Learner's tailoring e-Learning system on the item revision difficulty using PetriNet

Abstract

E-learning models are attempts to develop frameworks to address the concerns of the learner and the challenges presented by the technology so that online learning can take place effectively. So it usually used the item difficulty of item analysis method. But item guessing factor in learning results has to be considered to apply the relative item difficulty more precisely. So, for e-Learning system support to learner considering learning grade, it need item revision difficulty which considered item guessing factor. In this paper, I designed and embodied the learner's tailoring e-learning system on the item revision difficulty. For an efficient design, I use PetriNet and UML modeling. In building this system, I am able to support a variety of learning step choice to learners so that the learner can work in a flexible learning environment. © Springer-Verlag Berlin Heidelberg 2006.