Conference Agenda
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29 SES 01 B: Looking for advances in arts education (I)
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29. Research on Arts Education
Paper Comparing Dance Students’ Use of Artificial Intelligence (AI) within the CEEPUS Network Arts in Motion. Extended Survey. Hungarian Dance University, Hungary Presenting Author:Having researched art students’ use of and attitudes towards artificial intelligence between 2024 and 2025 in five art disciplines at seven Hungarian art universities (the results of which we presented at ECER 2025), the question arose whether differences exist between dance students’ perceptions of AI at the institutions involved in our newly formed Arts in Motion CEEPUS Partnership, and whether the time that has passed has had an impact on dance students’ frequency or modes of using AI applications. We aim to investigate both commonalities and discrepancies in order to take action regarding educational practices and policies. Teaching should create learning experiences that encourage students to go beyond the already known and learn with constructive disobedience (Barad, 2003), even when using new technologies. AI tools, with their flexible and adaptive features, may meaningfully shape students’ engagement by offering personalized learning pathways and tailoring content to individual learners (Illingworth & Forsyth, 2026). However, ethical concerns may arise (Roe & Perkins, 2025) and should therefore be addressed. Methodology, Methods, Research Instruments or Sources Used The sample analysed includes dance students from the institutions of the Arts in Motion Central European Exchange Program for University Studies (CEEPUS) Partnership, formed in autumn 2025: the Hungarian Dance University (HDU) (n = 200) and two other small higher education dance institutions. One of them is the Belgrade Dance Institute (BDI), Serbia (n = 15), and data is also being collected from the Alma Mater Europaea Dance Academy, Ljubljana, Slovenia. The vast majority of students are between 18 and 25 years old. The adapted English version of the original (2025) online Microsoft Forms questionnaire was administered using the same platform for data collection. The survey included demographic and educational background items, as well as multiple-choice and five-point Likert scale questions on AI use and attitudes, supplemented by open ended items for further explanation. Participation was anonymous, and no personal data were collected. The quantitative data analysis is descriptive. Conclusions, Expected Outcomes or Findings Our preliminary results are in line with data published on the most frequently used AI apps (Németh, 2026), as dance students also most often use ChatGPT, Canva, DuoLingo and Grammarly. Students of the BDI, however, reported less frequent use of AI applications than HDU students: around 13% of BDI students, compared to 30% of HDU students, reported frequent or very frequent AI use. At the same time, 40% of BDI students reported rarely, and 25% of HDU students very rarely, using AI. These data seem to contradict the hypothesis that, over the time passed since the first survey, dance university students might have developed more frequent AI using habits. It is possible that regional factors play a more decisive role. There is also a difference in the self-reported types of AI apps used across universities: 82% of HDU students preferred ChatGPT over other apps, compared with 52% of BDI students. In the more recent survey among BDI students, the EatBetter app—potentially particularly useful for dancers—also appeared, marking a possible tendency toward more dancer focused AI usage. Although the research has limitations, partly due to the small number of participants at the smaller dance universities involved, valuable information has been collected. The results may support collaborative efforts to update AI policies and educational practices in order to address ethical concerns and better meet educational needs. References Barad, K. (2003). Posthumanist performativity: Toward an Understanding of How Matter Comes to Matter. Signs: Journal of Women in Culture and Society, 28(3), 801–831. Illingworth, S., & Forsyth, R. (2026). GenAI in Higher Education: Redefining Teaching and Learning [Published online]. Bloomsbury Academic. https://doi.org/10.5040/9781350535824 Németh, Z. [Dr. Prezi]. (2026, January 4). A legyakrabban használt AI alapú appok, a havi látogatószám alapján. [The most Frequently Used AI Applications Based on Monthly Visitor Numbers.] https://tinyurl.com/wyxebjd5 Roe, J., & Perkins, M. (2025). AI and the Future of Education: Disruptions, Dilemmas and Directions. In UNESCO eBooks. https://doi.org/10.54675/keck1261 29. Research on Arts Education
