摘要
个性化和自适应学习系统是教育大数据应用服务的主要阵地,自适应学习系统能够采集学习过程中的行为数据,并对学生的学习兴趣、知识水平、学习风格、学习进度等做出分析和预测,以提供个性化的学习服务。近年来被学术界和企业界所广泛认可的典型自适应学习平台——牛顿平台(Knewton Platform)正逐步兴起,文章从自适应原理、核心技术、自适应服务三个方面对牛顿平台进行了剖析,以期能够为教育大数据分析研究人员和自适应学习平台设计者提供理论参考和技术借鉴。
Personalized and adaptive learning system is one of the vital applications of big data in education, which can collect learning behavior data and provide analysis and prediction on students＇ learning interest, knowledge level, learning style and learning progress. A typical adaptive learning system——Knewton Platform which has been widely recognized by academia and enterprise in recent years is rising gradually. A deep analysis on Knewton Platform, from the aspects of adaptive mechanism, core techniques and adaptive service, was made to provide some theory and technology references for the researchers of big data in education and designers of adaptive learning platform in the future.
出处
《现代教育技术》
CSSCI
2016年第5期5-11,共7页
Modern Educational Technology
基金
北京师范大学教育学部学生科研基金资助项目"泛在环境下自适应在线学习模型的设计与实现--以学习元平台为例"(项目编号:15秋-03-01)的阶段性研究成果
关键词
教育大数据
牛顿平台
自适应学习
知识图谱
项目反应理论
big data in education
Knewton platform
adaptive learning
knowledge graph
item response theory
