智慧教育背景下基于大数据的学生成绩预测模型

Student Achievement Prediction Model Based on Big Data in the Context of Intelligent Education

针对教师对学生升学成绩预测难度较大的问题,笔者提出智慧教育背景下基于大数据的学生成绩预测模型。该模型以数据关联原则为理论依据,以对学生成绩有直接关联的数据为预测数据,用牛顿插值法扩充数据,并利用Aprior算法对预处理后的数据进行特征提取,形成与数据特征相关的数据项,最后运用神经网络算法预测学生成绩。经实验证明,本模型能准确预测学生的升学成绩。

Aiming at the difficulty of teachers’prediction of students’progress in higher education,this paper proposes a student achievement prediction model based on big data in the context of wisdom education.Based on the principle of data association,the data directly related to student achievement is the forecast data.The Newton interpolation method is used to expand the data,and the Aprior algorithm is used to extract the features of the preprocessed data to form data items related to the data features.Neural network algorithms predict student achievement.The experiment proves that the model can accurately predict the student’s academic performance.