摘要
在数据分析驱动教育变革的大数据时代,教育领域蕴藏着具有广泛应用价值的数据。通过教育数据挖掘构建教学变量相关模型、探索学员行为态势的影响机制,是具有较高实践价值的研究选题。本研究以浙江省教师MOOC培训平台中的课程作为研究对象,以网络数据分析工具为依托,采用基础数据整合、聚类结构变换、可视化、回归分析等数据处理和学习分析技术,从资源使用率、搜索词关联度解析、互动版块相关性三个维度对在线教育平台的日志和学员行为数据进行挖掘分析,研究并解析学员群体在线学习特性和学习态势的影响机制。挖掘结果可为量化评估学员的在线行为态势、学习效果及支持服务等提供参考。
In the big data era with education transformation driven by data analytics, it can be of great research value to construct, through educational data mining, related models of teaching variables and explore the influence mechanism of learners. behaviors. This study focuses on the teacher trainees in a provincial MOOC platform. Using online data analysis tools and learning analytics technology such as raw data integration, clustering structure transformation, visualization, regression analysis and so on, this study analyzed through data mining the online records of the platform and the learners. learning behaviors from three dimensions: resources usage, search words relevance analysis and interactive block relevance, aiming to formulate the influence mechanism of these trainees. learning behaviors. The findings can provide reference for quantitative evaluation of online learning behaviors, effectiveness of these behaviors and learning support services.
出处
《中国远程教育》
CSSCI
北大核心
2018年第10期35-43,79,共9页
Chinese Journal of Distance Education
基金
2019年度浙江省哲学社会科学规划课题“基于人工智能的教师教育智慧生态系统的开发与应用研究”(课题立项号:19NDQN325YB)
关键词
在线教育
学习行为态势
象限
数据挖掘
维度
回归分析
互动版块
相关性
优化
online education
quadrant
learning behavior
data mining
dimension
regression analysis
interactive block
relevance
optimization
