Automatic Generation of Contents Models for Digital Learning Materials

Abstract

There has been much research that demonstrates the effectiveness of using ontology to support the construction of knowledge during the learning process. However, the widespread adoption in classrooms of such methods are impeded by the amount of time and effort that is required to create and maintain an ontology by a domain expert. In this paper, we propose a method to automatically generate a contents model by analyzing learning materials with the aim of supporting the construction of knowledge structures. A map of the keyword nodes is constructed by applying text mining techniques to find the important words and phrases and their relations contained within the learning materials. The process retains links between the nodes and the original learning materials, and it is therefore possible to recommend and rank sections that cover a concept contained within the contents model map.