Journal of Interactive Media in Education
***JIME is currently focusing on a number of Special Collections - see announcements below for more details on our calls for papers- the journal is therefore closed to general submissions at the present time.*** JIME is a peer reviewed open access online journal in educational technology that focuses on the implications and use of digital media in higher or post-compulsory education. It aims to foster a multidisciplinary and intellectually rigorous debate on both the theory and practice of interactive media in higher or post-compulsory education. JIME was launched in September, 1996.
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The following publication contains book reviews of these titles: Chigona, A, Crompton, H and Tunjera, N. (eds) 2024. Global perspectives on teaching with technology: theories, case studies, and integration strategies. Routledge. Gupta, SL, Kishor, N, Mishra, N, Mathur, S and Gupta, U. (eds) 2021. Transforming higher education through digitalization: Insights, tools and techniques. CRC Press, Taylor and Francis Group. Roushan, G, Polkinghorne, M and Patel, U. (eds) 2025. Teaching and learning with innovative technologies in higher education: Real-world case studies. Routledge. Mujtaba Asad, M, Sherwani, F, Bin Hassan, R and Churi, P. (eds.) 2021. Innovative education technologies for 21st century teaching and learning (1st ed.). CRC Press, Taylor & Francis Group. https://doi.org/10.1201/9781003143796
Copyright (c) 2025 The Author(s) https://creativecommons.org/licenses/by/4.0
Editorial: Open Education and Open Science in the Digital Age: Echoes and Horizons of the Dubai Declaration
Open Education and Open Science in the Digital Age: Echoes and Horizons of the Dubai Declaration
Copyright (c) 2026 The Author(s) https://creativecommons.org/licenses/by/4.0
Unsafe AI for Education: A Conversation on Stochastic Parrots and Other Learning Metaphors ⚠️
This interview article discusses the impact on popular and educational discourses of the metaphor for a Large Language Model of a “stochastic parrot”. The metaphor comes from the title of an influential paper on the harms of large language models from 2021. Here we present a perspective on the short but influential history of the metaphor through an interview with one of its creators, Professor Emily M. Bender. Using the broad lens of metaphor as a way to shape and frame discourse, the editors interviewed Professor Bender and asked her a series of questions to spark discussion around AI in Education. A variety of topics were covered, including: on how metaphors and anthropomorphisation when carelessly used can elide harms and obviate responsibilities; the role of BigTech, data theft and metaphors of colonisation; Whether AI is unsafe for education and if so to which learners; Techno-solutionism; Positionality and AI “voice”; and whether EdTech is a key driver of AI bullshit and enshittification. This article aims to give readers an accessible insight into how a particular metaphor may be enacted in discourse and to contribute to wider critical debates about how GenAI operates in the context of datafication and educational harms.
Metaphors of AI in Education: Discourses, Histories and Practices
AI-Driven Model for Fostering International Cooperation in Open Education: A Roadmap for Innovation and Equity
Although artificial intelligence (AI) is transforming educational practices worldwide, there is a limited understanding of how it can shape structured forms of international cooperation in open education. This study asks: How can AI support international cooperation in open education aligned with global equity agendas? An instrumental case study was conducted on the UNESCO/ICDE 2025 Residency, involving 110 participants from 13 countries. Data sources included team logs, a post-residency survey with 72 responses, and a co-authored manifesto. These materials were analysed through content analysis, inductive coding, and visual mapping. The results indicate four main contributions: first, ten interdisciplinary projects aligned with UNESCO frameworks; second, broad engagement across five strategic action areas; third, the identification of three key domains, which are Enabling Conditions, Cooperative Processes, and Sustainability Mechanisms; and fourth, the role of AI in enabling collaboration, design, and knowledge sharing. The proposed roadmap presents a scalable model for educators, policymakers, and global networks to foster equitable, AI-driven cooperation in open education.
