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This paper discusses data governance models for educational platforms that could better protect students’ and teachers’ privacy and reduce data management burdens for teachers and administrators. Within an ethnographic study involving four Swedish secondary schools and municipal- and national-level administrators working with educational technology, we conduct qualitative interviews informed by educational data-tracing activities done with the help of computational methods from infrastructure studies. We highlight the extractive nature of the current data governance model, and demonstrate the power imbalances inherent to it, the uncertainties surrounding big tech companies’ data management practices, the burdens placed on teachers and administrators, and the fragmentation of the data/platform ecosystem. This allows us to engage in conceptual analysis of the desirability and feasibility of three alternative data governance schemes as applied to education: personal information management systems (which enable individuals to make data-related decisions), data trusts (expert bodies handling data governance in a fiduciary way) and data cooperatives (which steward data in a decentralised fashion through participatory and democratic decision-making). We conclude that data trusts offer the best response to the concerns identified through our infrastructural and ethnographic study, while also being the most feasible to implement in a variety of school systems.

Set in the near future, this chapter takes an adversarial design fiction approach to examine how ‘intelligence as infrastructure’ reorganises education. A fiction of artificial intelligence (AI) empire explores the financialisation of schooling exposed by labour market upheaval, the fragmentation that follows as municipalities depend on opaque platform providers, and a state response that asserts algorithmic nationalism through a civic foundation model-based AI system. As the story progresses, decision-making moves away from classrooms into financial, technical, and security infrastructures, raising questions of accountability, auditability, and sovereignty. The method is speculative rather than predictive, exploring design fiction and adversarial design to stage value conflicts that remain largely invisible in routine practice. Conceptually, the chapter extends platform studies in education by treating AI foundation models as upstream infrastructures. Practically, it renders discussable which arrangements of policy, procurement, and pedagogy might protect public values when learning depends on privately owned, algorithmic systems. Although situated in Sweden, the analysis has broader relevance for education systems wrestling with digital sovereignty, corporate dependency, and interest in human-centred practices. It closes with provocations on ownership and obligation, education after delegation, and counter infrastructures that support plurality, accountability, and creative civic life in schools.

This study aims to develop a set of heuristics tailored for evaluating learning analytics in simulation-based professional learning, focusing on the following research questions: (1) What heuristics are appropriate for evaluating learning analytics in simulation-based professional learning contexts? (2) How can theoretical frameworks and empirical findings be combined in the development of such heuristics? (3) How can expert evaluation inform their refinement and applicability? The study combines a top-down approach, drawing on a theoretical framework for learning experience design, with a bottom-up analysis of empirical findings from prior studies in the context of a design project. An initial set of heuristics was iteratively reviewed and refined in collaboration with experts in user and learning experience design. The outcome is a detailed heuristic framework that supports the evaluation of learning analytics in simulation-based settings and accounts for the technological, pedagogical, and social dimensions of professional learning.

Background The metaverse has the potential to transform healthcare and healthcare education by offering immersive, interactive experiences. As research on the metaverse rapidly expands, a synthesis is required to understand its current state, trends, and future directions in healthcare. Methods We conducted a mapping review of existing review studies on the metaverse in healthcare using topic modeling, hierarchical clustering, and qualitative interpretation. This was complemented by computational text analysis to examine thematic developments and structural patterns. Results The analysis yielded three distinct clusters: (1) immersive therapeutic and educational applications with intelligent integration, (2) immersive technologies for surgical training and clinical simulation, and (3) integrated, immersive, and intelligent technologies for personalized, networked healthcare. These clusters illustrate a shift from conceptual exploration toward applied, system-level integration. Applications show promise in mental health, surgical education, and personalized care, among others, but the evidence is preliminary. Key risks include privacy concerns, governance gaps, and equity challenges. Conclusions As enthusiasm for metaverse technologies grows, it is crucial to ensure that optimism does not outpace evidence and readiness. The metaverse offers significant opportunities for human-centered healthcare and professional training, but it requires rigorous validation, ethical frameworks, and inclusive design. To ensure responsible adoption and a sustainable impact, it is critical to align developments with the WHO's strategic objectives of collaboration, implementation, governance, and human-centered systems.

