A Taxonomy of Literacy Practices for Engaging with Artificial Intelligence: Reading and Writing in the Age of Generative AI

AI Literacy: An Exercise in Power-Knowledge

As generative artificial intelligence becomes one of the most significant systems of knowledge production in our society today, questions relating to who can access and shape that production grow increasingly important in our discourse. This paper argues that the existing frameworks for AI literacy, which are dominated by technical competency and responsible-use principles, are insufficient because they enforce a"consumer"orientation toward AI rather than fostering genuine epistemic agency. Based upon Foucault's concept of power-knowledge, Freire's pedagogy of critical consciousness, and scholarship of digital literacy, this paper proposes a reconceptualization of AI literacy as a critical practice that equips individuals not just to use AI systems, but to critically evaluate them, resist their structuring assumptions, and participate in their governance. The paper further argues that unequal access to AI tools in society recapitulates longstanding epistemic injustices, and that a literacy framework oriented toward empowerment must account for these structural inequities. A three-part framework of AI literacy based on the notions of contextual use, critical interrogation, and participatory governance frames this literacy as a cultivation of epistemic"agents"rather than the training of competent consumers of AI-generated information.

Rethinking Generative AI Literacy: An Integrative, Developmental, and Dialectical Framework for K-12 Teacher Education

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.

Reconceptualising academic reading-to-write in the age of generative AI: an AI-mediated knowledge construction framework

Generative artificial intelligence (GenAI) research has largely focused on text generation, feedback, and writing enhancement, overlooking the cognitive and epistemic processes underlying academic knowledge construction. This paper proposes the AI-mediated knowledge construction (AMKC) framework to explain how GenAI may support graduate students' reading-to-write development. Integrating academic literacies, reading-to-write research, sociocultural theory, and dialogic approaches, the framework positions GenAI as a cognitive mediator and dialogic partner across dialogic reading, knowledge transformation, source integration, disciplinary meaning-making, critical reflection, and academic writing. Six theoretical propositions elaborate the mechanisms of AI-mediated literacy development, while pedagogical implications and a future research agenda address implementation and empirical validation. By shifting attention from writing assistance to knowledge construction, AMKC provides a theoretically grounded account of GenAI-mediated academic literacy development in higher education.

From Information Literacy to AI Literacy: A New Pedagogical Role for Academic Libraries

The rapid integration of artificial intelligence (AI) into higher education is reshaping teaching, learning, and knowledge production, prompting academic libraries to reconsider their pedagogical roles. Traditionally positioned as key actors in developing information literacy, libraries are now increasingly confronted with the need to foster AI literacy, which is understood as the ability to critically understand, evaluate, and ethically engage with AI-driven systems. This paper offers a theoretical exploration of the transition from information literacy to AI literacy and examines how this shift redefines library pedagogy. Drawing on established information literacy frameworks and emerging scholarship on AI literacy, the paper conceptualizes AI literacy as an extension rather than a replacement of information literacy. It argues that academic libraries are uniquely positioned to mediate this transition due to their longstanding expertise in critical inquiry, ethical information use, and learner-centered pedagogy. The discussion highlights key pedagogical dimensions of AI literacy, including algorithmic awareness, data ethics, transparency, bias, and responsible use of generative AI tools in academic contexts. The paper further positions librarians as pedagogical partners and learning facilitators who support students and faculty in navigating AI-enhanced learning environments. By reframing AI literacy within a critical and human-centered pedagogical approach, the study underscores the strategic role of academic libraries in promoting informed, reflective, and ethical engagement with AI technologies. The paper concludes by outlining implications for library teaching practices and future research directions in library-based AI pedagogy.

Design Principles for Generative AI Literacy Development in Design Principles for Generative AI Literacy Development in Teaching Teaching

AI in EFL Writing Instruction: A Systematic Review of Writing Conceptualizations and Learner Agency

The findings revealed that learner agency is influenced more by pedagogical integration than by the technology itself, which underlined the importance of teaching EFL writing through theoretically informed, process-oriented approaches that empower learners and incorporate effective AI use.