摘要
从学习分析系统角度研究MOOC教育中低通过率与有效学习的问题。通过分析学习者学习活动情况,在MOOC社区取样大量原始数据,生成平台学习数据,采用一个基于Hadoop的MOOC学习分析系统对数据进行分析和挖掘,促进学习者进行有效学习。为了评估该系统的有效性,开发一种分析方法来识别那些容易辍学、低延迟的在线学习者,以使得MOOC服务商能够有效地进行教学策略调整,提高了课程通过率。
Study on the problems of low pass rate and effective learning in MOOC （massive open online courses） education from the perspective of the learning analysis system. Through the analysis of learners＇ learning activities, sampling a large number of original data in MOOC community to generate the platform＇s learning data, a Hadoop based MOOC learning analysis system is used for data analysis and data mining to promote learners for effective learning. In order to evaluate the effectiveness of the system, an analytical method is developed to identify those online learners who are easy to drop out of school, so that the MOOC service providers can effectively adjust the teaching strategies, and improve the pass rate of the course.
出处
《计算机时代》
2016年第7期45-48,共4页
Computer Era
基金
韶关学院韶州师范分院2015教研项目(SZSF20150103)
