Jun 2026· International Journal of Multilingualism and Languages for Specific purposes· Vol 8, pp. 124-143· 0 citations
TL;DR
This research demonstrates how a pedagogy synergistically combining CDA with hands-on AI interaction fosters deeper digital citizenship, enhances critical thinking, and improves employability skills, and recommends curriculum design that reward critical engagement over mere output generation.
Abstract
The rapid integration of Artificial Intelligence (AI) into academia and industry necessitates a fundamental transformation of higher education curricula. Moving beyond purely technical proficiency, this paper proposes a comprehensive framework for embedding AI Literacy and Critical Discourse Analysis (CDA) as transdisciplinary core competencies, positioning AI outputs not as neutral tools but as ideologically laden discourse requiring rigorous scrutiny. Drawing on a qualitative multiple-case study involving undergraduate Communication (n=45) and Business (n=38) courses at a Zambian university, this research demonstrates how a pedagogy synergistically combining CDA with hands-on AI interaction fosters deeper digital citizenship, enhances critical thinking, and improves employability skills. Over a three-week intervention, students applied Fairclough’s three-dimensional CDA model to AI-generated press releases and marketing content. The findings reveal three transformative outcomes: first, students adeptly identified embedded societal biases such as gendered leadership stereotypes; second, they reconceptualised AI from an authoritative “oracle” into a fallible, dialogic partner requiring ongoing interrogation; and third, they developed sophisticated, ethically-informed prompting strategies that directly corrected identified biases, a synergistic loop between critique and creation. This approach ensures graduates emerge as critical, innovative, and ethical producers rather than passive consumers of technology. The paper recommends curriculum design, including transdisciplinary modules, faculty development, open-access resources, and reformed assessment strategies that reward critical engagement over mere output generation.
The Responsible AI Literacy in Education (RAIL-Ed) framework is introduced, developed through a systematic review and qualitative framework analysis of 67 studies (2023-2025), grounded in critical, pragmatist, sociocultural, and human-centered traditions.
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