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’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.