This paper argues for the need to develop a relational, emergent and plural understanding of learning spaces. We take an ecological perspective on learning, which allows us to conceptualize learning spaces as (co‐)constructed by learners; emerging through learners' practices, interactions and activities; and facilitated by pedagogical arrangements. In the co‐construction of spaces for learning, tapping into various ecologies of resources—whether intellectual, relational or digital material—becomes an organic, iterative, agentic endeavour for learners. This paper proposes a set of principles to synthesize this conceptualization and facilitates an understanding of such emergent learning spaces. An empirical illustration extracted from a collaborative student project in software engineering education contributes to grounding the conceptual argument and provides a clarifying example. Ultimately, this contribution suggests that in order to support the emergence of learning spaces that are resource‐rich and conducive to learning, educational contexts and pedagogical arrangements must provide both the framing conditions and also the flexibility and permeability required to access the wider ecologies of resources made available through digital technologies.
Practitioner NotesWhat is already known about this topic
Learning spaces can be individual or collective.
Physical space is an important element that can facilitate or hinder learning.
Technology can contribute to hosting learning spaces (eg, online).
What this paper adds
A potential new conceptualization drawing on an ecological perspective on learning.
Insights into how learning spaces are customized versions of the learners' intellectual, relational or digital‐material resources available in various contexts.
Examples of how learning spaces are constitutive through learners' individual or collective practices, based on affordances provided by pedagogical designs.
Propositions on how pedagogical designs can provide learners with opportunities to access wider ecologies of resources made available through digital technologies.
Implications for practice and/or policy
Teachers need support to develop pedagogical designs that support learners in creating their own learning spaces.
Helping students to create their learning spaces requires guidance, which must be facilitated by appropriate institutional infrastructures and conditions.
Professional learning approaches are needed to build teachers' knowledge and capacities to support students.
Institutional arrangements must be open to change.
Numerous case studies show that citizens engage in various ways in renewable and low carbon energy projects, thereby contributing to the sustainable energy transition. To date, however, a systematic and cross-country database on citizen-led initiatives and projects is lacking. By performing a major compilation and reviewing copious data sources from websites to official registries, we provide a Europe-wide inventory with over 10,000 initiatives and 16,000 production units in 29 countries, focusing on the past 20 years. Our data allow cross-country statistical analysis, supporting the elicitation of empirical insights capable of extending beyond the perspective of single case studies. Our data also align with ongoing efforts to implement two EU Directives that aim at strengthening the active role of citizens in the energy transition. While the focus of our data collection is on Europe, the data and methodology can contribute to the global analysis of citizen-led energy action.
To face the impact of climate change in all dimensions of our society in the near future, the European Union (EU) has established an ambitious target. Until 2050, the share of renewable power shall increase up to 75% of all power injected into nowadays’ power grids. While being clean and having become significantly cheaper, renewable energy sources (RES) still present an important disadvantage compared to conventional sources. They show strong fluctuations, which introduce significant uncertainties when predicting the global power outcome and confound the causes and mechanisms underlying the phenomena in the grid, such as blackouts, extreme events, and amplitude death. To properly understand the nature of these fluctuations and model them is one of the key challenges in future energy research worldwide. This review collects some of the most important and recent approaches to model and assess the behavior of power grids driven by renewable energy sources. The goal of this survey is to draw a map to facilitate the different stakeholders and power grid researchers to navigate through some of the most recent advances in this field. We present some of the main research questions underlying power grid functioning and monitoring, as well as the main modeling approaches. These models can be classified as AI- or mathematically inspired models and include dynamical systems, Bayesian inference, stochastic differential equations, machine learning methods, deep learning, reinforcement learning, and reservoir computing. The content is aimed at the broad audience potentially interested in this topic, including academic researchers, engineers, public policy, and decision-makers. Additionally, we also provide an overview of the main repositories and open sources of power grid data and related data sets, including wind speed measurements and other geophysical data.
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