Content classification and Context-Based retrieval system for e-learning
AbstractA recent focus in web based learning systems has been the development of reusable learning materials that can be delivered as personalized courses depending of a number of factors such as the user's background, his/her learning preferences, current knowledge based on previous assessments, or previous browsing patterns. The student is often confronted with complex information mining tasks in which the semantics of individual sources require a deeper modelling than is offered by current learning systems. Most authored content exist in the form of videos, audio, slides, text, and simulations. In the absence of suitable annotations, the conversion of such materials for on-line distribution, presentation, and personalization has proven to be difficult. Based on our experiences with Open Courseware (OCW) and Singapore-MIT Alliance (SMA) video database, this paper presents a personalized delivery system that uses a domain ontology and pedagogical models to compose course materials in response to a users query. We also present several important E-learning applications emerging from the framework.