With the development of modern information technology,teaching data collection has covered the whole process of online and offline education.The establishment of modern teaching decision-making mode depends on whether the teaching data can be effectively mined and analyzed.The data in the paper iscollected from the online and offline teaching and learning of the course of Fundamental of Mechanical Engineering.Several data analysis methods,such as correlation coefficient analysis,principal component analysis and multiple linear regression methods are adopted to analyze the data.Through the analysis and research,the rationality of the test scores,the correlation and weight of the principal components that affect the test scores,and the prediction equation of academic performance are all obtained.Through the presented analysis methods,the information-based teaching and data analysis technique get effective integration.The study effectiveness analysis and diagnosis methods are preliminary established based on data mining in the paper.It provides basis and thinking for teaching improving and lays the foundation for setting up the data-driven teaching feedback mechanism and personalized teaching model.
correlation analysisprincipal component analysismultiple linear regressioninformation-basedteachingbigdata
国家科技期刊平台
NSTL
万方数据
维普