Empowering Equity, Diversity and Inclusion: The Impact and Future of Open Education in Latin America
The objective of the research presented in this paper is to understand the current state of Equity, Diversity and Inclusion (EDI) within Open Education in Latin America, and to explore how communities of open practice can be more equitable, diverse and inclusive within this context. Insights from 12 experts in the region were collected through interviews and a focus group. Latin America emerges as a critical region for examining these goals due to its uneven digital infrastructure and diverse educational contexts. The study results highlight Latin America’s potential to foster open ecosystems through increased collaboration among universities, capacity-building with local experts, and clearer regional identity and communication. It also recommends supporting multilingual content and inclusive events to strengthen the community. From an EDI perspective, expanding access in low-bandwidth environments is essential. While AI offers promising tools like multilingual translation, its high resource demands pose sustainability and equity challenges, especially in Latin America. The study cautions against premature AI adoption without foundational infrastructure and digital confidence. It also warns of risks like algorithmic bias and cultural erasure if AI tools lack authentic community engagement. UNESCO’s 2024 Dubai Declaration outlines a strategic vision for enhancing the accessibility and impact of Open Educational Resources (OER), with a strong emphasis on EDI. The Dubai Declaration’s emphasis on capacity-building and inclusive access aligns with the study’s findings, which underscore the need for participatory, context-sensitive approaches.
Co-Creation Strategies for Equitable Open Education: A Framework for Diversity and Inclusion
Education must be inclusive for all. Higher education institutions are aware of their responsibility to provide alternatives to meet the challenges of equitable education. But the great diversity of possibilities creates an even greater challenge: how to include everyone? This article presents the development of the INSPIRA framework, a participatory model designed to guide co-creation strategies that foster inclusion and equity in open and digitally mediated educational environments. Grounded in the collective experience of educational communities, the framework proposes to use the collective experience of the educational community of institutions as a focus for the creation of context-specific strategies. To this end, we analyzed 20 co-creation strategies developed with specific communities that contribute to inclusion in the educational context. The study yielded findings that allow us to conclude that the INSPIRA framework may serve as a meaningful contribution to ongoing efforts in developing contextualized, relevant, and up-to-date inclusion strategies for institutions committed to embracing classroom diversity with dignity and purpose.
Open Education in Latin America: A Regional Assessment of Open Educational Resources Initiatives
Open education has emerged as a key approach to promoting equitable access to knowledge, grounded in collaboration, content reuse, and the use of open licenses. Within this framework, Open Educational Resources (OER) represent a fundamental strategy for expanding learning opportunities in Latin America, particularly in contexts characterized by structural inequalities. Although numerous initiatives have emerged across the region, there remains a lack of a comprehensive regional diagnosis that would allow for an understanding of their distribution, characteristics, and stage of development. This study aimed to map and analyze the OER available on web platforms from Spanish-speaking countries in Latin America, considering variables such as resource type, educational level, institutional support, licensing, covered topics, and their degree of alignment with the strategic objectives outlined in UNESCO’s 2019 Recommendation on Open Educational Resources (UNESCO 2022). An exploratory, automated methodology was employed, combining web crawling tools (Netpeak Spider), scraping scripts in Python/Selenium, manual review, and expert validation. A total of 210 active websites offering open educational resources were identified. The findings reveal a strong emphasis on accessibility, with a notable concentration in higher and postgraduate education, primarily driven by universities. While the analysis shows that most initiatives align with UNESCO’s third strategic objective—ensuring inclusive and equitable access—other key areas such as regional cooperation, the development of sustainable models, and institutional capacity-building are less prominently represented. This situation highlights the need to move toward a more comprehensive approach that not only prioritizes access, but also fosters sustainable, collaborative, and legally sound open practices.
Open Education and Science in the Digital Age: Virtual Reality and Competency Development in Physiology Learning within Health Sciences
This quasi-experimental study evaluates the impact of Virtual Reality (VR), implemented as an open educational resource, on teaching physiology to Health Sciences students. Recent studies have shown that immersive technologies enhance conceptual understanding and increase students’ active engagement; however, their adoption remains limited in formal higher education contexts. Building on this background, the present study seeks to confirm these benefits and examine whether integrating VR into the classroom contributes to developing additional generic competencies relevant to professional performance in dynamic environments. An experimental group (VRG, n = 100), which used classrooms equipped with VR technology, was compared with a control group (CG, n = 63), which followed the traditional dissection-based method. The results show a significant increase in academic performance and knowledge retention in the VRG (a 25.93% improvement compared to a 9.87% decrease in the CG), as well as a strengthening of generic competencies such as practical application, autonomous learning, adaptability to change, decision-making, and collaboration. This research aligns with the goals of the UNESCO Dubai Declaration on Open Educational Resources, by highlighting VR’s potential to democratize access to knowledge and foster the development of open, inclusive, and sustainable educational and scientific ecosystems.
