动态学生模型与智能教学系统研究

Research into the Dynamic Student Module and Intelligent Tutoring System

从分析当前网络学习系统中存在的适应性和个性化方面的严重缺陷出发,在开发实践项目的基础上,探讨了智能教学系统中利用模糊评价算法和神经网络等关键技术提取远程学习者的行为数据和绩效信息等参数,评价并建立动态学生模型库的方法,并对学生学习特征分类,根据不同的特征提供不同的教学策略与教学内容.最后,介绍了一个基于这种学生模型的智能网络教学系统.

From analyzing the existing serious defects in the current e-learning system in the areas of adoptability and individualization,based on empirical data collected during the tutoring system development,this paper discusses the use of key technologies such as fuzzy evaluation method and neural network in Intelligent Tutoring System(ITS) to obtain distance e-learners' behavioral and performance data.The establishment and evaluation of the dynamic student model are studied and different teaching strategies and course contents are used for various students with different learning characteristics.Finally,an ITS based on the proposed student model is outlined.