网络智能教学系统中双层学生模型的设计  

Design of Double-leveled Student Model in an Online Intelligent Tutoring System

作　　者：郝耀军[1] 王建国[1] 赵青杉[1] 

机构地区：[1]忻州师范学院计算机系

出　　处：《中国远程教育》2011年第23期64-67,96,共4页Chinese Journal of Distance Education

基　　金：山西省高等学校科技研究开发项目"基于虚拟人情绪的智能学习支持系统的研究与开发"(项目编号:20111124)基金资助

摘　　要：本文探讨了在网络智能教学系统中建立一个双层动态学生模型的方法,模型的初始层采用复合认知型学生模型,高级层利用Hopfield神经网络算法,在初始层数据的基础上加入兴趣、爱好、知识状态、学习历史等信息进行评价、分类。该模型克服了单一学生模型结构数据处理的障碍,能够灵活、全面地对学生的学习特征进行分析,有效改善了智能网络教学系统的教学决策过程。Student model in an online intelligent tutoring system(ITS) is the foundation for individualized teaching decision making,and a qualitative standard for learner customized teaching in adaptive tutoring.This study explores the methodology to construct a dynamic student model in an online ITS,consisting of a basic level and a higher level.The basic level deals mainly with students' cognitive abilities,while the higher level involves evaluation and classification of interests,hobbies,knowledge status,and education background of students.This new model can provide flexible and thorough analysis about students' characteristics,and improve the decision making system of ITS.This double-leveled model has been successfully experimented in the SQLlearning system.

关 键 词：学生模型 智能教学系统 HOPFIELD神经网络 

分 类 号：G434[文化科学—教育学]