智慧学习环境中基于贝叶斯网络构建学生模型的研究

Research on Structure of Student Model Based on Bayesian Network in Smart Learning Environment

智慧学习环境是当前教育技术学界的一个前沿研究领域,从C/S架构的智能学习系统发展到B/S架构的智能化网络学习环境,学生模型仍然是其最核心的功能模块,是学生自我导向式学习情境中构建智慧学习环境的关键因素.本文采用文献分析法和实践调研法,从学生模型的分类、数据结构和建模方法等几个方面,对国内智能网络学习环境中学生模型的研究现状进行了较为详细的研究,并通过梳理近年来关于静态学生模型和动态推理模型的研究,提出了智慧学习环境中基于贝叶斯网络构建学生模型的框架,期望为智能学习系统中学生模型的理论研究和实践发展提供可借鉴的参考和经验.

Smart learning environment is a frontier research field in educational technology. In the development of the intelligent learning system from C/S architecture to B/S architecture, student model is still the most core part in the web-based intelligent learning system. It is the key factor to build the self-regulated context in smart learning environment. In this paper, using literature analysis method, we research on the classification, data structure and modeling method of student model in China, marshal the static student model and the dynamic reasoning model. And then a framework of student model based on Bayesian network in smart learning environment is proposed.