[1]任占广,尚福华.基于行为分析的在线课程成绩预测模型[J].计算机技术与发展,2019,29(11):139-143.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 028]
　REN Zhan-guang,SHANG Fu-hua.Online Course Grade Prediction Model Based on Behavior Analysis[J].,2019,29(11):139-143.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 028]
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基于行为分析的在线课程成绩预测模型()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年11期
页码:
139-143
栏目:
应用开发研究
出版日期:
2019-11-10

文章信息/Info

Title:
Online Course Grade Prediction Model Based on Behavior Analysis
文章编号:
1673-629X(2019)11-0139-05
作者:
任占广1 ; 尚福华2
1. 重庆文理学院 软件工程学院,重庆 402160; 2. 东北石油大学 计算机与信息技术学院,黑龙江 大庆 163318
Author(s):
REN Zhan-guang 1 ; SHANG Fu-hua 2
1. School of Software Engineering,Chongqing University of Arts and Sciences,Chongqing 402160,China; 2. School of Computer &Information Technology,Northeast Petroleum University,Daqing 163318,China
关键词:
行为分析; 数据处理; 神经网络; 成绩预测
Keywords:
behavior analysis; data processing; neural network; grade prediction
分类号:
TP39
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 11. 028
摘要:
随着大学在线课程占全部课题比重的不断提高,为了更加科学地分析在线学习行为和准确地预测在线课程成绩,提出了一种基于行为分析的在线课程成绩预测模型。 首先,对学习行为及成绩预测策略进行了系统分析,构建了在线平台数据处理、成绩预测算法设计、成绩预测及算法优化的在线成绩预测机制;其次,利用数据挖掘技术收集在线学习行为数据,结合在线用户的操作特点对行为数据进行分析,提取了与成绩密切相关的 10 种行为指标数据并存储到数据库中;最后,以“玩课网冶平台的重庆文理学院“大学生计算机基础冶课程后台数据库作为实验数据基础,结合该课程实施特点,分析了学生学习行为,确定了学习行为指标等级,提取和转换了学生学习行为数据,并利用神经网络实现了在线课程成绩的预测。 实验结果表明成绩预测的准确率较高。
Abstract:
With the increasing proportion of online courses in all subjects,in order to analyze online learning behaviors more scientifically and predict online course grade more accurately, a behavior analysis-based online course grade prediction model is proposed. Firstly,the learning behavior and grade prediction strategy are systematically analyzed,and an online grade prediction mechanism is constructed,which includes data processing of online platform,design of grade prediction algorithm and optimization of grade prediction algorithm.Secondly,data mining technology is used to collect online learning behavior data,and according to the online user’s operational characteristics,the behavior data is analyzed,and 10 kinds of behavior indicators are extracted and stored in the database. Finally,with the database of the course “Computer Basis for College”of Chongqing University of Arts and Sciences as the platform of “Wankewang”,combined with the characteristics of course implementation, we analyze the learning behavior of students,determine the level of learning behavior indicators,extract and transform the data of students’ learning behavior,and utilize the neural network to finish the prediction of online course grade. The experiment shows that the performance prediction is more accurate.

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更新日期/Last Update: 2019-11-10