This paper highlights the use of State Space Grids (SSGs) for studying real-time classroom discourse in an intervention targeting professional development. State Space Grid analysis is both a powerful way to visualise patterns in interactional data, and a starting point for further quantitative analysis. In the present study SSGs were used to explore patterns in teacher–student interactions. The study shows the importance of using micro-level time-serial data and illustrates how change in interactions during and after an intervention can be studied. SSG analysis was applied to study interaction in terms of the coupling of a teacher and a student variable: autonomy support and musical creativity. Video data from 40 music lessons of five teachers and their classes was used as input for plotting teacher–student interactions in SSGs, consisting of two dimensions. SSGs allow visualising change in the situation of interactions in the grid and identifying change in patterns to different grid areas. The findings show how interactions tended to settle in areas representing more productive interaction for all but one class. We discuss the benefits of using SSGs in intervention studies and the implications for educational practice and research of using this time-serial approach.
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In the Netherlands, energy cooperatives are increasingly active in the production of renewable energy. Many cooperatives have concrete plans to invest in energy projects, such as solar fields and wind turbines. Unfortunately, in the coming years there will hardly be any room for such projects in the electricity grid. In their quest to help solve this predicament, energy cooperatives develop new and innovative energy services, for example delivering grid services to distribution system operators (DSOs). However, in this endeavor they encounter legal as well as economic obstacles.
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Combining electric cars with utility services seems to be a natural fit and holds the promise to tackle various mobility as well as electricity challenges at the same time. So far no viable business model for vehicle-to-grid technology has emerged, raising the question which characteristics a vehicle-to-grid business model should have. Drawing on an exploratory study amongst 189 Dutch consumers this study seeks to understand consumer preferences in vehicle-to-grid business models using conjoint analysis, factor analysis and cluster analysis. The results suggest that consumers prefer private ownership of an EV and a bidirectional charger instead of community ownership of bidirectional charger, they prefer utility companies instead of car companies as the aggregator and they require home and public charging. The most salient attributes in a V2G business model seem to be functional rather than financial or social. The customer segment with the highest willingness to adopt V2G prefers functional attributes. Based on the findings, the study proposes a business model that incorporates the derived preferences
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