“教学法转型”:人机共生时代的教学原则构建  

Pedagogical Transformation:Constructing Teaching Principles in the Era of Human-AI Symbiosis

作　　者：乐惠骁 宋小伟 于青青 汪琼[1] LE Hui-Xiao;SONG Xiao-Wei;YU Qing-Qing;WANG Qiong(Graduate School of Education,Peking University,Beijing,China 100871;Center for Excellent Teaching and Learning,Peking University,Beijing,China 100871)

机构地区：[1]北京大学教育学院,北京100871 [2]北京大学教师教学发展中心,北京100871

出　　处：《现代教育技术》2025年第2期6-15,共10页Modern Educational Technology

基　　金：国家社会科学基金2023年度教育学重大项目“新一代人工智能对教育的影响研究”(项目编号:VGA23001)的阶段性研究成果。

摘　　要：当前,随着以ChatGPT为代表的生成式人工智能技术的兴起,教学活动正从传统的“师-生”二元主体结构转变为“师-生-机”三元结构。在此背景下,作为新主体的AI代理应该秉持怎样的设计原则,才能够实现不输于传统“师-生”互动的有效教学?“人-人”教学中的有效教学策略又能否迁移到“人-机”教学的场景中?为回答上述问题,文章回顾了教学代理的相关研究,围绕两个方面展开研究:一是保证情感互动。在媒介层面,提升机器的社会临场感,使其能够通过拟人化的声音、表情和行为与学习者进行情感化互动;在社交层面,重视社交规范的作用,重新构建机器和学习者之间的互动规则,促进有效的教学交互。二是保证信息有效性。针对大模型的“幻觉”问题,提出结合领域知识库和技术护栏机制来提升信息的准确性;关注人机信任的平衡,避免过度信任和算法厌恶,培养学习者的批判性思维和数字素养。文章通过这一系列讨论,旨在提出构建适用于“人-机”教学场景的设计原则,为人工智能教育应用的开发设计和教学实践创新提供参考。With the emergence of generative artificial intelligence technologies exemplified by ChatGPT,the fundamental structure of educational activities is transitioning from the traditional binary“teacher-student”framework to a ternary“teacher-student-machine”structure.What design principles should AI agents,as new actors in this structure,follow to establish effective teaching interactions that are comparable to traditional teacher-student dynamics?What differences between humans and machines pose unprecedented challenges when translating existing human-to-human teaching theories and models to human-machine teaching scenarios?This paper addresses two critical issues:First,ensuring emotional interaction-at the media level,enhancing the machine’s social presence to enable emotional engagement with learners through humanized voice,expressions,and behaviors;at the social level,emphasizing the role of social norms and reconstructing interaction protocols between machines and learners to promote effective teaching interactions.Second,ensuring information validity-addressing the“hallucination”issue of large language models by proposing the integration of domain knowledge bases and technical guardrail mechanisms to improve information accuracy;focusing on the balance of human-machine trust to avoid both over-reliance and algorithm aversion while fostering learners’critical thinking and digital literacy.This paper aims to propose design principles for future human-machine teaching scenarios through these discussions.

关 键 词：生成式人工智能 教学理论 临场感 算法信任 社交规范 

分 类 号：G40-057[文化科学—教育学原理]