Teacher agency and generative artificial intelligence: teaching in higher education as a responsive, cultural activity

代理(哲学) 功能可见性 教育学 社会学 高等教育 自反性 框架(结构) 数学教育 生成语法 教师教育 教学方法 语篇分析 活动理论 概念化 认识论 心理学 结构和代理 主题(文档) 体验式学习 教育社会学 语言习得 能力(人力资源) 弱势群体 教育研究 语言教育 关系(数据库)
作者
Peter Kahn,Mark Carrigan,Paul Vincent Smith,Lisa Murtagh,R.Y. Liu,Fangtong Song
出处
期刊:Learning, Media and Technology [Taylor & Francis]
卷期号:: 1-12 被引量:1
标识
DOI:10.1080/17439884.2025.2575993
摘要

The widespread adoption of Generative Artificial Intelligence tools by students poses a challenge to teachers in Higher Education. This study aimed to explore the nature of teacher agency in a setting where students were making extensive use of Large Language Models. The study was conducted in a research-intensive university in the UK, adopting a sequential mixed methods research design. It found that challenges entailed in university teaching can helpfully be framed in terms of a relationship between the agency of teachers and the agency of students, even as this relationship is subject to cultural influences. Given a reflexive basis for agency, this framing underscores the importance of dialogue between teachers and students, even as the uncertainty generated by Large Language Models undercuts the conditions which make the dialogue possible. The study also highlights the limitations of existing perspectives on higher education pedagogy that see the relation between teaching and learning as something primarily determined by structural considerations. It offers an original conceptualisation of higher education pedagogy that sees teacher agency as incorporating a collective response to shifts in the epistemic agency of students – in a fashion that accounts for the affordances of contemporary digital tools and expertise in their use.
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