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Integrating GenAI with genre-based pedagogy and the PAA model in a college writing course: Enhancing critical engagement in an AI-mediated learning ecology

代理(哲学) 教育学 批判性思维 批判教育学 批判性识字 社会学 读写能力 批判性反思 心理学 反射(计算机编程) 批判理论 语言习得 数学教育 高等教育 教学方法 生成语法 语篇分析 半结构化面试 学习环境 生成模型 主动学习(机器学习)
作者
Jiajia Eve Liu,Zhuang Qiu,Angel M. Y. Lin
出处
期刊:Linguistics and Education [Elsevier BV]
卷期号:92: 101487-101487
标识
DOI:10.1016/j.linged.2025.101487
摘要

• Integration of GenAI, genre-based pedagogy, and the PAA model can enhance one another to support students' learning. • The integrated approach enabled students to gain access to the patterns and norms of different genres while enhancing students’ critical awareness of how to engage with AI in agentic, empowering ways. • Students were supported to learn in a linguistically and culturally inclusive and emotionally aware educational ecology. • The study offers a technology-enhanced critical pragmatic approach to genre-based pedagogy. While recent advances in Generative Artificial Intelligence (GenAI) have opened new opportunities for integrating GenAI into language and literacy education, there remains a significant gap regarding how GenAI can be effectively integrated with linguistics-based education theories to enhance AI-mediated learning. This study addresses this gap by exploring a systematic integration of GenAI with genre-based pedagogy and the PAA (Plurilingualism, Affect, Agency) model to foster students’ critical learning in a college English writing course. Through qualitative analysis of students’ writing samples, chatlogs, and their reflection logs, we noticed enhanced student agency in mastering genre conventions, generating ideas, and learning genre-specific lexicogrammatical patterns through contrasting and analyzing AI-generated texts to improve their writing. More importantly, students also developed critical awareness of the potential epistemic and cultural biases in GenAI outputs, and started prompting GenAI with critical feedback to generate more inclusive and contextually relevant responses. Through this positive and affective journey, students gained confidence not only in their genre writing skills but also in learning how to critically and responsibly co-learn and co-work with AI. Informed by the PAA model, the paper proposes a teacher-actionable framework to integrate GenAI with genre-based pedagogy to enable students to gain access to the patterns and conventions of different academic genres while enhancing students’ critical awareness of how to engage with AI in agentic, responsible and empowering ways.

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