Paper Creative MASS: Re-worlding Post-AI Creativity 1: Aalto University, the school of Arts, Design and Architecture, Finland; 2: Pennsylvania State University Presenting Author:This article examines the evolving discourse of creativity in the context of generative artificial intelligence (genAI), proposing the term MASS—Massive Abstract Statistical Systems—to critically reframe the role of genAI in creative practice. Drawing from literature across art education and computer science, the authors trace how creativity is conceptualized differently within these fields: as an embodied, culturally situated process in art education, and as a quantifiable, solvable question in AI research. Through comparative literature analysis of publications from arXiv, Studies in Art Education, and International Journal of Education Through Art, the study highlights tensions between human-centric, process-oriented notions of creativity and algorithmic, output-driven models characteristic of genAI. The authors argue that the rise of genAI reconfigures creative agency, moving from intuitive and situated practices to data-driven processes shaped by prompting, statistical modeling, and computational abstraction. They critique popular narratives that frame genAI as inherently creative, asserting that such claims obscure its material and ecological costs, ethical concerns, and lack of intentionality or authenticity. MASS is introduced as a conceptual tool to shift discourse away from misleading anthropomorphisms of AI, emphasizing the system’s statistical logic and infrastructural implications. The article concludes by calling for post-AI perspectives in art education—ones that critically engage with AI’s epistemologies, promote AI literacy, and foreground ethical and ecological considerations. Through this lens, creativity is not only redefined but re-worlded, opening new pedagogical and theoretical pathways for understanding the intersection of art, technology, and society in a computationally saturated era. Methodology, Methods, Research Instruments or Sources Used This study used a comparative literature analysis to examine how “creativity” is defined and operationalized across two intersecting knowledge communities shaped by generative AI: computer science research developing AI systems for creative applications and art education scholarship treating creativity as pedagogical, sociocultural, and embodied practice; the aim was not to measure creativity directly but to map the discourse of creativity—its assumptions, emphases, and omissions—and to identify tensions that become pronounced in a post-AI context. The authors constructed a corpus from three main sources: arXiv (as a high-volume, open-access repository representing AI development discourse), and two established art education journals—Studies in Art Education and the International Journal of Education Through Art (IJETA)—to represent disciplinary discussions of creativity in arts learning and teaching; they also used Google Ngram searches as contextual evidence of changing attention to “creativity” and the pairing “artificial intelligence + creativity” over time. For arXiv, the search strategy targeted the keywords “creative artificial intelligence” and “art” within computer science, using “art” to refine relevance and screening the initial returns to focus on creative-domain work; this process yielded 55 arXiv articles announced in 2024 that met the stated criteria. For the art education journals, the authors searched titles, keywords, and abstracts for “creativity,” then excluded articles centered on the “creative industry” or those not substantively engaging creativity as a concept; after exclusions, the art education sample comprised 52 articles (34 from IJETA and 17 from Studies in Art Education, as reported). The analysis proceeded qualitatively, comparing how texts define creativity, what frameworks they invoke, and whether creativity is treated primarily as process, product, pedagogy, a measurement problem, or situated sociocultural practice; findings were then synthesized into thematic discussions (including GenAI and creative practice, differentiating creative applications of AI, and sociocultural implications of GenAI) to support cross-field “boundary work” that surfaces persistent divergences—such as quantification versus embodiment and output evaluation versus situated process—informing the paper’s broader conceptual claims. Conclusions, Expected Outcomes or Findings The study finds a pronounced disconnect between how creativity is framed in AI research versus art education scholarship: across the reviewed arXiv corpus, creativity is commonly treated as a measurable, optimizable problem—something that can be improved through the right procedures, models, and evaluation metrics—whereas art education literature understands creativity as a relational, culturally situated, and embodied assemblage of human and non-human activity that cannot be reduced to output scoring alone. The authors also observe that creativity-focused discourse has surged in AI development communities (e.g., arXiv outputs and related trend indicators), while art education research on creativity appears comparatively outpaced—an imbalance that matters because computational definitions of creativity risk becoming dominant in public and institutional understandings of what it means to create. As a critical outcome, the article proposes reframing generative AI as MASS (Massive