A knowledge-driven model to personalize e-learning

Abstract

This article highlights basic issues that have hindered e-learning systems from becoming the revolutionary force it could be for education. While current systems aim to foster significant improvements in learning, this article argues that most systems are still limited to just being online repositories. This and the lack of learning personalization has become a topic for research. A knowledge-driven model to personalize e-learning is proposed in this article. A novel methodology for eliciting and personalizing tacit knowledge is presented. We focus on describing the complex information processing in terms of knowledge, rather than the details of its implementation.