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Pedagogical Ontology Modelling for Cell Biology Domain With an Algorithm for Question Generation
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Author(s): Gerard Deepak (National Institute of Technology, Tiruchirappalli, India), Ayush Kumar (National Institute of Technology, Tiruchirappalli, India), Santhanavijayan A. (National Institute of Technology, Tiruchirappalli, India), Pushpa C. N. (University Visvesvaraya College of Enginnering, Bangalore University, India), Thriveni J. (University Visvesvaraya College of Enginnering, Bangalore University, India)and Venugopal K. R. (Bangalore University, India)
Copyright: 2021
Pages: 25
Source title:
Machine Learning Approaches for Improvising Modern Learning Systems
Source Author(s)/Editor(s): Zameer Gulzar (BSAR Crescent Institute of Science and Technology, India)and A. Anny Leema (Vellore Institute of Technology (VIT), Vellore, India)
DOI: 10.4018/978-1-7998-5009-0.ch006
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Abstract
In this chapter, an ontology that structures all the cell organelles and their parts are modelled to cognitively model domain knowledge by explicitly establishing relationships among them. The ontologies are modelled depicting the cell as a system and the parts of the cell as the subclasses of the cell along with various functionalities and behavior. The model further focuses on education pedagogy to generate questions based on the modelled ontologies. Furthermore, the defined ontologies are made consistent by defining the classes and the relationship between them, initializing the instances and axiomatizing the developed ontological content. The modelled ontologies are semiotically evaluated using various learners and domain experts. An overall reuse ratio of 0.91 has been achieved, and the proposed ontology has been differentiated from the existing cell ontologies by focusing on an educational pedagogy. Ultimately, an ontology-focused algorithm for multiple choice question generation has been proposed for cell biology as a domain of choice with an accuracy of 90.03%.
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