Sustainability Models for Open Educational Resources: A Pioneer Study Based on Interactive Media in Alignment with the 2024 Dubai Declaration
Open Educational Resources (OER) are openly licensed teaching, learning, and research materials that can be freely accessed, adapted, and redistributed to promote inclusive and equitable education. The 2019 UNESCO Recommendation on OER, adopted by Member States, outlined five strategic action areas, including the development of sustainable models (Action Area 4) to ensure the long-term viability of OER initiatives. Building upon this framework, the 2024 Dubai Declaration reaffirmed the global commitment to OER by emphasizing digital equity, sustainability, and cross-sector collaboration as essential principles for transforming education systems worldwide. This study investigates sustainability models for OER through a pioneering intervention that aligns with the 2024 Dubai Declaration and Action Area 4 of the 2019 UNESCO Recommendation on OER. Conducted during the UNESCO Stay 2025 event at Tecnológico de Monterrey, the research engaged over 100 professionals from higher education, government, civil society, and industry in a structured interactive workshop. A mixed-methods approach was employed, incorporating pre-tests and post-tests alongside a collaborative digital media space, to assess participants’ understanding and co-create practical strategies for sustainable OER ecosystems. The theoretical framework addressed four dimensions: sustainable environmental approaches, digital public goods, green computing, and interoperability. Results revealed a significant increase in participants’ knowledge, with teams proposing diverse solutions including the use of renewable-powered digital infrastructure, crowdfunding, institutional cost-sharing, open licensing standards, and cross-sector governance mechanisms. The participants’ reflections indicated a shift from conceptual awareness to actionable proposals, reinforcing the feasibility of implementing sustainable models in educational projects. Findings emphasize the need for educational institutions and policy-makers to adopt integrated sustainability frameworks that combine environmental responsibility, financial resilience, inclusive governance, and digital interoperability. While the study’s scope was limited to a regional cohort and a short duration, the results provide foundational insights into building resilient OER strategies. The research highlights the relevance of collaborative stakeholder engagement and digital innovation in shaping future-ready, sustainable education systems. Future investigations should expand longitudinally and geographically to enhance the scalability and traceability of sustainable OER initiatives.
Open Educational Practices as Digital Public Goods: Promoting Resilience, Equity and Innovation in Higher Education Ecosystems
Open Education (OE) plays a crucial role in advancing the United Nations’ vision for Digital Public Goods by fostering equitable, inclusive, and resilient higher education systems. While the global policy discourse often centres on Open Educational Resources (OER), OE encompasses a wider spectrum of Open Educational Practices (OEP) that include co-creation, inclusive pedagogies, care-centred teaching, and accessible learning design. These practices cultivate communities of open practice and promote systemic transformation in education through collaboration and innovation. This paper addresses policy-makers, institutional leaders, and educators seeking to better understand and support OEP within broader digital and open education agendas. It argues that to maximise OE’s impact as a Digital Public Good, policies must move beyond an OER focus to engage with the full range of open practices emerging from grassroots and academic communities. Drawing on a thematic and integrative review of international frameworks—including UNESCO Recommendations and UN development agendas—we examine the conceptual evolution of OEP and its practical implementation across diverse contexts. By analysing existing policy frameworks and synthesising inclusive, ethics-informed models of openness, the paper contributes new insights into how OE governance can align more closely with the lived realities of educators and learners. In doing so, it offers evidence-based recommendations for rethinking OE policies to reflect the complexity, creativity, and transformative potential of OEP.
Optimize to Open: An Exploratory-Experimental Approach to the Computational Optimization of Open Large Language Models for Educational Access
The rapid integration of artificial intelligence into open education has intensified global demands for equitable access, sustainable infrastructure, and technological inclusion. This study evaluated the feasibility and educational impact of optimizing Open Large Language Models (OLLMs) for deployment in low-resource learning environments. Five open-source models (Falcon, Bloom, GPT-NeoX, T5, and Flan-T5) were optimized using an exploratory-experimental approach with unstructured pruning and Retrieval-Augmented Generation (RAG). The intervention was tested in three simulated educational infrastructures (public university, community digital center, and rural classroom) and analyzed using quantitative metrics on system efficiency and educational output. The findings revealed: (a) a reduction of up to 11% in response time across all models; (b) a decrease of approximately 20% in RAM and VRAM usage; (c) a 1.4% improvement in the educational relevance of responses; and (d) a 33% increase in query throughput, indicating greater scalability in open education contexts. These results offer practical and ethical guidance for educators, policymakers, and technology developers by showcasing how optimized OLLMs can become key enablers of worldwide open, inclusive, and sustainable learning ecosystems.