Abstract Statistical Systems) to counter misleading anthropomorphisms of “intelligence” and “creativity,” emphasizing instead the statistical-logical nature of these systems and their material and infrastructural entanglements. In terms of key findings for post-AI art education, the review highlights recurring tension points requiring “tactical intervention and critical scholarship,” particularly debates over authorship and agency in co-creation, intellectual property and claims of “labor theft” tied to training data, algorithmic bias and cultural misrepresentation, and the comparatively weak attention to ecological costs (energy, raw materials, and sustainability concerns) within AI-facing creativity discourse. The authors conclude by calling for post-AI perspectives in art education that build AI literacy while foregrounding ethical, cultural, and ecological considerations, asking how creative practice and arts learning are being reshaped now that LLM-driven tools are embedded in everyday creative workflows—and what those practices should become. References Allred, A. M., & Aragon, C. (2023). Art in the machine: Value misalignment and AI “art”. In International Conference on Cooperative Design, Visualization and Engineering (pp. 31–42). Springer. Anderson, R. C. (2018). Creative engagement: Embodied metaphor, the affective brain, and meaningful learning. Mind, Brain, and Education, 12(2), 72–81. Anderson, T., & Guyas, A. S. (2012). Earth education, interbeing, and deep ecology. Studies in Art Education, 53(3), 223–245. https://doi.org/10.1080/00393541.2012.11518865 Banaji, S., Burn, A., & Buckingham, D. (2010). The rhetorics of creativity: A literature review (2nd ed.). Creativity, Culture and Education. Craft, A. (2001). An analysis of research and literature on creativity in education. Qualifications and Curriculum Authority. Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press. Demir, C. (2005). Enhancing creativity in art education through brainstorming. International Journal of Education through Art, 1(2), 153–160. https://doi.org/10.1386/etar.1.2.153/3 Garoian, C., & Gaudelius, Y. M. (2001). Cyborg pedagogy: Performing resistance in the digital age. Studies in Art Education, 42(4), 333–347. https://doi.org/10.1080/00393541.2001.11651708 Gay, C. H., Figueroa-Sarriera, H. J., Mentor, S. (1995). The cyborg handbook. Routledge. Goetze, T. (2024). AI art is theft: Labour, extraction, and exploitation: Or, on the dangers of stochastic Pollocks. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 186–196). ACM. https://doi.org/10.1145/3630106.3658898 Lewis, T. (2024). The creative act in the studio: A plea for rethinking potentiality in art education. International Journal of Education Through Art. 20. 337-350.10.1386/eta_00172_1. Runco, M. A. (2023). AI can only produce artificial creativity. Journal of Creativity, 33(3), 100063. https://www.sciencedirect.com/science/article/pii/S2713374523000225 Williamson, B. (2024, November 8). Critical keywords of AI in education. https://codeactsineducation.wordpress.com/2024/11/08/critical-keywords-of-ai-in-educ ation/ Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223–235. https://doi.org/10.1080/17439884.2020.1798995 29. Research on Arts Education
Paper Policy Enactments and Spatial Configurations in Swedish Visual Arts Teacher Education 1: Södertörn University, Sweden; 2: HDK Valand - Academy of Art and Design, Sweden Presenting Author:In 2011, a major reform in Swedish teacher education substantially altered qualification requirements for primary school teachers in visual arts. Students enrolled in the general teacher education programme with a specialization in leisure-time pedagogy can now qualify to teach and assess visual arts up to grade 6 after completing only 30 ECTS credits in the subject, in contrast to the more extensive subject studies required for certification grades in 7-9. This paper is part of a broader research project that examines the consequences of this reform by analysing how visual arts education policies are enacted, negotiated, and locally configured across different teacher education institutions in Sweden. Departing from the notion that conceptions of visual arts as a school subject are not only articulated in policy texts and syllabi but also embedded in material and infrastructural arrangements, the case study presented in this paper focuses primarily on the spatial organisation of teaching environments in these institutions. The study is guided by the research question: How are conceptions of visual arts as a school subject enacted and negotiated through the spatial organisation of visual arts teaching facilities? More specifically, it explores how different configurations of studios, classrooms, storage rooms, equipment and material resources express and shape locally situated interpretations of national policies in visual arts education, and how these configurations contribute to the construction of distinct subject cultures within teacher education. Theoretically, the study draws on policy enactment theory (Ball et al., 2012), which conceptualises policy not as