An Approach of Optimizing Learner Model for Personalized Distance Learning/Training

The construction of learner model is one of the important aspects when designing personalized distance learning/training system. Most of which usually take the cognitive aspects of the learning into account only, for examples, show the right content, correct mistakes and provide explanations. However, besides cognition, learning strategies are increasingly recognized as the important aspect for personalized learning/training, and correlate with learner´s individual differences, which include personality traits, learning styles and conceptions etc. In this paper, the relationships between learners´ individual differences and learning strategies are investigated by using two different methods - the rough set theory based method and the correlation analysis method to analyze the same data set and compare the results. At last, some conclusions are made. The results help to construct an optimized learner model in a personalized distance learning/training environment.