TOLUCATRAIN VR 1.0: Implementation and Evaluation of an Open Educational Resource for Railway Training
This article presents the development and functional evaluation of TOLUCATRAIN VR 1.0, an immersive Open Educational Resource (OER) aimed at technical railway training. The proposal aligns with the open science and education movement, integrating Virtual Reality (VR) technologies as a strategy to democratize access to specialized knowledge in contexts with limited physical infrastructure. The proof of concept (Technology Readiness Level 4 /TRL4) was implemented at two campuses of the Instituto Politécnico Nacional using a mixed-methods approach, including quantitative instruments (System Usability Scale/SUS scale and pre/post knowledge test) and qualitative testimonies. Results indicate high usability, significant improvement in technical learning, and strong user appropriation of the content. Moreover, the open, sovereign, and contextualized nature of the resource stands in contrast to closed commercial models. The study concludes that this type of OER can be scalable and adaptable to other sectors, with recommendations for future steps including longitudinal validation, progressive curricular integration, and enhanced accessibility.
From Niche to Regime: Rethinking Openness in the Age of Artificial Intelligence
In this paper, we critically evaluate the evolving process of Open Education (OE) amidst the ongoing proliferation of Artificial Intelligence (AI). The Multi-Level Perspective (MLP) framework developed by Geels (2002) is utilized in the present analysis of contemporary calls for “openness” in AI, with a focus on the concepts of democratization, cost-effectiveness, sustainability and decentralization. Moving beyond a binary framing of openness as either commercialized or emancipatory, the analysis conceptualizes openness as a contested imaginary shaped by a diverse array of actors. Furthermore, we aim to draw parallels with historical OE and Open Science (OS) developments and identify recurring socio-technical challenges. The analysis conducted reveals a persistent disconnection between landscape aspirations, niche innovations, and unruly educational regimes. It is argued that the readjustment of these levels necessitates a robust theoretical and philosophical foundation for imaginaries of ‘openness’, through which strategic investments in open infrastructure and context-specific policy development can be applied. The paper offers a more balanced and theoretically grounded framework for rethinking openness in the age of AI by integrating critiques from the state-led instrumentalisation of openness.
Active Learning, Mentoring and AI- Open Educational Resources: A Case Study in a Virtual Laboratory
Active learning strategies integrated with generative Artificial Intelligence (AI) technology applied to Open Educational Resources (OER) represent an advancing approach to the evolution of open education in response to digital-era demands. From this perspective, the objective of this paper is to examine how mentoring interventions, framed as an active learning strategy, contribute to the collaborative development of a generative AI-based OER within the context of a virtual social innovation laboratory. A qualitative case study was conducted using a digital ethnographic approach, complemented by participant observation to understand the patterns of digital collaboration group dynamics and mentoring interventions within this context. Mentoring was analyzed using a structured framework that supported the interpretation of interpersonal dynamics and developmental processes. The results illustrate how an OER including a chatbot, manual, video, and website emerged through interdisciplinary collaboration supported by structured mentoring. The findings demonstrate a possible way for generative AI tools to support authentic tasks. In particular, the OER developed in this laboratory was designed to assist human resources management by AI. This research contributes to a growing body of knowledge on how generative AI can support open education, offering insights into the design of AI-enhanced educational tools and collaborative authorship.
AI and Learning with AI: University Students’ Metaphorical Conceptualizations
The introduction of artificial intelligence (AI) in people’s lives, including in educational settings, is happening rapidly and on a massive scale. However, AI represents a complicated and abstract concept for laypeople and is, in its entirety, still quite unfamiliar to many, including students in higher education. Metaphors may facilitate the comprehension of novel or abstract concepts in terms of something already known, and help investigate implicit beliefs that have the potential to influence an individual’s actions. This study explored undergraduate students’ (n = 124) perceptions of AI and of learning with AI by analyzing metaphors collected following an established metaphor elicitation paradigm. Students’ attitudes towards AI, AI content knowledge, and usage of AI tools were assessed. The qualitative analysis of metaphors of AI yielded nine categories (e.g., brain, human, machinery, unknown), while the analysis of metaphors for learning with AI yielded seven categories (e.g., self-regulation, educator, shared learning). Overall, the anthropomorphization of AI for both foci was observed. Many conceptualized learning with AI as learning with trustworthy support, and foregrounded the perceived facilitation of learning on the basis of AI. This study highlights the importance of fostering accurate conceptualizations of AI and its role in learning, while addressing misconceptions and overly simplistic representations. Promoting a nuanced understanding of AI is essential to ensuring its effective use as a tool that enhances, rather than impedes, learning processes.
