基于贝叶斯网络的自适应学生模型的研究

首先介绍了贝叶斯网络的基础理论，贝叶斯网络是目前不确定知识表达和推理领域最有效的理论模型之一。适用于不确定性和概率性的知识表达和推理。接着介绍了自适应学生模型的概念和理论，然后运用贝叶斯网络构建了一个自适应性学生模型，并对贝叶斯网络学生模型的知识表达方法进行了研究，最后举例说明这个理论的可行性。基于贝叶斯网络构建的适应性学生模型能够有效地提供适应性的网络教学资源，从而有助于实现网络教学平台的适应性学习。

The research of adaptive student model on Bayesian networks

This study first introduced the Bayesian networks, basic theory of Bayesian network is now one of the most effective theory models in uncertainty knowledge expression and the inference field, and applies to uncer- tainty, probability knowledge. Using the Bagesian networks the adaptive student model concept and the theory, was introduad and then an adaptive student module was construhed by using the Bayesian network. The knowl- edge representation methods for student model of Bayesian networks was studied. Finally, an example was intru- luced to illustrate the feasibility of this theory. Based on the Bayesian networks, adaptive students model can ef- fectively provide adaptive network teaching resouwes which can contribute to the realization of adaptive learning in the network teading platform.