摘要
常态教学往往只关注学习者已有能力的差异,忽视学习者的发展潜能,不易实现真正的因材施教。维果斯基提出最近发展区的概念,正是解决教学与发展的关系,并由此衍生出动态能力评估。然而,评估最近发展区需要采集大量学习者的数据作为支撑,传统教学中由于缺乏对学习过程中的数据采集和分析手段,难以对学习者的最近发展区进行有效评估,也就难以支持精准教学。利用大数据技术对学习者在线学习数据有效采集和分析,为诊断最近发展区,促进精准教学提供了技术支持。文章提出学习者在学科概念理解过程中的最近发展区表征模型;结合动态能力评估理论,以学科素养-能力表现-核心概念为统一的编码体系,计算学习者在不同能力维度的发展区间与能力表现的认知状态;结合一线教学实践,归纳出基于最近发展区的精准教学之主要环节,以期为基于大数据分析与改进教学的实践与研究提供借鉴。
Normal teaching usually only focuses on the differences of learners'existing abilities and ignores their development potential,which makes it difficult to teach students according to their aptitude.Vygotsky has proposed the concept of the Zone of Proximal Development,which addresses the relationship between teaching and development and leads to dynamic ability assessment.However,to assess the Zone of Proximal Development requires the acquisition of a large amount of learners'data as support.In traditional teaching,due to the lack of data collection and analysis tools in learning process,it is difficult to effectively evaluate learners'Zone of Proximal Development and then to support precision teaching.Using big data technology to effectively collect and analyze learners'online learning data provides technical support for diagnosing the Zone of Proximal Development and promoting precision teaching.This paper proposes a presentation model of the zone of proximal development in the process of learners'understanding of subject concepts.In combination with the theory of dynamic ability assessment,the development interval and cognitive states of learners'competence performance in different competence dimensions are calculated based on the unified coding system of subject accomplishment,competence performance and core concept.Based on the front-line teaching practice,this paper summarizes the main steps of precision teaching based on the zone of proximal development,in order to provide reference for the practice and research of teaching based on big data analysis and improvement.
作者
刘宁
余胜泉
LIU Ning;YU Shengquan(School of Educational Technology,Faculty of Education,Beijing Normal University,Beijing 100875;Advanced Innovation Center for Future Education,Beijing Normal University,Beijing 100875)
出处
《电化教育研究》
CSSCI
北大核心
2020年第7期77-85,共9页
E-education Research
基金
教育部哲学社会科学研究重大课题“‘互联网+’教育体系研究”(课题编号:16JZD043)
北京师范大学教育学部科研基金资助项目“大数据分析视角下自适应学习支架的构建与实践研究”(项目编号:1712201)。
关键词
大数据
精准教学
最近发展区
智慧学伴
个性化学习
Big Data
Precision Teaching
Zone of Proximal Development
Smart Learning Partner
Personalized Learning