. Tailoring privacy to users' needs (invited keynote). Bauer M., Gmytrasiewicz P.J., Vassileva J. User Modeling 2001: Eighth International Conference UM2001. 2001;303-313 Springer, Berlin, Heidelberg.
21. Kobsa A., Orwant J. Heterogeneous learning in the Doppelganger user modeling system. User Modeling and User-Adaptive Interaction (Special Issue on User Modeling Shell Systems). 4(2):1995;107-130.
22. Kobsa A., Pohl W. The user modelling shell system BGP-MS. User Modelling and User Adapted Interaction. 4(2):1995;59-106.
23. Kono Y., Ikeda M., Mizoguchi R. THEMIS. A nonmonotonic inductive student modeling system Journal of Artificial Intelligence in Education. 5(3):1994;371-413.
24. Machado I., Martins A., Paiva A. One for all and all in one. A learner modelling server in a multi-agent platform. Kay J. Proceedings of the Seventh International Conference UM99. 1999;211-221 Springer, Wien, New York.
25. Mayo, M., 2001. Bayesian student modelling and decition-theoretic selection of tutorial actions in intelligent tutoring systems. Ph.D. Thesis, Department of Computer Science. University of Canterbury, New Zealand.
26. Mislevy R.J., Gitomer D.H. The role of probability-based inference in an intelligent tutoring system. User Modeling and User-Adaptive Interaction (Special Issue on Numerical Uncertainty Management in User and Student Modeling). 5(3):1996;253-282.
27. Müehlenbrock M., Tewissen F., Hoppe H.U. A framework system for intelligent support in open distributed learning environments. International Journal of Artificial Intelligence in Education. 9:1998;256-274.
28. Murray, W.R., 1999. An easily implemented, linear-time algorithm for Bayesian student modeling in multi-level trees. Proceedings of the Ninth International Conference of Artificial Intelligence in Education, pp. 413-420.
29. Orwant, J., 1991. The Doppeldanger user modeling system. In: Proceedings of the IJCAI workshop: Agent Modelling for Intelligent Interaction, Sydney, Australia, pp. 164-168.
30. Paiva A., Self J. TAGUS - a user and learner modeling workbench. User Modelling and User Adapted Interaction. 4(3):1995;197-228.
31. Paiva, A., Self, J., Hartley, R., 1995. Externalising learner models. Proceedings of World Conference on Artificial Intelligence in Education, Washington, DC, pp. 509-516.
32. PAPI Learner Standard, 2000. IEEE 1484.2: Learner Model Working Group. Learning Technology Standards Committee (LTSC). Available on line at: http://ltsc.ieee.org/wg2/.
33. Pearl J. Probabilistic Reasoning in Intelligent Systems. Networks of Plausible Inference:1988;Morgan Kaufmann, San Mateo, CA.
34. Reye J. A Belief Net Backbone for student modelling. Frasson C., Gauthier C., Lesgold A. Intelligent Tutoring Systems, ITS'96, Montreal, Canada. 1996;596-604 Sringer, Berlin.
35. Reye J. Two-phase updating of student models based on dynamic belief networks. Goettl B.P., Halff H.M., Redfield C.L., Shute V.J. 4th International Conference on Intelligent Tutoring Systems, ITS '98. 1998;274-283 Springer-Verlag.
36. Shafer G. A Mathematical Theory of Evidence. 1976;Princeton University Press, Princeton, NJ.
37. Stern M., Beck J., Wollf B. Naïve Bayes Classifiers for User Modeling. 1999;Center for Knowledge Communication, Computer Science Department, University of Massachusetts.
38. VanLehn K., Martin J. Evaluation on an assessment system based on Bayesian student modeling. International Journal of Artificial Intelligence and Education. 8:1997;179-221.
39. Vassileva, J., Greer J., McCalla, G., Deters, R., Zapata, D., Mudgal, C., Grant, S., 1999. A multi-agent approach to the design of peer-help environments. In: Proceedings of Artificial Intelligence in Education AIED'99, Le Mans, France, July 1999, pp. 38-45.
40. Vergara, H., 1994. PROTUM: a prolog based tool for user modeling. WIS Memo 10, WG Knowledge-based Information Systems, Department of Information Science University of Konstanz, Germany.
41. Villano M. Probabilistic student models. Bayesian belief networks and knowledge space theory Frasson C., Gauthier C., McCalla G. Intelligent Tutoring Systems ITS'92 Montreal, Canada. 1992;491-498 Springer, Berlin.
42. Zadeh, L., 1973. Outline of a new approach to the analysis of complex systems. IEEE Transactions on Systems, Man and Cybernetics SMC-3, 28-44.
43. Zapata-Rivera, J.D., 2003. Learning environments based on inspectable student models. Ph.D. Thesis, Department of Computer Science, University of Saskatchewan.
44. Zapata-Rivera J.D., Greer J. Inspecting and visualizing distributed bayesian student models. Gauthier G., Frasson C., Vanlehn K. Intelligent Tutoring Systems ITS 2000, Montreal, Canada. 2000;544-553 Springer, Berlin.
45. Zapata-Rivera, J.D., Greer, J., 2003. Student model accuracy using inspectable Bayesian student models. International Conference on Artificial Intelligence in Education AIED 2003, pp. 65-72.