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Research conducted by Henk van den Hurk shows that teachers’ knowledge of effective instructional behaviour is of limited influence on their actual performance in daily teaching. Observing teachers within their own educational practice and the subsequent feedback in teacher training college, however, has shown to be effective in improving teacher instructional practice. Van den Hurk studied the effects of the application of a cyclic model for data-feedback in initial teacher training as well as in a master course for teachers. In the applied model, teachers are observed with standardised observational instruments, while teaching their own classes. Back in teacher training college they are supported in formulating specific points of improvement for their own instructional behaviour. Subsequently, in their own classroom, the students practice the skills they further have to develop. After a short while another classroom observation is scheduled. The use of this model has proven to lead to a substantial improvement of teacher instructional behaviour. It is remarkable that advances in the quality of teacher instructional behaviour are reached in a limited time-span of only several weeks.
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Wanneer je met je lessen specifieke leerdoelen hebt, zoals tactisch inzicht, regelvaardigheden, of samenwerking, dan hoort daar ook een specifieke aanpak bij. De laatste jaren zijn er in de LO, met name in het buitenland, verschillende modellen ontwikkeld die je hierbij kunnen helpen. Deze aanpak wordt ook wel 'Models-Based Physical Education genoemd”.
The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
Little is known about the effects of different instructional approaches on learner affect in oral interaction in the foreign language classroom. In a randomized experiment with Dutch pre-vocational learners (N = 147), we evaluated the effects of 3 newly developed instructional programs for English as a foreign language (EFL). These programs differed in instructional focus (form-focused vs. interaction strategies- oriented) and type of task (pre-scripted language tasks vs. information gap tasks). Multilevel analyses revealed that learners’ enjoyment of EFL oral interaction was not affected by instruction, that willingness to communicate (WTC) decreased over time, and that self-confidence was positively affected by combining information gap tasks with interactional strategies instruction. In addition, regression analyses revealed that development in learners’ WTC and enjoyment did not have predictive value for achievement in EFL oral interaction, but that development in self-confidence did explain achievement in EFL oral interaction in trained interactional contexts.
Particulate matter (PM) exposure, amongst others caused by emissions and industrial processes, is an important source of respiratory and cardiovascular diseases. There are situations in which blue-collar workers in roadwork companies are at risk. This study investigated perceptions of risk and mitigation of employees in roadwork (construction and maintenance) companies concerning PM, as well as their views on methods to empower safety behavior, by means of a mental models approach. We held semi-structured interviews with twenty-two employees (three safety specialists, seven site managers and twelve blue-collar workers) in three different roadwork companies. We found that most workers are aware of the existence of PM and reduction methods, but that their knowledge about PM itself appears to be fragmented and incomplete. Moreover, road workers do not protect themselves consistently against PM. To improve safety instructions, we recommend focusing on health effects, reduction methods and the rationale behind them, and keeping workers’ mental models into account. We also recommend a healthy dialogue about work-related risk within the company hierarchy, to alleviate both information-related and motivation-related safety issues. https://doi.org/10.1016/j.ssci.2019.06.043 LinkedIn: https://www.linkedin.com/in/john-bolte-0856134/
This paper discusses two studies - the one in a business context, the other in a university context - carried out with expert educational designers. The studies aimed to determine the priorities experts claim to employ when designing competence-based learning environments. Designers in both contexts agree almost completely on principles they feel are important. Both groups emphasized that one should start a design enterprise from the needs of the learners, instead of the content structure of the learning domain. However, unlike business designers, university designers find it extremely important to consider alternative solutions during the whole design process. University designers also say that they focus more on project plan and desired characteristics of the instructional blueprint whereas business designers report being more client-oriented, stressing the importance of "buying in" the client early in the process.
New Dutch agrifood business models are emerging in response to economic, social and ecological pressures: new players arrive, new logistical pathways come to the fore and innovative consumer and farmer relationships – food coöperatives – are forged. How do new business models relate to reconfiguring the Dutch agrifood system? Our research combines future exploration (backcasting) and analysis of new business models. We developed three agrifood transition scenarios with various groups of stakeholders. For each scenario, we then analysed a specific, representative business model to explore the different roles of business models in agrifood transition. Business models in the “Added value in and with the countryside” already exist and occupy a niche in the market. However, a breakthrough of these business models require large-scale institutional and behavioural change. Business models in the “New products, specific markets” exist but are rare. They usually concern high-value specialist products that could result in widespread market change, but might require little institutional change. The “Sustainable production methods” most resembles the current system. Some associated business models become successful, but they have difficulty distinguishing themselves from conventional produce, which raises questions about whether business models are able to drive a transition in this direction. Thus, our results lend credence to the hypothesis that different transition pathways offer specific potential for and requirements of new business models.
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© Springer International Publishing AG 2016. A serious game needs to combine a number of different aspects to help the end user in reaching the desired effects. This requires incorporating a broad range of different aspects in the design, stemming from a broad range of different fields of expertise. For designers, developers, researchers, and other stakeholders it is not straightforward how to organize the design and development process, to make sure that these aspects are properly addressed. In this chapter we will discuss a number of ways of organizing the design and development process and various models that support specific design decisions during this process, concluding with a discussion of design patterns for serious games.
