OntoCIP - an ontology of comprehensive integrative puzzle assessment method suitable for automatic question generation

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Abstract

Application of the Comprehensive Integrative Puzzle (CIP) assessment method is novel in medical education. Because of its high discriminatory quality, its application in medical education increases. However, creating a CIP question can be very labor intensive and time consuming while a team of experts is needed. On the other hand, Semantic web and ontologies have proven their usefulness in fine-grain knowledge management and reasoning. This paper describes a concrete development of ontology for Comprehensive Integrative Puzzle assessment method, called OntoCIP. This ontology supports automatic question generation that will reduce workload for teachers as well as engage domain experts while keeping feasibility, reliability, and validity of CIP assessment method. Conducted evaluation of OntoCIP shows that it is suitable for the purpose.

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Radovic, M., Tosic, M., Milosevic, D., & Jankovic, D. (2018). OntoCIP - an ontology of comprehensive integrative puzzle assessment method suitable for automatic question generation. In Advances in Intelligent Systems and Computing (Vol. 716, pp. 394–399). Springer Verlag. https://doi.org/10.1007/978-3-319-73204-6_44

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