吉林大学学报(信息科学版) ›› 2021, Vol. 39 ›› Issue (4): 451-455.

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基于 BP 神经网络的高校学生成绩预测

姚明海, 李劲松, 王 娜
  

  1. 渤海大学 信息科学与技术学院, 辽宁 锦州 121013
  • 收稿日期:2020-12-30 出版日期:2021-07-24 发布日期:2021-08-07
  • 作者简介:姚明海(1980— ), 男, 辽宁锦州人, 渤海大学副教授, 博士, 主要从事模式识别与智能计算研究, (Tel)86-416-3400346 (E-mail)yao_ming_hai@ 163. com
  • 基金资助:
    辽宁省自然科学基金资助项目(2019-ZD-0503); 辽宁省教育厅科学技术基金资助项目(LJ2020003; WJ2020004); 渤海大学 教改立项基金资助项目(BDJGAY2019024)

Prediction of College Students' Performance Based on BP Neural Network

YAO Minghai, LI Jinsong, WANG Na   

  1. College of Information Science and Technology, Bohai University, Jinzhou 121013, China
  • Received:2020-12-30 Online:2021-07-24 Published:2021-08-07

摘要: 现有成绩预测研究多集中于如何构建预测模型, 但都忽略了预测时间的重要性。 针对此问题, 提出基于 BP(Back Propagation)神经网络方法构建大一成绩同最终毕业时的成绩预测模型, 旨在挖掘大一成绩同毕业成绩存在的潜在联系, 实现早指导早见效的原则。 通过对某高校信息与计算科学专业 2016 级学生成绩进行随机预测实验, 证明大一成绩同毕业成绩间具有潜在联系。 同时, 提出的基于 BP 神经网络的高校学生成绩预测模型具有良好的预测精度、 实用性和推广性, 可以成为提升教学质量的重要组成部分, 为实现人才培养的目标发挥更大的作用。

关键词: BP 神经网络,  , 成绩预测,  , OBE 教学模式,  , 教育数据挖掘

Abstract:  Existing performance prediction research focuses on how to build prediction model, ignoring the importance of prediction time. In order to solve this problem, a prediction model based on BP ( Back Propagation) neural network is proposed to find out the potential relationship between freshmen's grades and graduation grades and realize the principle of early guidance and early effect. Through a random prediction experiment on the grades of 2016 students majoring in information and computing science in a university, it is proved that there is a potential relationship between freshman scores and graduation scores. The proposed prediction model has excellent prediction accuracy and good practicability and popularization, which can become an important part of improving teaching quality and play a greater role in realizing the goal of talent training.

Key words: back propagation (BP) neural network, performance prediction, outcomes-based education (OBE) teaching model, educational data mining

中图分类号: 

  • TP183