Knowledge environment for personalizing e-learning

In this research, we attempt to realize the learning personalization aspect of e-learning. Through an elaborate process of (1) eliciting what the learner wants to learn, (2) eliciting the learner’s prior expertise in that domain of interest, (3) dynamically assembling a learning course that starts off from the learner’s prior knowledge and (4) personalizing the learning instructions according to the learner’s constraints and learning preferences, we propose a systematic methodology and mathematical model to provide learning personalization. Besides providing a learning personalization methodology, we also devise a pedagogical content development methodology. This pedagogical methodology, designed in collaboration with a pedagogy expert from the National Institute of Education, Singapore, lays the pedagogical foundation for structuring, designing, developing, and implementing the e-learning resources. Using our developed Goal Driven Learning Model, we show how the learner’s needs can be characterized into goals. Based on the learning goals, the model determines what parts of prior knowledge are to be presented, in what sequence, and how the delivering of the desired knowledge can be supported.DOCTOR OF PHILOSOPHY (EEE