Biodiversity loss and widespread ecosystem degradation are among the most pressing challenges of our time, requiring urgent action. Yet our understanding of their causes remains limited because prevailing ecological concepts and approaches often overlook the underlying complex interactions of individuals of the same or different species, interacting with each other and with their environment. We propose a paradigm shift in ecological science, moving from simplifying frameworks that use species, population or community averages to an integrative approach that recognizes individual organisms as fundamental agents of ecological change. The urgency of the biodiversity crisis requires such a paradigm shift to advance ecology towards a predictive science by elucidating the causal mechanisms linking individual variation and adaptive behaviour to emergent properties of populations, communities, ecosystems, and ecological interactions with human interventions. Recent advances in computational technologies, sensors, and analytical tools now offer unprecedented opportunities to overcome past challenges and lay the foundation for a truly integrated Individual-Based Global Change Ecology (IBGCE). Unravelling the potential role of individual variability in global change impact analyses will require a systematic combination of empirical, experimental and modelling studies across systems, while taking into account multiple drivers of global change and their interactions. Key priorities include refining theoretical frameworks, developing benchmark models and standardized toolsets, and systematically incorporating individual variation and adaptive behaviour into empirical field work, experiments and predictive models. The emerging synergies between individual-based modelling, big data approaches, and machine learning hold great promise for addressing the inherent complexity of ecosystems. Each step in the development of IBGCE must systematically balance the complexity of the individual perspective with parsimony, computational efficiency, and experimental feasibility. IBGCE aims to unravel and predict the dynamics of biodiversity in the Anthropocene through a comprehensive study of individual organisms, their variability and their interactions. It will provide a critical foundation for considering individual variation and behaviour for future conservation and sustainability management, taking into account individual-to-ecosystem pathways and feedbacks.

Virtual Reality (VR) is currently on everyone’s lips for various purposes. Although the hype is currently nearing its productive plateau, there are still uncertainties about the utilization and potential of the technology in research and educational contexts. Together with the two following articles on the subject of VR research, this article provides an overview of the inherent potential as well as remaining challenges in the use of VR as an instrument for research and education. These will be clarified and critically examined on the basis of specific academic projects. Based on this, the article concludes with a comprehensive look on the need for further discussion of ethical issues as the key for VR success in research and education.

The selection and manipulation of objects in Virtual Reality face application developers with a substantial challenge as they need to ensure a seamless interaction in three-dimensional space. Assessing the advantages and disadvantages of selection and manipulation techniques in specific scenarios and regarding usability and user experience is a mandatory task to find suitable forms of interaction. In this article, we take a look at the most common issues arising in the interaction with objects in VR. We present a taxonomy allowing the classification of techniques regarding multiple dimensions. The issues are then associated with these dimensions. Furthermore, we analyze the results of a study comparing multiple selection techniques and present a tool allowing developers of VR applications to search for appropriate selection and manipulation techniques and to get scenario dependent suggestions based on the data of the executed study.

Accelerated by the COVID-19 pandemic, private EdTech companies and emerging digital education ecosystems have significantly reshaped digital governance in education. This shift has pressured governments into rapid digital transformation while also raising concerns about increasing inequalities, fueled by a data-driven approach to teaching and learning. The public education debate increasingly calls for tighter data regulations, alternatives to private sector dominance, and digital education offerings by traditional education actors that create value in the digital realm. Responding to these pressures, the German government develops a national digital education ecosystem (NDEE) to guide this transformation. Using data from 10 semi-structured interviews, a stakeholder survey ( n = 121), and three stakeholder workshops with in total of 80 participants, our mixed-method research contributes to the discourse on digital education governance and the creation of public data ecosystems. We identify 19 orchestration tensions, aggregated into four tension groups, shed light on education stakeholders’ preferences, and identify with the three ecosystem vision models: “Education Interconnectivity Infrastructure,” “Public Education Space,” and the “Public–Private Education Marketplace.” These findings underscore the importance of a coherent ecosystem vision that balances public and private interests, leads the foundation for ecosystem governance, and aligns the ecosystem’s scope with government orchestration capabilities. We offer valuable insights for researchers and policymakers working toward a government-orchestrated national digital education ecosystem.

The integration of artificial intelligence (AI) literacy and data literacy into school education is increasingly proposed in educational frameworks, leading to an urgent need to train computer science teachers in AI and data literacy. However, there is a lack of professional development programs for these skills. To fill this gap, we developed a training concept and evaluated it with computer science teachers from Germany, Austria, and Lithuania in three sessions. In the following, we present selected evaluation results.

The educational sector currently faces a massive digital transformation with various digital offerings entering the market. To provide some orientation in this transforming space, a national digital education platform (NDEP) is under development in Germany as part of a nationwide flagship project. On the one hand, in efficiently connecting the relevant stakeholders to each other and to value-adding education-related offerings, various benefits emerge. On the other hand, monopolising the educational sector and influencing the respective market through a state-controlled platform bears potential regulatory risks from misuse of power by the platform to malpractice by the users. Against this background, we aim to identify and systematise these potential drawbacks prior to the platform’s actual development and implementation. We pursue a qualitative, interpretivist approach for policy analysis, based on ten elite interviews and two workshops. Our results are threefold: (1) We capture the consolidated NDEP architecture; (2) We categorise the range of relevant functions and value propositions of the NDEP; (3) We derive 23 regulatory areas of conflict across the three building blocks that result from the potential ecosystem and function scope configurations of the NDEP. As a contribution to research, we shed new interdisciplinary light on the governance and infrastructure of public-private platforms that enable innovation and collaboration while integrating respective market segments. As a contribution to practice, we provide clear guidance for policy-makers in strategizing the development and governance of and through national digital platforms in education.