Fear and Awe: Making Sense of Generative AI Through Metaphor
In this paper, we advance the examination of generative AI (GenAI) in educational contexts in two distinct ways. First, we introduce and evaluate an innovative workshop model designed to explore GenAI metaphors, helping participants to articulate their own and their peers’ responses to the technology. These workshops included students, academics and educational support staff at a large Australian university. Second, we analyse the metaphors and collaborative discussions generated during these workshops, which reveal a diverse spectrum of perspectives on GenAI, from practical tool to existential threat. Our analysis surfaces tensions that align closely with prevailing attitudes and current literature on metaphor and GenAI, particularly the tensions between human versus machine agency, and the known versus the unknowable capabilities of the technology. Through these contributions, we propose a qualitative approach that maps the complex interplay of perceptions surrounding emerging technologies, inviting critical reflection on GenAI’s ethical and societal dimensions. Our work offers a structured yet flexible approach for facilitating meaningful dialogue about the implications of GenAI in education that moves past fear and awe.
The Staging of AI: Exploring Perspectives About Generative AI, Creativity and Education
In this article we investigate the role of generative AI in education with a focus on creativity, metaphorically utilising relevant features from Augusto Boal’s Forum Theatre as part of a participatory qualitative inquiry. Presenting three distinct perspectives—Gatekeeper, Evangelist, and Diplomat—our article explores emotional and intellectual responses to AI and creativity, utilising theatrical forms to offer personal insights about the intricate balance between AI’s benefits and risks. Adopting a post-qualitative approach, we avoid forced consensus, instead weaving individual viewpoints with a reflective commentary that seeks to elucidate and critically engage with the ideas presented. The adoption of Forum Theatre as a metaphor for our inquiry serves to deepen our understanding of AI’s transformative potential in educational settings and highlights the need for a collaborative, dialogic and critical approach to AI in education in a time of global change, one that honours the diversity of opinions in this evolving domain.
Reflecting Reality, Amplifying Bias? Using Metaphors to Teach Critical AI Literacy
As educational institutions grapple with questions about increasingly complex Artificial Intelligence (AI) systems, finding effective methods for explaining these technologies and their societal implications to students remains a major challenge. This study proposes a methodological approach utilising Conceptual Metaphor Theory (CMT) and UNESCO’s AI competency framework to develop activities to foster Critical AI Literacy (CAIL). Through a systematic analysis of metaphors commonly used to describe AI systems, we develop criteria for selecting pedagogically appropriate metaphors and demonstrate their alignment with established AI literacy competencies, as well as UNESCO’s AI competency framework. Our method identifies and suggests four key metaphors for teaching CAIL. This includes AI as a funhouse mirror, a map, an echo chamber, and a black box. Each of these metaphors seeks to address specific characteristics of GenAI systems, from filter bubbles to algorithmic opacity. We present these metaphors alongside pedagogical activities designed to engage students in experiential learning of these concepts. In doing so, we offer educators a structured approach to teaching CAIL that touches on aspects of technical understanding and provokes questions about societal implications. This work contributes to the growing field of AI and education by demonstrating how carefully selected metaphors can make complex technological concepts more accessible while promoting CAIL.
Assessment of Open Educational Resources Instruments: A Systematic Review
The measurement associated with Open Educational Resources (OER) represents one of the points to be addressed in the research agenda. This study aims to conduct a systematic literature review of studies that addressed the construction or validation of instruments on OER developed from 2018 to 2023. Through data collection in Elsevier, PubMed, and Google Scholar search engine databases, 17 studies provided reports of psychometric properties of scales measuring factors related to OER. The results show that, although few studies have been found, these have been increasing, and the scales present further evidence of reliability and validity. In conclusion, the measurement of OER is an area that should be addressed to a greater extent by researchers; having measurement scales with adequate psychometric properties leads to better empirical research results.
