International Journal of Information Technology & Computer Science ( IJITCS )
This paper describes an Adaptive Courseware Tutor – an intelligent tutoring system based on stereotypes, Bayesian networks and Bloom's knowledge taxonomy. The main feature of our approach is the automatization of learning object generation and courseware adaptivity in every stage of learning and teaching process. The student module is enhanced by double stereotypes based on student's knowledge level and on Bloom's knowledge taxonomy, as well as, by Bayesian networks. The tutor module is responsible for the automatic generation of courseware elements, their dynamic selection and sorting, as well as their adaptive presentation using templates for statements and questions. In order to evaluate the model’s effectiveness, a controlled experiment with a large sample was conducted..
:Intelligent tutoring systems, adaptive e-learning systems, adaptive courseware, stereotypes, Bloom's knowledge taxonomy
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