Personalized SCORM learning experience based on rating scale model

Abstract

Sharable Content Object Reference Model (SCORM) is the most popular suite of technical standard among existing international standards for e-Learning; although it has been designed to provide accessibility, adaptability, interoperability, and reusability, it still suffers from lack of personalization, which may lead to inappropriate learning experience; In other words, learner may suffer from distraction or restriction, when it comes to interact with large or restricted amounts of information respectively, resulting in reduced learning efficiency and performance. However, this can be avoided by providing personalized services. In this paper, we propose a personalized SCORM learning experience based on Rating Scale Model (RSM), which takes into account both the difficulty of learning activity and the learner's ability considering responses from individual learner's understanding and characteristics. To obtain more accurate estimation of learner's ability, polytomous Item Response Model (IRT) is used rather than dichotomous IRT. Experimental results show that the proposed system can exactly provide the closer learning resource to the learner's ability, resulting in increased the learning efficiency and learning performance. © 2009 Springer Berlin Heidelberg.