文献类型：期刊文献

中文题名：基于MOOC数据挖掘的学习行为和学习成效分析

英文题名：Analysis of Learning Behavior and Learning Effectiveness Based on MOOC Data Mining East China University of Science and Technology College of information science and Engineering

作者：陈兰岚[1];宋海虹[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2019

期号：21

起止页码：50

中文期刊名：教育教学论坛

外文期刊名：Education And Teaching Forum

基金：华东理工大学继续教育教学研究项目的研究成果

语种：中文

中文关键词：MOOC;学习行为;学习成效;数据挖掘;个性化学习

外文关键词：MOOCs;learning behavior;learning effectiveness;data mining;personalized learning

摘要：随着近年来慕课教学的兴起,教育大数据的分析与挖掘正成为一个新的研究方向。本文基于Canvas Network提供的MOOC开放数据,使用数据统计和数据挖掘的方式,对学习者的类型与行为进行了统计分析,并探究了学习行为与学习成效之间的相关性,并基于分析结果对个性化的在线学习方式提出了有益的建议。
With the advance and popularity of MOOCs in the recent years,the analysis and mining of large educational data is becoming a new research direction.This research utilized the public MOOCs learning data provided by Canvas Network.By using data statistics and data mining methods,the types and behaviors of learners were statistically analyzed and the correlation between learning behavior and learning effectiveness was explored.Based on the analysis results,some useful suggestions for personalized online learning could be put forwarded.