Abstract
In this paper we deal with the problem of enhancing the decision making abilities of broker agents in digital learning resources brokerage systems. Following a multi-criteria decision making approach, we provide broker agents with the means to qualitatively represent the user preferences and efficiently evaluate the proposed alternatives. Learner modelling and digital learning resources description parameters are inferred by a classic cognitive style modelling method, the Honey and Mumford model. We study two different aspects in modelling the learning resources recommendation problem: first formulated as a decision problem for the agent representing the learner by using a unique synthesis criterion approach; second, as a decision problem for the agent representing the content provider by using an approach based on the UTA method. Both aspects are studied in the context of a generic agent-based brokerage architecture, with broker agents requesting, describing and offering e-learning courses.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Beuthe, M. and Scannella, G. (2001). Comparative analysis of UTA multicriteria methods. European Journal of Operational Research, vol. 130.
Guttman, R., Moukas, A. and Maes, P. (1998). Agent-mediated Electronic Commerce: A Survey. Knowledge Engineering Review, vol. 13 (3).
Honey, P. and Mumford, A. (1992). The Manual of Learning Styles. 3rd Ed., Maidenhead, Peter Honey.
Jacquet-Lagreze, E. and Siskos, J. (1982). Assessing a set of additive utility functions for multicriteria decision-making: The UTA method. European Journal of Operational Research, vol. 10, 151–164.
Jacquet-Lagreze, E. and Siskos, Y. (2001). Preference disaggregation: 20 years of MCDA experience. European Journal of Operational Research, vol. 130, 233–245.
Jennings, N. R. (2001). An agent-based approach for building complex software systems. Communications of the ACM, vol. 44 (4), 35–41.
Maes, P., Guttman, R. and Moukas, A.. (1999). Agents that Buy and Sell: Transforming Commerce as We Know It. Communications of the ACM, vol. 42 (3), 81–91.
Manouselis N., and Sampson, D. (2003). Agent-based e-Learning Course Discovery and Recommendation: Matching Learner Characteristics with Content Attributes. International Journal of Computers and Applications (IJCA), vol. 25 (1).
Roy, B. (1996). Multicriteria Methodology for Decision Aiding. Kluwer Academic Publishers.
Sampson, D., and Karagiannidis, C. (2002). Accommodating Learning Styles in Adaptation Logics for Personalised Learning Systems, in Proc. ED-MEDIA 2002, Denver, Colorado, USA.
Tennant, N. (1988). Theories, Concepts and Rationality in an Evolutionary Account of Science. Biology and Philosophy, vol. 3, 224–231.
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
About this article
Cite this article
Manouselis, N., Sampson, D. Multi-criteria decision making for broker agents in elearning environments. Oper Res Int J 2, 347–361 (2002). https://doi.org/10.1007/BF02936390
Issue Date:
DOI: https://doi.org/10.1007/BF02936390