生成式人工智能赋能教学的机制、需求与路径  

The Mechanisms,Needs,and Pathways of Generative Artificial Intelligence Teaching Empowerment

作　　者：顾小清 王成梁 王培均 景玉慧 GU Xiaoqing;WANG Chengliang;WANG Peijun;JING Yuhui

机构地区：[1]华东师范大学教育学部,上海200062 [2]中国教育学会中小学信息技术教育专业委员会 [3]南京师范大学教育科学学院,江苏南京210097 [4]浙江工业大学教育学院,浙江杭州310023

出　　处：《中国教育学刊》2025年第4期15-22,共8页Journal of The Chinese Society of Education

基　　金：浙江省社科规划“党的二十大和省委十五届二次全会精神研究阐释”专项一般课题“教育高质量发展战略下学习空间赋能课堂教学的机制及路径研究”;国家社会科学基金2019年度重大项目“人工智能促进未来教育发展研究”(项目编号:19ZDA364)阶段性研究成果。

摘　　要：面对生成式人工智能的革命性影响,教学如何趋利避害应变成为当前教育领域关注的重点。本研究主要采用对比和演绎方法,首先,通过生成式人工智能与主体人对比,发现生成式人工智能具有知识授导者和启发探究者双重角色,能从助力高效获取已知、深度建构未知两方面促进教学提质增效;其次,立足双重角色,以活动理论为支撑,构建生成式人工智能赋能教学的机制模型;之后,基于机制模型,从培养目标、学习活动、教学方法、学习工具、学习评价五大观测指标,解析生成式人工智能赋能教学的应变需求与路径。Facing the revolutionary impact of Generative Artificial Intelligence(GAI),how education can adapt to maximize benefits and minimize drawbacks has become a focal point.This article employs comparative and deductive methods.First,by comparing GAI with human subjects,this article identifies that GAI obtains dual roles as a knowledge instructor and an inquiry facilitator,demonstrating its potential to enhance teaching efficiency by aiding in the efficient acquisition of known knowledge and the deep construction of the unknown.Second,grounded in these dual roles and guided by the activity theory,this article constructs a mechanism model for GAI-empowered teaching.Subsequently,based on this mechanism model,this article further analyzes the adaptive requirements and pathways of GAI-empowered teaching through five key observational indicators:educational objectives,learning activities,teaching methods,learning tools,and learning assessments.

关 键 词：生成式人工智能 活动理论 课堂教学 赋能机制 

分 类 号：G43[文化科学—教育学]