Call for submissions

AI in Media Education: Disruptions and Continuities

Media Education Research Journal  –  Special Issue

Major technologies tend to arrive with near-identical claims of wholesale disruption for education. The printing press, radio, television and the internet were all heralded as remaking the classroom, diminishing the development opportunities for students and potentially rendering those that teacher them obsolete. This same pattern has been repeated in the 21st century with pronouncements of intelligent tutors, virtual reality and MOOCs.

In 1986, Larry Cuban presciently traced this recurring pattern across a century of classroom technologies, identifying a four-stage cycle of exuberance, scientific credibility, disappointment, and the blaming of teachers. Justin Reich’s Failure to Disrupt (2020) drew the sobering and perhaps reassuring conclusion that technology alone does not simply transform education. Instead, educators play an active, if negotiated role, in integrating new technologies.

Artificial Intelligence (AI) has arrived wrapped in the same rhetoric of rupture, threating academic integrity, critical thinking and more. Between the expected disruption and what is actually happening on the ground, there is a widening gap. This special issue of MERJ invites the field to take stock, reflect on and to reconcile the real-world negotiations, tensions and trade-offs that are unfolding in practice.

We invite contributions relating to the role of AI in media education, making a distinction between teaching about AI (as an object of critical study), teaching through AI (as a tool for learning) and teaching against AI (as a site of principled resistance). We welcome contributions aligned to any one of these orientations, or to the relationships and tensions between them.

1. Teaching about AI

Media education has always had to keep pace with the industries its students go on to enter or critique. Here, we invite educators to submit contributions about how they have had reconciled and integrated AI into their existing teaching content. We welcome work that treats AI as an object of critical study and that contextualises its place in wider curricular.

Possible topics include, but are not limited to:

  • Algorithmic literacy: moving beyond basic fact-checking towards a deeper understanding of platform mechanisms, datafication and algorithmic manipulation.
  • Individualised news and AI curation: how AI-driven personal feeds shape the development of ’empowered citizens’ and the capacity to distinguish ‘news from noise’.
  • AI and institutional power: how AI’s integration into global platforms challenges established media education frameworks of ownership, representation and political economy.
  • Changing industry practice: how AI is reshaping professional workflows across journalism, production, design and communications — and how teaching content must track, and critically interrogate, the working practices students will enter or contest.
  • Generative AI, deepfakes and ethical engagement: teaching the societal repercussions of synthetic media and the deepfake crisis.
  • Digital divides in the AI era: how ‘deep mediatisation’ exacerbates or bridges disparities in media access, skills and socio-economic participation.

2. Teaching through AI

Here we ask how educators are integrating AI into their teaching practice. This covers the use of AI to produce the learning materials themselves, as well as putting AI in front of students as a medium for them to engage with. We are especially interested in accounts of what changes in the classroom, the studio and in assessments when educators and students are producing with and alongside AI.

Possible topics include, but are not limited to:

  • Designing with AI: how educators use AI to design and produce learning materials or activities differentiate or scaffold student tasks, and what is gained or lost in doing so.
  • Assessment redesign: reworking briefs, feedback and academic-integrity practices around generative tools.
  • AI as a learning medium: the role AI plays as a learning tool for students independently and / or within a structured learning environment.
  • Practice-based accounts: reflections from the studio, newsroom or production classroom on making with AI.
  • Learning-by-doing interventions: active, co-evaluated media literacy work in which students make with AI and reflect on the making.

3. Teaching against AI

Although this call situates AI within a long history of proclaimed ‘disruptive technologies’, we also invite grounded, reasoned accounts of friction and refusal. This does not extend to impassioned, reflexive rejection, but to cases where the consequences of AI’s adoption can be clearly articulated, where it does not belong, or where it belongs only on particular terms.

Possible topics include, but are not limited to:

  • The ethics of creative practice: where AI-generated, media threatens the training and professionalization of media makers at different stages of their career.
  • Critical pedagogy and AI: interrogating whose interests are served when AI is embedded in the design of student tasks and curricula.
  • Deskilling, labour and value: what is lost, and who bears the cost, when areas of media production are automated.
  • Institutional and industry pressure: the political economy of ‘adopt or fall behind’, and the case for slow, selective or refused adoption.
  • Policy and curriculum: how AI literacy is being contextualised into, or resisted by, formal school subjects and disciplinary frameworks.

Submission

For the special edition we will accept the following submission types:

  • Research Articles. Complete reports of qualitative, critical, empirical or action research studies (typically 5,000–7,000 words).
  • Research in Progress. Shorter ‘in progress’ reports on early/mid-stage research findings and/or methodologies. We particularly encourage doctoral students to submit here. (typically 1,500–3,000 words).
  • Educator Insights. Reflective accounts from educators, attending to the tensions and negotiations that arise within specific educational practices (typically 1,500–3,000 words).
  • Thought Pieces. Discursive pieces, interviews and dialogues that present focused argumentation relating to critical debates, philosophical reflections or ‘unsanctioned narratives’ (typically 1,500–3,000 words).
  • We also welcome suggested Book Reviews (typically up to 2,000 words).

AI Usage Statement and Guidance

This special issue takes AI seriously as an object of study and a matter of pedagogy, and we approach it with the same critical, evidence-led scrutiny we bring to any media technology. We welcome work that studies, uses, critiques or produces with AI. At the same time, MERJ upholds ordinary scholarly expectations of transparency and accountability. See here for further information: Submission guidelines

Submission Deadline: January 8th, 2027.

We welcome pre-submission queries or outlines. Please contact the editorial team at merj@bournemouth.ac.uk.