基于自我效能感的数学成绩的预测模型  

Prediction Models of Academic Performance in Math Based on the Self-Efficacy

作　　者：王志祥[1] 赵佩佩 张加明[3] 周友士[4] 

机构地区：[1]淮阴师范学院数学与统计学院,江苏 淮安 [2]新淮高级中学,江苏 淮安 [3]江苏省淮海中学,江苏 淮安 [4]淮阴师范学院教育科学学院,江苏 淮安

出　　处：《统计学与应用》2021年第4期706-713,共8页Statistical and Application

摘　　要：本文以淮安市淮海中学的实际调查数据为样本进行实证研究。基于数学学习自我效能感,本文给出了数学成绩的两个预测模型:线性回归模型和Logistic回归模型。结果表明,利用加权最小二乘法得到的线性回归模型具有较高的拟合优度;而Logistic回归模型对“优”、“良”、“差”有较高的预测正确率,对“中”的预测正确率最差。In this paper, an empirical study is conducted by taking samples from survey in Jiangsu Huaihai senior high school. Two prediction models of academic performance in math are obtained based on the self-efficacy, which are linear regression model and Logistic regression model. The results suggest that the linear regression model obtained by weighted least square method has high goodness of fit, and the Logistic regression model has a high prediction accuracy for “excellent”, “good” and “poor”, but has the lowest prediction accuracy for “medium”.

关 键 词：自我效能感 线性回归 LOGISTIC回归 实证研究 

分 类 号：G63[文化科学—教育学]