Towards an ontology-based system for intelligent prediction of student dropouts in distance education
by Dimitris Kanellopoulos, Sotiris Kotsiantis
International Journal of Management in Education (IJMIE), Vol. 2, No. 2, 2008

Abstract: The objective of this work was to design an intelligent web portal to serve as a service provider for predicting which students of the Hellenic Open University (HOU) are dropout-prone students; i.e., such students indirectly generate 'Student Dropout Statements' (SDSs). These statements are generated if a combination of events occurs; for example, a student is not computer literate, he/she is absent from his/her first face-to-face consulting meeting with the tutor, and/or he/she has failed in the first written assignment. The portal has been conceived to help tutors to detect dropout-prone students. The information contained in the portal is related to 'Formal Students Statements' (FSSs) such as class records or the student registry of the HOU. The portal helps tutors to find students with a high probability of dropping out. For this purpose, the knowledge of the student domain has been represented by means of an ontology, which has been used to guide the design of the application and to supply the system with semantic capabilities. The reasoning engine of the system executes logic rules related with well-established student attributes, which characterise a student as dropout-prone or not.

Online publication date: Mon, 19-May-2008

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