基于综合评价模型的大学生学业成绩测量与预测

Measurement and Prediction of College Students’ Academic Achievements Based on Comprehensive Evaluation Model

定量地了解学生的日常行为、身心健康和学业成绩之间的关系是迈向个性化教育的重要一步。与先前基于问卷调查的研究相比,笔者收集了某高校理学院800名本科生的校园一卡通和综合素质测评表的数据,选取12个影响因素进行主成分分析,提取了学习勤奋度、饮食规律性和身心健康3个特征并与学业成绩建立非线性回归模型。同时,利用得到的非线性回归模型对学业成绩进行预测。基于这些分析,教育管理者可以在必要时实施针对性的干预以帮助学生提高学业成绩。

Quantitative understanding of the relationship between students’daily behavior,physical and mental health and academic performance is an important step towards personalized education.Comparing with the previous research based on questionnaire survey,the author collects the data of 800 Undergraduates’campus card and comprehensive quality evaluation form in a college of science,chooses 12 influencing factors for principal component analysis,extracts three characteristics of study diligence,dietary regularity and physical and mental health,and establishes a non-linear regression with academic achievement.Regression model.At the same time,the obtained non-linear regression model is used to predict academic performance.Based on these analyses,education managers can implement targeted interventions when necessary to help students improve their academic performance.