Edu-ACoCM: Automatic Co-existing Concept Mining from Educational Content

Introduction

The traditional colleges and libraries are being supported by learning management systems and online learning material repositories. Students themselves choose the subject of study, corresponding learning material and the studying path. In such a scenario where there is no physical tutor, the learning management system can help the student in choosing an appropriate topic to study, learning materials and learning path. After an extensive study of learning materials on different subjects the authors have identified that, each learning concept possess different roles when used in different context. Figure 1 shows the classification of learning concepts based on their significant role in a learning material.

Figure 1.

Keyword taxonomy

The concepts listed in Figure 1 co-exist with each other in a learning material. The presence of co-existing concepts in a learning material can be identified using content specific patterns. Separate patterns exist for the occurrences of definitions, prerequisites, subsequent topics, features and comparable concepts. The learning concepts, its co-existing concepts and patterns to identify co-existing concepts can be found in the same sentence or consecutive sentences. This paper proposes the application of Rule based algorithms on these patterns to automatically identify and extract definition concepts, prerequisites, features, subsequent topics and comparative concepts.