something implemented top-down, but as something that is interpreted, translated and enacted within specific institutional and cultural contexts. At the same time, enactment processes are shaped by power relations that construct and privilege particular conceptions of what visual arts education is and should be. From this perspective, the enactment of the 2011 teacher education reform can be understood as a complex process in which teacher educators select, interpret and translate national policies into local syllabi, spatial arrangements and teaching practices. These enactments give rise to locally specific subject cultures, shaped by historical traditions, institutional resources and professional identities, while simultaneously reflecting broader structures of governance and control embedded in contemporary education policy. In this paper, particular attention is paid to the material/spatial policy enactments and how they in turn privilege certain pedagogical practices, subject traditions, and forms of knowledge while constraining others. Although empirically grounded in a Swedish case, the study addresses issues of clear European and international relevance. Across many educational systems, visual arts and other art subjects face challenges related to reduced instructional time, changing qualification requirements and shifting priorities in curriculum reform. By highlighting the relationship between policy, material conditions and teacher agency, the paper contributes to broader debates about the status and role of arts education in schools undergoing structural and ideological change. By making visible the conditions under which visual arts education is shaped, constrained and transformed in contemporary policy contexts, the study contributes with insights that may inform both teacher education and compulsory school development. Methodology, Methods, Research Instruments or Sources Used In order to make the material conditions of visual arts education visible and possible to analyse, the study adopts a visual ethnographic approach. Visual ethnography can help direct attention towards aspects of mundane spatial and material arrangements that are otherwise often taken for granted or forgotten (Pink 2021; van den Scott 2018). As proposed by Pink et al. (2018), visual documentation is particularly useful for exploring the relationships between everyday practices and more policy-driven narratives in different fields of society. In educational contexts, this approach makes it possible to examine how official accounts of reform and curriculum are translated into, or come into tension with, the material realities of teaching and learning. In this respect, visual ethnography can be used to access what Prosser (2007) refers to as “the visible but hidden curriculum” of schools. This includes forms of visual culture and spatial organisation that are fully observable, but whose influence on teaching practices and pedagogical possibilities often escapes explicit attention. As emphasised by Prosser, such material conditions are not limited to formal teaching spaces, but also include non-teaching areas, such as storage rooms and other adjacent facilities, which play a central role in structuring everyday educational work. Empirically, the study draws on photographic documentation of teaching facilities for visual arts education at seven higher education institutions offering teacher education in Sweden. The material includes both wide-angle photographs of entire teaching spaces and close-up images of specific material arrangements, equipment and storage practices. It is important to point out that the analytical process begins already in the moment of photographing, as the selection of what to document involves an initial interpretation of what is considered analytically relevant. The visual material is therefore not treated as neutral representations, but as situated and theoretically informed materials shaped by the analytical choices made in the moment of documentation (Pink, 2021). The photographs are further contextualised through field notes based on conversations with teacher educators conducted during guided walks through the facilities. Analytically, the material is interpreted through a policy enactment lens, focusing on how conceptions of visual arts as a school subject become visible in spatial arrangements and material configurations. Rather than treating teaching facilities as direct translations of policy, the analysis approaches them as sites where educational policy is both enacted and challenged through everyday material organizations. Conclusions, Expected Outcomes or Findings The preliminary analysis reveals substantial variation between institutions in how visual arts teacher education is materially and spatially organised. Teaching facilities varied in terms of size, equipment, and spatial layout, resulting in significantly different conditions for teaching and learning across institutions. These differences can be understood as spatial expressions of a “hidden curriculum” where inherited material arrangements and environments continue to structure