Ioannis Hatzilygeroudis

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In this paper, we present the architecture and describe the functionality of an Intelligent Tutoring System (ITS), which uses an expert system to make decisions during the teaching process. The expert system uses neurules for knowledge representation of the pedagogical knowledge. Neurules are a type of hybrid rules integrating symbolic rules with(More)
In this paper, we present the architecture and describe the functionality of a Web-based Intelligent Tutoring System (ITS), which uses neurules for knowledge representation. Neurules are a type of hybrid rules integrating symbolic rules with neurocomputing. The use of neurules as the knowledge representation basis of the ITS results in a number of(More)
In this paper, we first present and compare existing categorization schemes for neuro-symbolic approaches. We then stress the point that not all hybrid neuro-symbolic approaches can be accommodated by existing categories. Such a case is rule-based neuro-symbolic approaches that propose a unified knowledge representation scheme suitable for use in expert(More)
In this paper, we make a first effort to define requirements for knowledge representation (KR) in an ITS. The requirements concern all stages of an ITS’s life cycle (construction, operation and maintenance), all types of users (experts, engineers, learners) and all its modules (domain knowledge, user model, pedagogical model). We also briefly present and(More)
In this paper, we present an approach that integrates symbolic rules, neural networks and cases. To achieve it, we integrate a kind of hybrid rules, called neurules, with cases. Neurules integrate symbolic rules with the Adaline neural unit. In the integration, neurules are used to index cases representing their exceptions. In this way, the accuracy of the(More)
In this paper, we present a web-based intelligent education system to help students in the context of an AI course. We concentrate on the adaptivity and student evaluation aspects of the system. Adaptivity refers to the capability of the system to adapt teaching to student needs, specified by the student model characteristics. Student evaluation refers to(More)