学习分析技术在教学中的应用研究

Application Research on Teaching Improvement Based on Learning Analysis Technology

探讨了如何利用学习分析技术促进教学改进。在数字化学习环境中,教师通过对学生学习过程的跟踪,记录其学习行为的数据;利用相关分析方法确定变量,利用聚类分析方法将学生划分为被动型、游离型、事倍功半型、学有余力型,并针对不同类别学生的知识图谱和问卷调查结果安排教学进度和侧重点;用回归分析建立模型,进行成绩预测并识别困难学生;最后针对不同类型学生采用不同策略进行干预,提高了学业成绩的合格率。

This paper discusses how to improve teaching with the techniques of learning analysis. Based on the students’ learning process in the digital learning environment,the teacher records the students’ learning behavior data,uses the method of correlation analysis to determine the variables of performance. By using the method of cluster analysis,the students are clustered into passive type,instable type,less effective,capable type,and the teaching progress and focus are arranged according to the knowledge map and questionnaire results of different categories of students. Regression analysis is used to predict and identify students who have difficulties to learn. According to different types of students the teacher adopts different strategies to intervene. Passing rate of the examination is greatly improved.