Flexible, Dynamic and Improved Intelligent Tutoring Systems (ITSs)

Now day's online learning is very common and fast growing industries worldwide in different institutions. This paper presents novel approach for optimized ITSs. We proposed methodology and algorithms for designing efficient deployment, interoperability and ontology extraction of ITSs framework. There are three main contributions in this research work. First, proposed an efficient open framework for ITSs which can solves the limitations related to interoperability issues. Proposed solution is not requiring the resources like databases; hence the restriction on interoperability learning objects is removed. This approach overcomes the limitations of external resources dependencies. Secondly, proposed method for automatic ontology generation using fuzzy ontology algorithm in order save efforts of end users those are required to analyze the large number of messages in ITS of big universities or organizations. Finally, proposed the improved automatic fuzzy ontology extraction method by using relevance feedback technique. In this paper, we presented the algorithms, architecture and results achieved for each contribution. The results are compared with existing methods and claimed that proposed methods are efficient for ITSs.