In this paper a knowledge representation approach of an adaptive and/or personalized tutoring system is\npresented. The domain knowledge should be represented in a more realistic way in order to allow the adaptive\nand/or personalized tutoring system to deliver the learning material to each individual learner dynamically taking\ninto account her/his learning needs and her/his different learning pace. To succeed this, the domain knowledge\nrepresentation has to depict the possible increase or decrease of the learner�s knowledge. Considering that the\ndomain concepts that constitute the learning material are not independent from each other, the knowledge\nrepresentation approach has to allow the system to recognize either the domain concepts that are already partly or\ncompletely known for a learner, or the domain concepts that s/he has forgotten, taking into account the learner�s\nknowledge level of the related concepts. In other words, the system should be informed about the knowledge\ndependencies that exist among the domain concepts of the learning material, as well as the strength on impact of\neach domain concept on others. Fuzzy Cognitive Maps (FCMs) seem to be an ideal way for representing graphically\nthis kind of information. The suggested knowledge representation approach has been implemented in an\ne-learning adaptive system for teaching computer programming. The particular system was used by the students of\na postgraduate program in the field of Informatics in the University of Piraeus and was compared with a\ncorresponding system, in which the domain knowledge was represented using the most common used technique\nof network of concepts. The results of the evaluation were very encouraging.
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