神经网络模型在大学生在线学习预测中的应用研究  

Application of Neural Network Model in College Students'Online Learning Prediction

作　　者：叶梓 何国荣[1] 牛甲[1] YE Zi;HE Guo-rong;NIU Jia(Yangling Vocational and Technical College,Yangling 712100 China)

机构地区：[1]杨凌职业技术学院,陕西杨凌712100

出　　处：《自动化技术与应用》2024年第4期173-176,共4页Techniques of Automation and Applications

基　　金：2022年度陕西省职业技术教育学会一般研究课题(2022SZX365)。

摘　　要：为了较为准确地预测大学生在线学习效果,提出一套基于神经网络的学生在线学习行为分析模型。首先介绍该模型的输入项、输出项、数据处理方法以及整体拓扑结构。利用学生日常学习行为数据对神经网络模型进行训练,并通过该模型对学生的期末考试成绩进行预测。实验研究发现,所提出的神经网络模型在学生学习效果预测方面体现出了较为理想的准确度水平,具有一定的应用价值。In order to accurately predict the effect of college students'online learning,this study proposes a set of student online learning behavior analysis model based on neural network,and introduces the input items,output items,data processing methods and overall topology of the model in detail.The neural network model is trained by using students'daily learning behavior data,and the final examination scores of students are predicted by the model.Through the experimental research,it is found that the neural network model proposed in this study reflects an ideal accuracy level in the prediction of students'learning effect,and has a certain application value.

关 键 词：学习预测 神经网络模型 算法设计 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]