Citiverses offer virtual environments for regulatory learning via experimentation with governance, policy, and technology scenarios in safe, immersive settings. This paper proposes a science-for-policy agenda for regulatory learning in citiverses, developed through an expert consultation and informed by the literature and by international policy frameworks from the European Union and the OECD. It identifies four key research areas, including scalability, real-time feedback, complexity modelling, cross-border collaboration, risk reduction and citizen participation. In addition, the paper outlines a set of experimental topics, spanning transportation, urban planning and the environment/climate crisis, that could be tested in citiverse platforms to advance citiverse-enabled regulatory learning in these domains. The agenda emphasizes a responsible, human-centred approach, prioritizing ethical, social, environmental, and governance [ESG] considerations to inform future policy. To our knowledge, this is the first work to explicitly introduce regulatory learning as a citiverse use case, thereby contributing to ongoing debates on people-centric digital governance and the future of experimental policymaking in smart cities.

Hannes Lundkvist och Per Apelmo beskriver i sin text tillämpandet av en modell, på samma gång pedagogisk och vetenskapligt metodologisk, av författarna identifierad som en gestalt vilken de kallar ”musik-dikt-tystnad”. Gestaltens sammanhang kan vara pedagogiskt eller terapeutiskt. Utgångspunkten är deltagarna själva och deras livssituationer, den ”intra-aktion med andra människor, ting, ljud, känslor, erfarenheter” i vilken de som människor alltid befinner sig och blir till.

Despite the increasing interest in learning analytics over the past decade, there remains relatively little integration with pedagogical practice in higher education. The limited engagement of teachers in the design and development of teacher facing dashboards has been cited as a significant issue. As the purpose of a teacher facing dashboard is to enable deep insights into student learning as a basis for data-driven decision making, successful integration depends on compatibility with pedagogical needs and intentions. In this paper, we outline findings from a series of focus groups with nautical simulator instructors ( n = 12) from three different universities in Sweden, Norway and Finland. During focus groups, the design concept of multimodal learning analytics was presented and discussed, with focus on the usefulness of a teacher-facing learning analytics dashboard in addressing typical instructional concerns during simulation-based training. In the analysis, we focus on the juxtaposition between user wants, needs and resistance, prioritizing the simulator instructors’ pedagogical concerns in learning analytics design. The findings highlight a crucial gap between the technological capabilities of learning analytics and the practical, everyday challenges of teaching in simulation-based environments. To bridge this gap, it is essential to design dashboards that are not only professionally intuitive and data-rich but also adaptable to the specific pedagogical strategies of instructors. Ultimately, successful implementation depends on a user-centred design process that integrates instructors’ perspectives, ensuring that learning analytics tools align with the complexities of simulation-based training.

As the digital landscape of education continues to evolve, learning analytics has become an integral tool for understanding, measuring, and improving student outcomes. However, a significant gap remains in the design and implementation of these technologies, particularly in their ability to cater to the diverse cognitive and neurological profiles of students. This conceptual paper highlights the need for a neuroinclusive approach to learning analytics, arguing that current practices in educational technology risk excluding neurodivergent students by reinforcing a neurotypical-centric design. In doing so, the paper highlights the limitations of existing frameworks and offers suggestions for how learning analytics can become more inclusive to better serve all students, especially those with undiagnosed or undisclosed neurodivergence.

