数据驱动下的个性化自适应学习研究综述

智能教育环境下的教学更加关注学习者的个性化诉求,而自适应学习能够为实现个性化教育提供技术和方法支持.文章从数据驱动的视角出发,通过开展国内外个性化自适应学习研究的综述分析,对其系统框架和相关组件进行阐述和解读.其中,重点从领域知识模型、学习者特征模型和教学模型三方面对其实现机制进行探析,提出当前研究存在的问题和不足,并在此基础上介绍了近年来可促进解释性提升的相关组件技术研究,奠定进一步深入个性化自适应学习研究的基础.

A Review of Data-Driven Personalized Adaptive Learning

Teaching in a smart education environment pays more attention to the individual demands of learners, and adaptive learning can provide technical and methodological support for achieving personalized education. A review of the domestic and foreign research on personalized adaptive learning research is conducted to interpret its system framework and related components. Its implementation mechanism is given at three aspects, i.e., the domain knowledge model, the learner characteristic model, and the teaching model. After a comprehensive analysis, the problems and deficiencies of current research are pointed out. On that basis, the research on related component technologies in recent years that can promote interpretability is introduced to provide references for the next step of personalized adaptive learning research.