Ontological Representation and Analysis for Smart Education

A solid instructional design knowledge base is lacking in the majority of educational technology today, resulting in dubious instructional quality. The ability to modify these educational technologies for a variety of adaptable instructional designs is also a key problem. In the literature, ontology...

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Bibliographic Details
Published inApplications of Artificial Intelligence and Machine Learning Vol. 925; pp. 381 - 389
Main Authors Bhuyan, Bikram Pratim, Garg, Shelly
Format Book Chapter
LanguageEnglish
Published Singapore Springer 2022
Springer Nature Singapore
SeriesLecture Notes in Electrical Engineering
Subjects
Graph theory
Knowledge representation and reasoning
Lattice theory
Ontology
Smart education
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Summary:A solid instructional design knowledge base is lacking in the majority of educational technology today, resulting in dubious instructional quality. The ability to modify these educational technologies for a variety of adaptable instructional designs is also a key problem. In the literature, ontology’s are considered to be one of the most effective systems for representing instructional design. A flexible instruction design cannot be modelled using the present techniques. Our study proposes a knowledge-based ontological framework for grouping similar student traits, which is necessary for forming a smart educational framework. It is evident from the algorithms created and execution that the students have integrated the system. Lastly, a set of inference rules is constructed.
ISBN:9789811948305
9811948305
ISSN:1876-1100
1876-1119
DOI:10.1007/978-981-19-4831-2_31