An adaptive E-learning portal for DSP learning

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.