Conference Agenda

The symposium takes up the #ECER2026 theme and asks about changing ways of action and knowledge regarding Artificial Intelligence (AI) and its implications from a Media Education perspective. Our primary focus of research is (digital) media and educational contexts. Thus we will be looking at AI as a mediating instance in different fields of educational research and practice.

The first contribution by Petra Grell will highlight a historical perspective on AI in Education focussing on central questions on socio-technical aspects of the systems, practices of hyping and how to unmask AI-technology so that “magic crumbles away” and practitioners are enabled for critical use.

In the second contribution, Klaus Rummler and Colette Schneider Stingelin will raise issues on the distribution of knowledge to ‘the public’ through scientific journals. Their current project focuses on transforming Open Access content to multimodal content, dedicated to lay audiences, transformed by on-premises LLMs (i.e., AI).

In the third contribution, Anne Mette Bjørgen and Yvonne Fritze will present a project focusing on students and academic staffs’ experiences from using AI and chatbots (CB) in study work and in teaching. Based on qualitative interviews, the intention has been to gain more insight into students' and staff's expectations of and experiences with AI and CB, how this is shaped in relation to expectations in and outside the educational context, and how this can change practice. Three examples involving the use of AI will be discussed

In the fourth contribution, Caroline Grabensteiner and Alexandra Totter will present a comparative review of three teaching media that are currently used but usually analysed individually: Textbooks, Open Educational Resources (OER), and AI-powered platforms. In a comparative approach (looking at the teaching media themselves as well as the scientific discourse about them), they ask how teaching is addressed and mediated as a knowledge practice on a technological, pedagogical and content level.

In the symposium we discuss AI ecologies in different educational fields to get a better understanding of how knowledge practices are shaped in interaction with technologies. In a historical, theoretical and practical perspective, we shed light on the ways in which knowledge and technologies are intertwined, how they make a difference and where to take a closer look in order to not only follow the hype but get to the core of current educational change.

Hyping the newest technology as an omnipotent solution for human affairs or particularly educational challenges isn’t a new thing. Any older researcher in media education can give a couple of examples how in their career lifespan a new tool or idea entered the spotlight of public attention and was easily forgotten when the next omnipotent technical solution entered the stage. Gouseti (2010) called this another circle of hype, hope and disappointment. And she – as others – reminded us that we are often focus the short-term technical aspects (potentials or threads) and tend to ignore the long-term social consequences. The current discussion about technology in education focusses on Artificial Intelligence (AI). And our observations during our latest literature review about AI in Education (unpublished yet) shows the same bias. Sloane, Danks and Moss (2024) highlight that “hyping”, the generating of excitement by simply claiming capabilities is an activity done by multiple agents. This kind of „AI hyping structurally hinders efforts to consider AI as the sociotechnical system it is “ (Sloane et al. 2024, p. 671). Another challenge is the public discussion about AI (and AI in Education) that triggers beliefs of magic. You can follow Clarke (1968) and phrase that: „Any sufficiently advanced technology is indistinguishable from magic.“ (Clarke 1968; p. 255) However it was computer scientist Joseph Weizenbaum, who developed the well-known chat bot ELIZA, who reminded us, that it is our responsibility to unmask the programs, to explain “in a language sufficiently plain to induce understanding” and that “the magic crumbles away” once the technology stands “revealed as a mere collection of procedures, each quite comprehensible” (1968, p. 36). In my contribution to this symposium, I will provide a historical view on the discussion about AI in Education with a focus on three question: (1) In which way are the socio-technical aspects of the systems integrated (or ignored)?, (2) In which way can we identify practices of hyping? (3) In which way can we identify aspects to help practitioners to unmask and understand the technology so that “magic crumbles away”?

Clarke, Arthur C. (1968). "Clarke's Third Law on UFO's". Science. Vol. 159, Issue 3812, p 255. DOI: 10.1126/science.159.3812.255.c Clarke, Arthur C. (1973) Hazards of Prophecy: The Failure of Imagination. Collection Profiles of the Future. 1962, revised 1973, Harper & Row Gouseti, Anastasia: Web 2.0 and education: not just another case of hype, hope and disappointment? In: Learning, Media and Technology 35 (2010), Nr. 3, S. 351–356. – URL http://dx.doi.org/10.1080/17439884.2010.509353 Sloane, M., Danks, D. & Moss, E. Tackling AI Hyping. AI Ethics 4, 669–677 (2024). https://doi.org/10.1007/s43681-024-00481-y Wanner, T.; Palmer, E. (2015): Personalising learning: Exploring student and teacher perceptions about flexible learning and assessment in a flipped university course. In: Computers & Education 88 (2015), 354-369 Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45.

Klaus Rummler and Colette Schneider Stingelin will report from their Horizon Europe Project ‘MUTASK’, which will be led by Mikołaj Leszczuk (University of Krakow, PL) with partners from France and Switzerland. Relating to Media Education, one of the guiding questions will be, if it is possible to generate multimodal content from scientific Open Access journals targeted to lay audiences on different levels of comprehension with the help of Large Language Models (i.e., AI). Previous studies indicated that it is possible to generate lay abstracts from articles in scientific Open Access journals in coordination with the authors and editorial workflows (Rummler et al., 2026; Falkenberg et al., 2024; Stoll et al., 2022). Further studies indicate that lay audiences comprise of different levels of comprehension (c.f. Cousseran et al., 2024) that should be respected for the generation of content targeted towards them. Research at the interface between Communication Studies/Audience Research (Colette Schneider Stingelin) and Media Education (Klaus Rummler) will have to ask for ‘How to identify lay audiences and the different levels of comprehension’ for each selected scientific journal and ‘How do these identified audiences read and comprehend the presented educational content derived from those Open Access articles’.

