基于隐马尔可夫模型的智能教学研究  

Research on intelligent teaching based on Hidden Markov Model

作　　者：朱忠旭[1] ZHU Zhongxu(Department of Computer and Information Engineering,AnHui Industry and Trade Vocational College,Huainan232007,Anhui,China)

机构地区：[1]安徽工贸职业技术学院计算机信息工程系,安徽淮南232007

出　　处：《安顺学院学报》2021年第2期106-110,共5页Journal of Anshun University

基　　金：安徽省高校自然科学研究重点项目“贝叶斯网络在大学生就业能力培养中的应用研究”(KJ2019A1054);安徽省重大线上教学改革研究项目“‘互联网+教育’背景下线上线下深度融合的研究与实践——以《Java web应用开发》为例”(2020zdxsjg036)。

摘　　要：研究了将一个改进的隐马尔可夫模型应用于在线教学平台智能化的方法。将学习资源作为状态变量,学习时间作为输入观察,测试成绩作为输出观察,对学生每一次上线学习涉及的学习对象、时间投入和学习收获等要素的关系建模。根据学生的学习特点为其推荐适合的学习资源,使其可以用较少时间取得较好的学习效果。通过对比由模型推断得到的学习数据与实际学习记录数据,验证了模型的有效性。The method of applying an improved hidden Markov model to the intelligence of online teaching platform is studied.The learning resources are taken as the state variables,the learning time as the input observation,and the test results as the output observation.The relationship between the learning objects,the time input and the learning harvest involved in each online learning is modeled.According to the students'learning history,it is recommended that students can use less time to achieve better results for each learning activity.The validity of the model is verified by comparing the student's achievement with the actual academic achievement.

关 键 词：隐马尔可夫模型 智能教学 学习资源推荐 知识追踪 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]