疫情下学生在线学习过程指标与学习效果分析——以微机原理及单片机技术课程为例

Analysis of Students’Online Learning Process Indicators and Learning Effects During the Epidemic——Taking the Course“Microcomputer Principle and Single Chip Microcomputer Technology”as An Example

随着互联网与在线教育的兴起,教育与大数据关系越来越密切。学习过程数据分析可为评价学生学习效果提供依据,据此提出基于学习过程的指标评价方法。对超星“学习通”平台上的学习行为数据进行分析,发现学业表现、学习过程投入程度与学习质量正相关;根据学业表现和学习过程投入正相关指标对学生进行聚类,利用其均值进行比较,分析得出不同类型学生的学习效果,并给出不同类型(学习效果)学生的学习行为特点及教学建议。通过分析不同学生的学习习惯,为教师在线授课提供多方位指导,为以数据为驱动的在线及混合式教学改革提供参考。

At present,the evaluation of student learning effect is generally judged by student performance.With the rise of the Internet and online education,education and big data are becoming more and more closely related.Analyzing student learning process indicators in education data can provide new ways to evaluate student learning effects.A method to evaluate students’learning effect based on students’learning process indicators is proposed.By analyzing the learning behavior data of students on the Superstar“Learning Tong”platform,it is found that academic performance and the degree of input in the learning process are positively correlated with the learning quality of students;then students are clustered according to the positive correlation indicators of academic performance and learning process input,use the mean values are compared,analyze the learning effects of different typesof students,and give different types of students’learning behavior characteristics and teaching suggestions.By analysis,we find different learning habits of students,and provide teachers with multi-faceted guidance for online teaching.The research in this article provides ideas for online and hybrid teaching reform driven by data.