The impact of Large Language Model (LLM) based chatbot use on university students’ writing receives considerable attention in current research. One significant strand investigates how LLMs can support writing performance (Li et al, 2025) and literacy practices (Anson, 2024; Zakirova & Bedeker, 2025). Another focuses on specific writing strategies, including feedback (Khuder, 2025), student voice (Singh et al., 2025), and text-editing (Perez, 2025). While existing research shows that LLMs can become meaningful partners in students’ writing processes, fewer studies have explored what LLM-mediated writing processes constitute in terms of students’ situated work. Given that writing with LLMs exemplifies a textually organized, mediated, and epistemic practice (Prior, 2006), this study aims to explore how students engage in these emerging activities (cf. Prior & Thorn, 2015). How do students initiate and frame academic writing in relation to LLMs? What forms of agency do they adopt? To gain access to students’ ongoing work with LLMs, the study was designed as an extracurricular intervention conducted as a writing workshop for second-cycle students. Participants were invited to use LLMs unreservedly. Nine individual 30-minute writing sessions were recorded through screen-capture and analyzed to demonstrate how the initiation of the writing task unfolds in practice. Analytically, this material was approached through the notion of textually mediated activity (cf. Mäkitalo, 2012). A subsequent 60-minute group discussion, designed as a ‘report-and-share’ session, was video-recorded and analyzed discursively to enrich insights from the screen-capture material. The results identify how initiating a writing task involves distinct forms of student agency, approaches to LLM use, and orientations to what constitutes academic writing. They also unpack how agency emerges through students' management of one or more LLM and the roles they assume. Finally, the results detail approaches and orientations when students enter into dialogue with LLMs by specifying and contextualizing a task or requesting specific feedback. In sum, the study contributes to understanding of how writing with LLMs shapes not only individual writing processes but also the epistemic work accomplished through writing. Anson, D.W.J. (2024) The impact of large language models on university students’ literacy development: a dialogue with Lea and Street’s academic literacies framework. Higher Education Research & Development, 43:7, 1465-1478, https://doi.org/10.1080/07294360.2024.2332259 Khuder, B. (2025). Enhancing disciplinary voice through feedback-seeking in AI-assisted doctoral writing for publication, Applied Linguistics, amaf022, https://doi.org/10.1093/applin/amaf022 Li, H. Wang, Y., Luo, S. & Huang, C (2025) The influence of GenAI on the effectiveness of argumentative writing in higher education: evidence from a quasi-experimental study in China, Journal of Asian Public Policy, 18:2, 405-430. https://doi.org/10.1080/17516234.2024.2363128 Mäkitalo, Å. (2012). Professional learning and the materiality of social practice. Journal of Education and Work, 25(1), 59–78. https://doi.org/10.1080/13639080.2012.644905 Pérez, A., McClain, S. K., Roa, A. F., Rosado-Mendinueta, N., Trigos-Carrillo, L., Robles, H., & Campo, O. (2025). Artificial intelligence applications in college academic writing and composition: a systematic review. Íkala: Revista de Lenguaje y Cultura, 30(1), 1–37. https://doi.org/10.17533/udea.ikala.355878 Prior, P. (2006) A sociocultural theory of writing. In C.A. MacArthur, S. Graham & J. Fitzgerald, J. (Eds.). Handbook of writing research. 54-66. Guilford Prior, P., Thorne, S. L. (2014). Research paradigms: beyond product, process, and social activity. In D. Perrin & E-M. Jakobs (Eds.) Handbook of writing and text production (10). 31-54. De Gruyer. https://doi.org/10.1515/9783110220674.31 Singh, J.K., Daniel, B. & Koh, J. (2025) Empowering authorship with AI: a novel academic writing technology for authorial voice. International Journal of Artificial Intelligence in Education 35, 3406-3428. https://doi.org/10.1007/s40593-025-00503-8 Zakirova, Z., & Bedeker, M. (2025). AI and the emergence of new academic writing literacies: graduate student perspectives on its affordances and challenges. In M. Bedeker, T.M. Makoelle & S.A. Manan (Eds.). Exploring academic writing as social practice: institutional goals, complexities and possibilities in Central Asia. (pp. 295-318). Palgrave Macmillan, 2025. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/gu/detail.action?docID=32378338.