Cousseran, Laura, Tausche, Sandrine, Jennewein, Nadja, Hadergjonaj-Strodthoff, Vanesa, & Schober, Maximilian. (2024). Fünf Fragen an die Erstellung von Personas. Im Rahmen des Projektes Digitales Deutschland. JFF – Institut für Medienpädagogik in Forschung und Praxis. https://digid.jff.de/magazin/transfer/fuenf-fragen-an-die-erstellung-von-personas/ Falkenberg, LJ, Joyce, PWS, & Soranno, PA. (2024). How to write lay summaries of research articles for wider accessibility. LIMNOLOGY AND OCEANOGRAPHY LETTERS, 9(2), 93–98. https://doi.org/10.1002/lol2.10373 Rummler, Klaus, Schneider Stingelin, Colette, & Hüsser, Angelica. (2026). Lay-Abstracts als Element auf dem Weg zu Open Science. Ansätze für eine zugängliche und laiengerechte Wissenschaftskommunikation. Kommunikation@gesellschaft, Open Access – kultur-und sozialwissenschaftlich gelesen. Stoll, M., Kerwer, M., Lieb, K., & Chasiotis, A. (2022). Plain language summaries: A systematic review of theory, guidelines and empirical research. PLOS ONE, 17(6). https://doi.org/10.1371/journal.pone.0268789

Sub-paper had to be withdrawn

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Teachers’ knowledge practice is intertwined with a complex media ecology. In this contribution, we address this practice as media actions in the classroom (Totter & Grabensteiner, 2025) and lesson preparation, both aiming at supporting learning processes. Teaching media are created for assisting those processes, while at the same time mediating them. Teachers develop different practices towards technological, pedagogical, and content aspects in knowledge construction. TPACK is therefore a reference point for researching different aspects of teaching media and teachers’ media action (Mishra & Koehler, 2006). This contribution presents a comparative review of three teaching media that are currently used but usually analysed individually: Textbooks, Open Educational Resources (OER), and AI-powered platforms. In a comparative approach (looking at the teaching media themselves as well as the scientific discourse about them), we ask how teaching is addressed and mediated as a knowledge practice concerning technological, pedagogical and content affordances. - Textbooks have a long tradition and are a cornerstone of classroom teaching. They are typically oriented towards the curriculum and undergo governmental approval processes. Nowadays, textbooks are usually curated and edited by experts while produced and owned by commercial publishers. Currently textbooks undergo processes of digitalization. They are transformed from books to platform-based teaching resources or digitally extended via PDF-twins (Kastornova et al., 2023). - Open Educational Resources are based on the notion of “knowledge as a social practice” (Mishra, 2025, S. 305) and are produced by experts as well as teachers themselves. Initially developed for higher education, OER have been adopted in schools. They are published on OER platforms and predicated as teaching materials that are freely accessible, adaptable, community-created, and ready for immediate classroom implementation. - AI-Powered platforms for teachers combine both textbook views on teacher practice through ready to use materials, as well as creative uses of AI tools. Some literature calls for new measures of teachers’ practices and media-related competencies in AI-PACK (Lorenz & Romeike, 2023) or AI-TPACK models (Xu et al., 2025). This suggests that AI-powered platforms may offer yet another perspective on teachers’ knowledge practice, as AI may also act as an expert rather than a teaching medium. The literature review provides the basis for designing an empirical project investigating teachers’ knowledge practice in relation to the media ecology of (digital) textbooks, OER and AI-supported platforms.

Kastornova, V. A., Shikhnabieva, T. S., Mukhametzyanov, I. S., Polyakov, V. P., Roslova, L. O., & Kozlov, O. A. (2023). From a paper textbook to a digital educational resource. The evolution of requirements. In A. Arinushkina, A. Morozov, & I. Robert (Hrsg.), The impact of digitalization in a changing educational environment (S. 127–139). IGI Global. (from-a-paper-textbook-to-a-digital-educational-resource). https://doi.org/10.4018/979-8-3693-0433-4.ch010 Lorenz, U., & Romeike, R. (2023). AI-PACK – Ein Rahmen für KI-bezogene Digitalkompetenzen von Lehrkräften auf Basis von DPACK. Lecture Notes in Informatics (LNI), 11–24. Mishra, P., & Koehler, M. J. (2006). Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x Mishra, S. (2025). A Review of Reviews on Open Educational Resources. Open Praxis, 17(2), 305–325. https://doi.org/10.55982/openpraxis.17.2.851 Totter, A., & Grabensteiner, C. (2025). Digitales Lehrmittelhandeln als Medienhandeln zwischen Struktur und Agency: Eine Analyse medialer, zeitlicher und räumlicher Aspekte. MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung, 103–128. https://doi.org/10.21240/mpaed/jb22/2025.11.26.X Xu, G., Yu, A., Gao, A., & Trainin, G. (2025). Developing an AI-TPACK framework: Exploring the mediating role of AI attitudes in pre-service TCSL teachers’ self-efficacy and AI-TPACK. Education and Information Technologies, 30(15), 22471–22495. https://doi.org/10.1007/s10639-025-13630-5