In L1 grammar teaching, teachers often struggle with the students’ conceptual understanding of the subject matter. Frequently, students do not acquire an in-depth understanding of grammar, and they seem generally incapable of reasoning about grammatical problems. Some scholars have argued that an in-depth understanding of grammar requires making connections between concepts from traditional grammar and underlying metaconcepts from linguistic theory. In the current study, we evaluate an intervention aiming to do this, following up on a previous study that found a significant effect for such an approach in university students of Dutch Language and Literature (d = 0.62). In the current study, 119 Dutch secondary school students’ grammatical reasonings (N=684) were evaluated by language teachers, teacher educators and linguists pre and post intervention using comparative judgement. Results indicate that the intervention significantly boosted the students’ ability to reason grammatically (d = 0.46), and that many students can reason based on linguistic metaconcepts. The study also shows that reasoning based on explicit underlying linguistic metaconcepts and on explicit concepts from traditional grammar is more favored by teachers and (educational) linguists than reasoning without explicit (meta)concepts. However, some students show signs of incomplete acquisition of the metaconcepts. The paper discusses explanations for this incomplete acquisition.
Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economic-environmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services.
