Application of Bayesian Network Learning Methods in E-learning

E-learning is becoming one of the most important educational means. As more and more organizations and institutions are moving towards the e-learning strategy, self-learning model becomes a big challenge. Background knowledge and learning objectives of various groups of students on the network are very different. Self-learning system, which uses different learning programs for different students, can enhance the efficiency of learning process. In a self-learning system, the algorithm dealing with uncertainty factors of Self-learning model is very important. Bayesian network artifice is a very effective one within various methods dealing with uncertainty. In this paper, we applied Bayesian network method to self-learning model; designed Bayesian network structure in a self-learning model; assigned the local probability distribution and discussed the way to acquire and propagate related evidences. The practice has proven Bayesian network approach for self-learning model is a very effective method.