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“Better safe than sorry”: Unveiling doctoral students’ critical AI literacy development in academic writing

Year: 2026

Type: article

Abstract: Despite the growing incorporation of GenAI tools in academic writing, research has yet to adequately examine how doctoral students develop critical AI literacy in their interactions with such technologies. Adopting a sociocultural perspective, this qualitative case study investigates the processes through which nine doctoral students developed critical AI literacy in academic English writing. Drawing on semi-structured interviews, screen recordings, learning journals, reflective reports and AI logs, data analysis reveals four developmental trajectories of critical AI literacy: from uncritical consumers to informed users who examined GenAI tools' inner workings and limitations; from AI-dominated users to dominators of AI who valued text ownership and authorial agency; from passive recipients to strategic users who emphasized proactive GenAI use for self-learning; and from efficiency-oriented users to responsible scholars attentive to GenAI's epistemic, ethical and social implications. These changes were mediated by their interactions with knowledgeable others, engagement with cultural artefacts, and self-regulated exploration. The study highlights the socially-mediated process of critical AI literacy and offers practical implications for cultivating critical AI literacy in doctoral education.

Source: Journal of English for Academic Purposes

DOI: 10.1016/j.jeap.2026.101765

Authors: Min Zou, Yao Zheng

Institutions: Beijing Institute of Technology, Chongqing University

Language: English

Topic: Discourse Analysis in Language Studies

Subfield: Literature and Literary Theory

Field: Arts and Humanities

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,730