Responsible AI-Mediated Academic Literacy among Future Teachers: A Constructivist Grounded Theory of Ethical Scholarship in the Age of Generative AI

Abstract

The rapid emergence of generative artificial intelligence (AI) technologies has transformed academic writing, learning, and knowledge production in higher education. This constructivist grounded theory study explored how future teachers construct responsible AI-mediated academic literacy in their academic work. The study examined how pre-service teachers use AI-assisted tools, negotiate authorship and ownership, protect academic integrity, balance efficiency with learning, preserve personal voice, and respond to institutional and social expectations. Data were generated through semistructured interviews, observations, field notes, and analytic memoing involving teacher education students with experience using generative AI tools such as ChatGPT, Grammarly, and related platforms. Analysis followed constructivist grounded theory procedures, including initial coding, focused coding, constant comparative analysis, theoretical sampling, memo writing, and theoretical integration. Findings generated five major categories: AI as a supportive learning and writing resource rather than a replacement for human thinking; negotiating authorship, ownership, and academic integrity in AIassisted writing; balancing efficiency, learning, and dependence through ethical decision-making; preserving personal voice, authenticity, and human agency; and navigating institutional expectations, policies, and social influences in responsible AI use. These categories converged into the core category of constructing responsible AI-mediated academic literacy through Human-Guided Ethical Engagement. The study generated the Responsible AI-Mediated Academic Literacy Framework (RAALF), which explains responsible AI use as a cyclical, reflective, and human-directed process. The findings suggest that AI literacy in teacher education must extend beyond technical tool use toward ethical self-regulation, authorship preservation, critical evaluation, transparency, and professional responsibility.