pedagogical possibilities. Within these variations, tensions between different conceptions of visual arts as a school subject can be identified. On the one hand, both policy documents and most teacher educators participating in the study frame visual arts education as a visual culture subject, oriented towards contemporary image creation practices and critical visual literacy. On the other hand, this orientation coexists with a continued emphasis on more traditional craft-based practices, embedded in traditionally furnished and equipped art classrooms. A further finding concerns how negotiation and enactment of policy takes place not only through spatial organisation but also through everyday practices of use and non-use. Certain artefacts or spaces, such as kilns or darkrooms, remain physically present but are repurposed, only occasionally used, or used in ways that differ from their original pedagogical intentions. These practices reveal how inherited infrastructures are pragmatically adapted to new curricular priorities, and how policy enactment unfolds through everyday decisions. The analysis also points to an emerging ambition to align visual arts teacher education more closely with the material conditions of current compulsory education. In several sites, increased use of recycled and low-cost materials reflects an attempt to prepare future teachers for the resource constraints typical of primary schools. While this alignment may enhance professional relevance, it also raises questions about the extent to which teacher education risks normalising restricted conditions and lowering expectations regarding the material and symbolic status of the subject. References Ball, S. J., Maguire, M., & Braun, A. (2012). How schools do policy: Policy enactments in secondary schools. Routledge. Pink, S. (2021). Doing visual ethnography. 4th Ed. SAGE. Pink, S., Fors, V., & Lindgren, T. (2018). Emerging technologies and anticipatory images: Uncertain ways of knowing with automated and connected mobilities. Philosophy of Photography, 9(2), 195–216. Prosser, J. (2007). Visual methods and the visual culture of schools. Visual Studies, 22(1), 13–30. van den Scott, L.-J. K. (2018). Visual Methods in Ethnography. Journal of Contemporary Ethnography, 47(6), 719–728. 29. Research on Arts Education
Paper Value Wheel Integrating Knowing Through Art into Complex Interdisciplinary Design and Development Projects Aalto University, Finland Presenting Author:This research paper focuses on the linkage between knowledge through art and interdisciplinary design and development processes that can be fuelled and leveraged by art. The research introduces a conceptualization of the Value Wheel within the new interdisciplinary pedagogical and operational model (Haapaniemi & Leinoen, 2023). The Value Wheel highlights how socially engaged and responsible artistic knowing processes and art-based research (ABR) methodologies including performative inquiry and drama pedagogy, can serve as catalysts for meaning-making in complex interdisciplinary development projects and educational ecosystems and integrate broader societal stakeholders, such as enterprises or youngsters at schools. The Value Wheel explains the nwly estblished pivotal role of knowing through art, art-based research methods (ABR) and explaines the possible roles of art in RDI development projects and in interdisciplinary meaning-making processes in both development work and design university context. Art-based methods act as disruptors, crystallizers, and stimulants in educational and developmental processes. They spark curiosity, invite emotional engagement, and embrace the unknown through metaphor, collision, and creative friction. These elements open new perspectives and allow participants to dwell in liminal spaces – transitional states where transformation begins. Such states are vital in navigating and managing the ambiguity and emergence inherent in interdisciplinary design projects. Art functions as a powerful medium for communication, expression, and knowledge creation across multiple disciplines. Depending on the situation, project and utility it plays a therapeutic role, contributes to development processes, and engages in social discourse through diverse forms and methods. Knowledge through art is generated via socially responsible and socially engaged art methodologies to integrate broader societal stakeholders. Art as communication and expression: Art conveys messages, ideas, and emotions in various forms, serving as a vital tool for communication and personal expression. Powerful narratives: Different art forms, methods, and materials act as communication tools, creating and emphasizing worlds of meaning and values, including through new media, interactive spaces, and the fusion of design, art, and technology. Interdisciplinary knowledge and development: Art supports research and knowledge production within multidisciplinary models. Knowing through art can be integrated into development processes to drive change. Socially responsible art enhances engagement and participation: Community art, socially responsible art