An Inference Network Model for Retrieving Reusable Learning Objects

Reusing learning materials is an essential issue in developing e-learning content. For this purpose, the concept of Reusable Learning Objects (RLOs) has been developed by different organizations, and recently RLOs' metadata has been standardized to push up their reusability to its extent. In this paper, we focus on our vision of RLOs that have standard metadata and are stored in repositories. To enable advanced retrieval and browsing operations on RLOs' repositories, we have developed the LORIN model. This new model is based essentially on an Inference Network Retrieval model which is applied generally in Information Retrieval applications. LORIN model has been implemented and tested on a repository of learning objects that we have developed for pre-university curricula.