摘要
随着教育信息化的不断深入,网络教育的个性化发展已成为研究重点之一,这也对个性化学习及支持服务系统的核心组件——学习者模型提出了更高要求。针对当前网络教育已有学习者模型存在的问题,设计了一个多层次、多维度的个性化学习者模型,以研究数据挖掘、学习分析等技术在实现网络教育个性化学习者模型中的作用与影响,解决学习者模型中学习者信息笼统杂乱、学习者特征单一、学习者模型无层级性、各维度指标不清晰等问题,为网络教育的个性化支持服务提供决策依据,从而有效提升网络教育学习者的学习成效。
With the deepening of educational informatization, personalized development of online diploma education has b e-come the focus of research, which puts forward higher requirements from learner model, the core component of personalized learning system. This paper analyzes the problems existing in the student model of online education, and designed a multi-level and mul ti -di-mensional personalized student model. Then, it elaborates the techniques’ role in achieving the personalized learner model under the online education, such as Data Mining and Learning Analytics. This model solves these problems of lack of detailed analysis of stu-dent information, single student characteristics, non-hierarchical student model, and uncleanness of dimension index. This model im-plements personalized student model and provides decision support for personalized service of online education. Personalized learner model would provide foundations for personalized services, and effectively raise the learning performance.
作者
孙力
张婷
Sun Li Zhang Ting(Research Center of Educational Informatization, Jiangnan University, Wu xi Jiangsu 214122)
出处
《远程教育杂志》
CSSCI
2017年第3期93-101,共9页
Journal of Distance Education
基金
中央高校基本科研业务费专项项目"信息技术与教学融合创新多维研究"(项目编号:2015JDZD08)的研究成果
关键词
网络教育
个性化学习
个性化
学习者模型
学习者特征
Online education
Personalized learning
Personalization
Learner model
L ea rn ers ’ characteristics
