Stereotype Student Model for an Adaptive e-Learning System

Authors: Ani Grubišić, Slavomir Stankov, Branko Žitko

Abstract:

This paper describes a concept of stereotype student model in adaptive knowledge acquisition e-learning system. Defined knowledge stereotypes are based on student's proficiency level and on Bloom's knowledge taxonomy. The teacher module is responsible for the whole adaptivity process: the automatic generation of courseware elements, their dynamic selection and sorting, as well as their adaptive presentation using templates for statements and questions. The adaptation of courseware is realized according to student-s knowledge stereotype.

Keywords: Adaptive e-learning systems, adaptive courseware, stereotypes, Bloom's knowledge taxonomy.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1081417

References:

[1] S. Stankov, A. Grubi┼íić, and B. Žitko, "E-learning paradigm & Intelligent tutoring systems," Annual 2004 of the Croatian Academy of Engineering, pp. 21-31, 2004.
[2] O. Park and J. Lee, "Adaptive instructional systems," Handbook of research for educational communications and technology, pp. 634-664, 1996.
[3] D. Benyon and D. Murray, "Adaptive systems: From intelligent tutoring to autonomous agents," Knowledge-Based Systems, vol. 6, no. 4, pp. 197-219, 1993.
[4] C. Ullrich, "Descriptive and Prescriptive Learning Theories," Pedagogically Founded Courseware Generation for Web-Based Learning, pp. 37-42, 2008.
[5] B. Bontchev and D. Vassileva, "Adaptive courseware design based on learner character", pp. 23-25. 2009
[6] F. Essalmi, L. J. B. Ayed, M. Jemni, Kinshuk, and S. Graf, "A fully personalization strategy of E-learning scenarios," Computers in Human Behavior, vol. 26(4), pp. 581-591, 2010.
[7] P. Brusilovsky, "Methods and Techniques of Adaptive Hypermedia," User Modeling and User Adapted Interaction, vol. 6, no. 2-3, pp. 87- 129, 1996.
[8] P. Mohan, J. Greer, and G. McCalla, "Instructional planning with learning objects," Knowledge Representation and Automated Reasoning for E-Learning Systems, pp. 52-58, 2003.
[9] B. S. Bloom, Taxonomy of educational objectives. The classification of educational goals, Handbook I Cognitive Domain. Green, New York, NY: Committee of College and University Examiners, Longmans, 1956.
[10] D. Sleeman and J. S. Brown, "Introduction: Intelligent Tutoring Systems: An Overview," in Intelligent Tutoring Systems, Sleeman, D.H., Brown, J.S., Academic Press, Burlington, MA, pp. 1-11., 1982.
[11] H. L. Burns and C. G. Capps, "Foundations of intelligent tutoring systems: An introduction," in Foundations of intelligent tutoring systems, M. C. Poison, J. J.Richardson (Ed.)., Lawrence Eribaum, London, pp. 1-19., 1988.
[12] J. W. Rickel, "Intelligent computer-aided instruction: A survey organized around system components," Systems, Man and Cybernetics, IEEE Transactions on Systems, Man, and Cybernetics, vol. 19, no. 1, pp. 40-57, 1989.
[13] B. Woolf, "AI in Education. Encyclopedia of Artificial Intelligence," New York, Wiley, pp. 434-444, 1992.
[14] J. Self, "Formal approaches to student modelling," Student modelling: The key to individualized knowledge-based instruction, vol. 25, 1994.
[15] A. Grubi┼íić, "Adaptive student-s knowledge acquisition model in elearning systems," PhD Thesis, University of Zagreb, Croatia, Faculty of Electrical Engineering and Computing, 2012.
[16] S. Stankov, "Isomorphic Model of the System as the Basis of Teaching Control Principles in an Intelligent Tutoring System," PhD Thesis, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Croatia (in Croatian), 1997.
[17] S. Stankov, M. Rosic, B. Zitko, and A. Grubisic, "TEx-Sys model for building intelligent tutoring systems," Computers & Education, vol. 51(3), pp. 1017-1036, 2008.
[18] A. Grubi┼íic, S. Stankov, and B. Žitko, "An approach to automatic evaluation of educational influence," in Proceedings of the 6th WSEAS International Conference on Distance Learning and Web Engineering, Stevens Point, Wisconsin, USA, pp. 20-25, 2006.
[19] A. Grubi┼íić, "Evaluating effectiveness of intelligent e-learning systems," Master-s thesis, Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia (in Croatian), 2007.
[20] A. Grubi┼íić, "A Meta-Analytic Estimation of a Common Effect Size from a Series of Experiments Related to an E-Learning System Effectiveness Evaluation," Intelligent Tutoring Systems in E-Learning Environments: Design, Implementation and Evaluation, p. 327, 2010.
[21] J. Cohen, Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates, 1988.
[22] A. M. Riad, H. K. El-Minir, and H. A. El-Ghareeb, "Review of e- Learning Systems Convergence from Traditional Systems to Services based Adaptive and Intelligent Systems," Journal of Convergence Information Technology, vol. 4, no. 2, 2009.
[23] E. Rich, "Users are individuals: individualizing user models," International journal of man-machine studies, vol. 18, no. 3, pp. 199- 214, 1983.
[24] I. Beumont and P. Brusilousky, "Adaptive Educational Hypermedia", pp. 93-98., 1995.
[25] E. H. Shortliffe, R. Davis, S. G. Axline, B. G. Buchanan, C. C. Green, and S. N. Cohen, "Computer-based consultations in clinical therapeutics: explanation and rule acquisition capabilities of the MYCIN system," Computers and Biomedical Research, vol. 8(4), pp. 303-320, 1975.
[26] E. Rich, "User modeling via stereotypes," Cognitive Science: A Multidisciplinary Journal, vol. 3(4), pp. 329-354, 1979.
[27] R. Wilensky, Y. Arens, and D. Chin, "Talking to UNIX in English: an overview of UC," Communications of the ACM, vol. 27, no. 6, pp. 574- 593, 1984.
[28] R. Wilensky, D. N. Chin, M. Luria, J. Martin, J. Mayfield, and D. Wu, "The Berkeley UNIX consultant project," Computational Linguistics, vol. 14(4), pp. 35-84, 1988.
[29] R. Glaser and A. J. Nitko, "Measurement in Learning and Instruction.," 1970.
[30] T. B. Lee, J. Hendler, and O. Lassila, "The semantic web," Scientific American, vol. 284, no. 5, pp. 34-43, 2001.
[31] R. Conejo, E. Guzm├ín, E. Mill├ín, M. Trella, J. L. Pérez-De-La-Cruz, and A. R├¡os, "Siette: a web-based tool for adaptive testing," International Journal of Artificial Intelligence in Education, vol. 14, no. 1, pp. 29-61, 2004.
[32] N. E. Gronlund, Measurement and Evaluation in Teaching, 5th Revised ed. New York: Macmillan Publishing Company, 1985.
[33] B.S., Bloom (1984) The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring. Educational Researcher, 13, pp. 4-16.