An adaptive e-Learning portal for DSP learning

Abstract

This paper presents a novel adaptation mechanism taking student's preferences, knowledge and motivation states into account when it delivers the personalized learning materials to each learner through the customized interface. The adaptation is implemented with the help of a backend data mining engine and the Bayesian network technologies. To show the effectiveness of the proposed mechanism, an e-Learning portal, LearningVista, is constructed to support large classroom teaching. The initial feedback from students shows a positive sign in helping students to achieve better learning outcomes. ©2007 IEEE.