LMS, databases of learning objects, are used by teachers to store, search, and retrieve learning objects. Classification of these learning objects is a tedious job. Metadata standards are available in order to specify a learning object; however, a taxonomic path is normally left for the developer of the application to decide. A common taxonomic path consists of various domains and sub-domains in the form of a hierarchy. Annotators decide to place a particular learning object in a specified domain but this is a time consuming and laborious work. Automatic and intelligent classification of these learning objects in their respective domain is a great challenge. Each learning object has a pedagogical content and that content can be measured by various techniques. In this paper, we will try to find Information Content in a learning object and classifying it using intra-terms co-occurrences and their frequencies. By using this inverse co-occurrence factor and calculated information content, an intelligent and automatic classification of learning objects can be achieved by tagging it as positive or negative for a particular domain.
Imran Ihsan
