学习分析视角下面向高阶思维发展的课堂互动分析与评测

Classroom interaction is an important manifestation of new teaching and learning methods. It is a basic carrier for training high-quality talents and accelerating the modernization of education in the new era. With the rapid development of educational information technology, there is a growing need to explore the laws of teaching and learning in the new environment. The combination of learning analytics technology and classroom interaction has attracted wide attention from scholars at home and abroad. However, there are still some problems, such as the lack of a scientific and systematic evaluation model, the emphasis on the interactive form of coding system while lack of in-depth mining of thinking characteristics, focus on distance learning while lack of research based on digital classroom. To this end, this project intends to evaluate classroom interaction in primary and secondary schools in the context of digital classroom by using learning analytics technology and in particular, focuses on how classroom interaction promotes the cultivation of higher-order thinking. Through data acquisition, extraction and mining, breakthroughs are expected to be made in building theoretical models and coding systems for evaluating classroom interaction, diagnosing classroom interaction characteristics, exploring the rules of high-quality interaction, and tracking the interactive ways of high-level thinking training. The results of this project will help to promote the deep integration of information technology and classroom teaching, improve the quality of classroom interaction, and provide targeted strategic support for improving learning and teaching.

课堂互动是新型教学和学习方式的重要体现，是新时期培养高素质人才、加快推进教育现代化的基本载体。随着教育信息技术的飞速发展，探索新环境下的教与学规律的需求日益强烈，学习分析与课堂互动的结合已经引起国内外学者的广泛关注，但是仍存在缺乏科学系统的评测模型，编码体系重互动形式而对数据隐含的思维特征缺乏深入的挖掘、多关注远程教学而少基于数字化教室的研究等问题。为此，本项目拟基于学习分析的视角在数字化教学的场景下对中小学课堂互动展开评测，特别关注课堂互动如何促进学生高阶思维的发展。通过数据采集、数据抽取和分析挖掘，立足在构建评测课堂互动的理论模型和编码体系、诊断课堂互动特征、探究高质量互动的过程性规律、追踪高阶思维培养的互动途径等方面取得突破。研究结果有助于提升信息技术与课堂学习的深度融合，提高课堂互动的质量，为改进学习和教学提供有针对性的策略支持。

课堂是人才培养的主阵地，提升课堂教学质量是促进基础教育高质量发展、培养创新型人才的重要抓手。互动式课堂教学以课堂对话为载体，以思维培养为主要目标，智能技术为课堂教学分析提供了有效的工具手段。为了发挥智能技术的作用、赋能互动式课堂教学分析和高阶思维发展，本项目从以下三方面展开研究并取得相应成果，第一、提出了面向思维培养的课堂教学评价指标体系CI-PCD，评价体系将在提问-反馈经典模式的基础上引入体现思维发展的指标，以更有效地对接高质量教育发展背景下的思维培养目标，同时该指标体系应具有广泛的代表性和适用性，以支持区域和校际间的对比分析。第二，创设了基于音视频文本的课堂教学自动标注方法，以面向思维培养的课堂教学评价体系为依据，借助卷积神经网络与双向长短期记忆网络相结合的混合神经网络技术（CNN+BiLSTM）实现了大规模课堂数据的快速精准标注，能够有效提炼课堂教学中的思维特征。第三，发展了适应课堂教学场域的序列模式挖掘技术，揭示了课堂教学的过程性发展模式和思维进阶规律, 探究课堂教学中的深层认知规律和思维进阶规律，解构促进高阶思维培养的教学模式,有助于提炼高质量课堂教学的模式，促进高阶思维的发展。本项目在此基础上，为了验证以上智能技术在课堂教学分析和学生思维培养中的作用，以广东省A学校为例进行了为期一年的试验并进行了全过程监测，通过对比第一次和最后一次监测结果发现，在智能技术的加持下，涉及高阶思维的课堂对话比例得到显著提升，思维链条更长且能体现由低阶思维朝向高阶思维进阶的规律，其中较为显著的长链条对话呈现出知识习得→观点表达→分析阐释→总结归纳→迁移创新的进阶模式。研究有利于推动人工智能与课堂教学领域融合发展，有助于促进课堂教学转型，创建优质高效的课堂。