Model for Enhanced Data Management, Visualization, and Adaptation in e-learning

Abstract

This paper describes the model for semantic annotation of educational materials and related concepts, as well as the structure of dependent services that extend the functionalities of current learning management systems (LMS). The goal of the model is to enable simple discovery, while allowing formulation and execu- tion of advanced search queries, augmented with visualizations of result sets and domain structure and adaptation of results according to students' interests. Several components were also implemented and their descriptions and other remarks are given following the description of the model. In modern educational systems, the final outcome of the learning process heavily depends on providing learn- ers with an access to the right information at the right time. An appropriate presentation and visualization of information can strongly influence the learning experience by allowing learners to explore an educational do- main instinctively, gaining a better insight into its structure. The main goal of this paper is to enhance data man- agement, visualization, and adaptation within an e-learning system. A model for semantic annotation of concepts present in learning management systems is presented, including the description of a structure of se- mantic applications that will utilize annotated resources to enhance data handling, browsing, searching, vi- sualization, and adaptivity. The developed solution is based around the principles of modularity and independency among components.