and artwork engage with societal processes, promoting community, empathy, and understanding. This interaction reflects strategic values guiding individuals and organizations. Methodology, Methods, Research Instruments or Sources Used Action research (Somekh, 2012) in designing the Value Wheel in iterations within two RDI projects. Art-based research (ABR), art workshops, performative inquiry and drama pedagogy utilized in generating rich qualitative materials that constitute to value creation through artistic means. This generated material serves as research data and output of the value mappings via art. Teams cycle through Observe–Plan–Act–Reflect phases with both creative arts exercises and design prototyping tasks intertwined (Haapaniemi & Leinonen, 2023). Conclusions, Expected Outcomes or Findings A visualization that conceptualizes the Value Wheel with two blades: one that generates knowledge through art and ABR and the other with co-design and design briefs. The two blades spin as the process progresses. The right blade consists of interdisciplinary co-design processes in four Design Briefs representing the four parallel inquiry tracks undertaken by the teams. Each design brief focuses on creating tangible, digital and experiential outcomes with prototypes. The left blade generates value-laden narratives through art. This side represents all the preparatory arts-based interventions – such as drama workshops, storytelling sessions, and visual art exercises – that occur before and alongside design ideation. The goal is to create rich narrative material infused with human values. At the center of the Value Wheel is a “value circle” or hub where the two blades intersect. This hub represents the iterative innovation cycle and shared learning that happen when art and design integrate. As teams work, the wheel keeps turning and crystallized artistic knowing and created stories to inform design concepts, and as designs take shape, new questions arise that may be fed back as prompts for more art-based exploration. The Value Wheel model tolerates ambiguity and encourages iteration. It concretely links art-based activities with interdisciplinary co-design iterations so that artists, designers, technologists, sustainability experts and all involved are essentially co-creating from start to finish. References Appadurai, A. (2023). Disjuncture and difference in the global cultural economy. In Postcolonlsm (pp. 1801-1823). Routledge. Cieciuch, J. (2017). Exploring the complicated relationship between values and behaviour. In Values and behavior: Taking a cross cultural perspective (pp. 237-247). Cham: Springer International Publishing. Dekker, E., & Morea, V. (2023). Realizing the values of art. Cham: Springer. Eisner, E. (2008). Art and knowledge. Handbook of the arts in qualitative research: Perspectives, methodologies, examples, and issues, 4. Eyal, T., Sagristano, M. D., Trope, Y., Liberman, N., & Chaiken, S. (2009). When values matter: Expressing values in behavioral intentions for the near vs. distant future. Journal of experimental social psychology, 45(1), 35-43. DOI: 10.1016/j.jesp.2008.07.023 Haapaniemi, H., & Leinonen, T. (2023). Towards a Pedagogical Model Applying Commedia dell’Arte and Art Workshops in Higher Education Design Studies. Open Education Studies, 5(1), 20220199. Leavy, P. (Ed.) (2025), Handbook of Arts-Based Research, Guilford Publications. Manders-Huits, N. (2011). What values in design? The challenge of incorporating moral values into design. Science and engineering ethics, 17(2), 271-287. DOI: 10.1007/s11948-010-9198-2 McDougall, M., Bevan, B., & Semper, R. (2012). Art as a way of knowing. In Conference Report. San Francisco: Exploratorium. Sherman, A., & Morrissey, C. (2017). What is art good for? The socio-epistemic value of art. Frontiers in human neuroscience, 11, 411. DOI: 10.3389/fnhum.2017.00411 Sinek, S. (2009). Start with why: How great leaders inspire everyone to take action. Penguin. Stec, T., & Zwolinski, P. (2018). Using values management for shifting companies to circular economy. Procedia CIRP, 69, 805-809. ISSN: 2212-8271; DOI: 10.1016/j.procir.2017.11.112 Straker, K., & Nusem, E. (2019). Designing value propositions: An exploration and extension of Sinek’s ‘Golden Circle’ model. Journal of Design, Business & Society, 5(1), 59-76. Sunarto, B. (2015). Basic knowledge and reasoning process in the art creation. Open Journal of Philosophy, 5(5), 285-296. DOI: 10.4236/ojpp.2015.55036 Swart, J. (2011). That’s why it matters: How knowing creates value. Management Learning, 42(3), 319-332. DOI: 10.1177/1350507610391591 Van de Poel, I. (2013). Translating values into design requirements. In Philosophy and engineering: Reflections on practice, principles and process (pp. 253-266). Dordrecht: Springer Netherlands. Vuyk, K. (2010). The arts as an instrument? Notes on the controversy surrounding the value of art. International journal of cultural policy, 16(2), 173-183. Yau, L. F. C. (2012). The arts in a knowledge economy: creation of other knowledges. Journal of the Knowledge Economy, 3(1), 68-87. DOI: 10.1007/s13132-011-0054-7 | ||