Stereotype Student Model for an Adaptive e-Learning System
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.
[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. Ríos, "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.
[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. Ríos, "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.
@article{"International Journal of Information, Control and Computer Sciences:62610", author = "Ani Grubišić and Slavomir Stankov and Branko Žitko", title = "Stereotype Student Model for an Adaptive e-Learning System", 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.", volume = "7", number = "4", pages = "505-8", }
