Clustering of Content Supporting Computer Mediated Courseware Development

TL;DR

This paper proposes a data mining-based clustering method to develop generalized computer mediated courseware from multiple textbooks, enabling dynamic content allocation across various courses.

Contribution

It introduces a novel clustering approach for combining multiple textbooks into a hierarchical structure for courseware development.

Findings

Successfully applied to database courses at different levels.

Creates a generalized content structure adaptable to various courses.

Facilitates dynamic content allocation for courseware development.

Abstract

Computer Mediated Courseware (CMC) has been developed so far for individual courses considering single or multiple text books. A group of courseware can be developed by using multiple text books and in this case, it is a requirement to cluster the contents of different books to form a generalized clustered content. No work has been found to develop courseware applying generalized clustered content. We have proposed a clustering of content supporting computer mediated courseware development based on data mining techniques to construct a hierarchical general structure of a group of courseware combining the individual structure of a set of books. The clustering will help the courseware developer to dynamically allocate contents to develop different courses using a group of books. The authors have applied this methodology for different level of courses on database. The methodology is generalized and can be applied to any other courses.