Editorial – Connected Learning in Contexts of Forced Displacement
Connected Learning in Contexts of Forced Displacement
Autotune for Knowledge: A Generative Metaphor for AI in Education
This paper explores how Donald Schön’s concept of generative metaphor can serve as a conceptual frame for problematising AI in education. Our focus is on the metaphor of AI as autotune for knowledge, as originally proposed by educator Dave Cormier. Through a close reading and exploration of the metaphor, we draw on Schön’s conceptual materials to surface underlying assumptions and reframe key issues at play in Cormier’s story. We show that the autotune metaphor, while intuitively appealing, oversimplifies the analogy between autotune as a tool for professional music-making and the relationship between expertise and use of AI tools. Drawing on a more nuanced view of autotune in music production, we elicit several points of conflict with Cormier’s original metaphor to generate a richer problematisation of issues posed by AI in education.
The Language on GenAI: A Critical Exploration of Personification Metaphors in UNESCO’s Guidance for Generative AI in Education and Research
This paper examines how UNESCO’s Guidance for Generative AI in Education and Research uses personification metaphors to describe artificial intelligence and how these linguistic choices shape public understanding of AI’s educational role. Through critical discourse analysis, we identify personification metaphors that attribute human characteristics to AI: biological traits, cognitive abilities, and leadership qualities. These metaphors make technology appear more relatable while risking overly optimistic, techno-deterministic perspectives. These metaphors also construct a narrow educational future where AI serves as an essential teaching partner, potentially encouraging over-dependence while reducing critical human oversight. Our analysis reveals three key concerns: framing AI as an autonomous entity capable of substituting human educators in resource-limited contexts could inadvertently widen existing disparities; language influences how institutions integrate AI technologies; and educational discourse needs more expansive and critical perspectives on AI’s appropriate role. The findings highlight the necessity for nuanced discussions about AI in education that acknowledge both opportunities and limitations.
A Metaphor for Rethinking Artificial Intelligence in/and Education
Like Alice’s journey through the looking glass, so-called “Artificial Intelligence” (AI) in education distorts familiar truths revealing uncomfortable reflections of systemic values and biases. Drawing on metaphor theories and ecological models of technology, the paper shows how dominant metaphors shape educational imaginaries and policy responses. It critiques the anthropomorphic rhetoric surrounding “AI”, arguing that common framings, such as “tool” or “tutor”, obscure its statistical nature and legitimize systems that entrench efficiency and control under the guise of neutrality. The mirror metaphor reframes these technologies not as “intelligent” but as reflective surfaces, exposing the cultural, political, and pedagogical assumptions coded into their design and deployment. Through this lens, technologies like LLMs, proctoring systems, and predictive analytics reveal distorted priorities—personalization that conceals standardization, automation that amplifies bias, and efficiency that overrides pedagogical depth. Crucially, the mirror reveals what remains unseen: emotional nuance, creativity, collaborative dynamics, and broader social context. These blind spots are compounded when institutions misread the reflection, adopting punitive or cost-saving policies that deepen existing inequities. Ultimately, the mirror metaphor serves as a catalyst, demanding we look beyond technical functionality to confront the societal reflection. It connects educational dilemmas concerning digital technologies to broader existential crises driven by capitalism and narrow definitions of progress. Arguing that reactive fixes are insufficient, the paper calls for a fundamental reimagining of education’s purpose towards ecological awareness, social justice, community empowerment, and critical pedagogy—using the mirror not just to critique, but to inspire the transformation of the educational systems and societal structures it reflects.
Mapping AI Literacy Frameworks: An Analysis of the Evolving Metaphorical Relationships between Students, Teachers, and AI
Rich metaphors abound within the growing AI literacy research landscape, and there is no better place to look for them than within the rapidly proliferating number of AI literacy frameworks. Conceptual metaphors and AI literacy frameworks, which outline the skills, competencies, and dispositions needed to engage critically with AI, complement each other by organizing people’s perceptions of this complex technological change and coordinating our actions in response. Through idiographic metaphor analysis, we coded the metaphors in eighteen AI literacy frameworks to uncover the underlying metaphorical relationships between AI, students, and teachers. We highlight the dominant metaphors for each actor: AI-as-tool-transformer-ubiquitary-artefact-threat; student-as-analyst-citizen-creator; and teacher-as-designer-guide. We then discuss the connections between these metaphors and their alignment with dominant educational paradigms. Finally, we discuss three tensions within the metaphors that address blind spots within the current corpus of AI literacy frameworks. We suggest areas for future research that address these tensions and consider our individual and collective capacity in higher education to shape or reject an AI-saturated future.