摘要
随着终身学习体系的逐步构建,基于互联网的远程学习模式应用不断普及,各种网络学习平台也不断累积大量的学员学习和考试方面的数据。采用数据挖掘技术对这些数据进行分析,可以充分挖掘网络学习平台存量数据的价值。基于C5.0决策树算法,采用软件工具对研究数据进行分析,发现了影响考试结果的诸多因素及其重要性,可以针对如何改善学习方法、提升学习效果、改善平台的服务模式等提出很好的改进建议。
With the gradual construction of lifelong learning system,Internet based distance learning mode continues to spread. All kinds of network platforms also accumulate a large number of students learning and test data. Using data mining technology to analyze these data,we can fully tap the value of the stock data of the network learning platform. Based on C5. 0 decision tree algorithm,using software tools to analyze the research data,the author found many factors that affect the test results and their importance can improve the learning method,the learning effect,and the service mode of the platform.
出处
《微型机与应用》
2016年第8期68-70,共3页
Microcomputer & Its Applications
关键词
决策树
考试结果
预测
decision tree
test results
prediction
