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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.

Contemporary efforts to innovate simulation-based maritime education increasingly involve the development of multimodal learning analytics (MMLA) systems that use large language models (LLMs) to generate automated feedback on student performance. These systems are often presented as solutions to challenges such as limited instructor capacity, inconsistent assessment practices, and demands for greater standardization and accountability in competence evaluation. While such developments create new possibilities for personalized feedback and enhanced instructor support, they also raise important questions concerning transparency, responsibility, professional judgment, and regulatory compliance in maritime education. This study examines how MMLA can be introduced within a policy landscape shaped by the Standards of Training, Certification and Watchkeeping for Seafarers (STCW), European higher education policies, and the European Union AI Act. Drawing on Cultural-Historical Activity Theory (CHAT), we analyze how maritime simulator instructors and policy experts ( n = 12) position MMLA within the broader activity system of maritime education and training (MET), with particular attention to the relationships between new technologies, division of labor, and regulations. The analysis focuses on how MMLA reshapes instructor roles and feedback practices, as well as the contradictions and tensions that emerge between technological innovation, regulatory compliance, and the embodied, situated nature of professional judgment in simulator-based training. Our findings reveal tensions and contradictions between three fundamental aspects: innovation vs. regulation, automation vs. autonomy, and engineering design vs. pedagogical intent. The study concludes with implication for responsible implementation of MMLA in simulation-based maritime training.

BACKGROUND Three-dimensional virtual surgical planning (3D VSP) and patient-specific surgical guides (PSSGs) are increasingly used in wrist and forearm surgery. Despite their growing adoption, no standards define the minimum competencies required for their safe and independent use. This gap hinders standardized training and leaves surgeon competence unverified, which could pose risks to patient safety. OBJECTIVE To establish, through expert consensus, the competencies required for safe and independent use of 3D VSP and PSSGs in hand and forearm surgery. METHODS An initial competency list was generated through a purposive literature review and refined by a multidisciplinary steering group. Based on this list, a modified Delphi study will be conducted in accordance with CREDS recommendations. A structured questionnaire will be distributed to an expert panel of surgeons with documented experience in 3D VSP/PSSG use (at least 10 cases; at least 5 years post-specialization in hand or orthopedic surgery). Three iterative rounds using a 5-point Likert scale will be conducted, with controlled feedback between rounds. Consensus will be defined a priori using the median score, the interquartile range, and the proportion of agreement (70%). The study will be reported according to the ACCORD checklist. RESULTS A consensus-based list of competencies essential for safe and independent use of 3D VSP and PSSGs will be published. CONCLUSIONS This study will establish the first consensus-based competency framework for the safe and independent use of 3D VSP and PSSGs in wrist and forearm surgery. This framework will provide a foundation for standardized training and assessment of this rapidly growing field. By combining a rigorous modified Delphi methodology with an international, multidisciplinary expert panel, the resulting framework is expected to support the transition from informal apprenticeship models towards transparent, reproducible training standards.

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.