摘要
数据为王的大数据时代正在来临,如何将大数据关联于教育变革以及由此衍生的学习分析的应用逐渐成为了热点课题。文章以浙江省教师教育MOOC培训平台为例,任选其中的某门在线课程,通过常规挖掘、频次统计、跳转聚合、数据可视化等方法,以渐进深入的方式,对选课学员的学习行为和日志进行数据挖掘,并根据学员在平台中的学习行为数据,展示学员与课程的相关性和适应度,发掘学员模块的学习规律和学习喜好,定位平台中的模块功能和课程资源缺陷,优化适应性教学资源,定制个性化学习路径,促进个性化发展。研究表明:上述这些举措将大大提高选课学员的用户体验感和满意度。
The era of taking data as king is coming. How to relate big data to education reform and from which application of study analysis derived, have gradually become hot research topics. This article took teacher education MOOC training platform of Zhejiang province as example, selected one of these online courses, and employed the methods of conventional excavating, frequency statistics, jump aggregation, data visualization to excavate the data of students' learning behavior and studing log in a progressive way. According to students' learning behavior data in this platform, the relevance and adaptability of the students with the course were demonstrated, the module learning rules and learning preferences of students were explored, the module function and course resource defects of this platform were located, the adaptive teaching resources were optimized, personalized learning path was customized, personal development was cultivated. These initiatives will greatly enhance the students' experience and satisfaction to this platform.
出处
《现代教育技术》
CSSCI
2016年第8期109-115,共7页
Modern Educational Technology
基金
2014年度全国教育信息技术研究课题“基于Edu Soho与移动云技术的教师教育Mooc系统的开发与应用研究”(项目编号:146232067)的研究成果
关键词
大数据
学习分析
挖掘
碎片化
界面跳转
big data
study analysis
excavate
fragmentation
interface jump