A case study and method development research of online simulation gaming to enhance youth care knowlegde exchange. Youth care professionals affirm that the application used has enough relevance as an additional tool for knowledge construction about complex cases. They state that the usability of the application is suitable, however some remarks are given to adapt the virtual environment to the special needs of youth care knowledge exchange. The method of online simulation gaming appears to be useful to improve network competences and to explore the hidden professional capacities of the participant as to the construction of situational cognition, discourse participation and the accountability of intervention choices.
When it comes to hard to solve problems, the significance of situational knowledge construction and network coordination must not be underrated. Professional deliberation is directed toward understanding, acting and analysis. We need smart and flexible ways to direct systems information from practice to network reflection, and to guide results from network consultation to practice. This article presents a case study proposal, as follow-up to a recent dissertation about online simulation gaming for youth care network exchange (Van Haaster, 2014).
Objectives: Simulation is an important learning activity in nursing education. There is little knowledge about dialogue and communication between students and facilitators in a virtual simulation setting. The current study, conducted in Norway, explores the dialogic teaching approaches applied by facilitators in a virtual classroom and adapt an analytic tool from a physical classroom in lower education to a virtual classroom in higher education. Methods: Sixteen virtual simulation sessions of groups with nursing students were video-taped. The videos were coded with a coding scheme developed for physical classrooms and adapted to the virtual setting. The dialogic approaches from the facilitator were analysed using descriptive analysis. Results: The most frequently used approaches from the facilitator were categorized as listening (“Modelling prompts and body language to encourage continuation”) and asking (“Big questions”). The most frequent pattern seen in the use of dialogic approaches fall under the category listening. Conclusions: The coding scheme is suitable to analyse facilitators’ dialogic approaches in a virtual setting in nursing education. Further research should examine how the facilitator can strategically deploy dialogic approaches in other types of simulations with students. Innovation: The coding scheme was developed from lower to higher education, and from a physical to a virtual setting.
In the Glasgow declaration (2021), the tourism sector promised to reduce its CO2 emissions by 50% and reduce them to zero by 2050. The urgency is felt in the sector, and small steps are made at company level, but there is a lack of insight and overview of effective measures at global level.This study focuses on the development of a necessary mix of actions and interventions that the tourism sector can undertake to achieve the goal of a 50% reduction in greenhouse gases by 2030 towards zero emissions by 2050. The study contributes to a better understanding of the paths that the tourism sector can take to achieve this and their implications for the sector. The aim of the report is to spark discussion, ideas and, above all, action.The study provides a tool that positively engages the sector in the near and more distant future, inspires discussion, generates ideas, and drives action. In addition, there will be a guide that shows the big picture and where the responsibilities lie for the reduction targets. Finally, the researchers come up with recommendations for policymakers, companies, and lobbyists at an international and European level.In part 1 of the study, desk research is used to lay the foundation for the study. Here, the contribution of tourism to global greenhouse gas emissions is mapped out, as well as the image and reputation of the sector on climate change. In addition, this section describes which initiatives in terms of, among other things, coalitions and declarations have already been taken on a global scale to form a united front against climate change.In part 2, 40 policies and measures to reduce greenhouse gas emissions in the sector are evaluated in a simulation. For this simulation, the GTTMdyn simulation model, developed by Paul Peeters from BUAS, is used which works on a global scale and shows the effect of measures on emissions, tourism, transport, economy, and behaviour. In this simulation, the researchers can 'test' measures and learn from mistakes. In the end one or more scenarios will; be developed that reach the goals of 50% reduction in 2030 and zero emissions in 2050. In part 3, the various actions that should lead to the reduction targets are tested against the impacts on the consequences for the global tourism economy, its role in providing leisure and business opportunities and the consequences for certain destinations and groups of industry stakeholders. This part will be concluded with two workshops with industry experts to reflect on the results of the simulation.Part 4 reports the results of the study including an outline of the consequences of possibly not achieving the goal. With this, the researchers want to send a warning signal to stakeholders who may be resistant to participating in the transition.
Automated driving nowadays has become reality with the help of in-vehicle (ADAS) systems. More and more of such systems are being developed by OEMs and service providers. These (partly) automated systems are intended to enhance road and traffic safety (among other benefits) by addressing human limitations such as fatigue, low vigilance/distraction, reaction time, low behavioral adaptation, etc. In other words, (partly) automated driving should relieve the driver from his/her one or more preliminary driving tasks, making the ride enjoyable, safer and more relaxing. The present in-vehicle systems, on the contrary, requires continuous vigilance/alertness and behavioral adaptation from human drivers, and may also subject them to frequent in-and-out-of-the-loop situations and warnings. The tip of the iceberg is the robotic behavior of these in-vehicle systems, contrary to human driving behavior, viz. adaptive according to road, traffic, users, laws, weather, etc. Furthermore, no two human drivers are the same, and thus, do not possess the same driving styles and preferences. So how can one design of robotic behavior of an in-vehicle system be suitable for all human drivers? To emphasize the need for HUBRIS, this project proposes quantifying the behavioral difference between human driver and two in-vehicle systems through naturalistic driving in highway conditions, and subsequently, formulating preliminary design guidelines using the quantified behavioral difference matrix. Partners are V-tron, a service provider and potential developer of in-vehicle systems, Smits Opleidingen, a driving school keen on providing state-of-the-art education and training, Dutch Autonomous Mobility (DAM) B.V., a company active in operations, testing and assessment of self-driving vehicles in the Groningen province, Goudappel Coffeng, consultants in mobility and experts in traffic psychology, and Siemens Industry Software and Services B.V. (Siemens), developers of traffic simulation environments for testing in-vehicle systems.
Based on the model outcomes, Houtlaan’s energy transition will likely result in congestion and curtailmentproblems on the local electricity grid within the next 5-7 years, possibly sooner if load imbalance between phasesis not properly addressed.During simulations, the issue of curtailment was observed in significant quantities on one cable, resulting in aloss of 8.292 kWh of PV production per year in 2030. This issue could be addressed by moving some of thehouses on the affects cable to a neighboring under-utilized cable, or by installing a battery system near the end ofthe affected cable. Due to the layout of the grid, moving the last 7 houses on the affected cable to the neighboringcable should be relatively simple and cost-effective, and help to alleviate issues of curtailment.During simulations, the issue of grid overloading occurred largely as a result of EV charging. This issue can bestbe addressed by regulating EV charging. Based on current statistics, the bulk of EV charging is expected to occurin the early evening. By prolonging these charge cycles into the night and early morning, grid overloading canlikely be prevented for the coming decade. However, such a control system will require some sort of infrastructureto coordinate the different EV charge cycles or will require smart EV chargers which will charge preferentiallywhen the grid voltage is above a certain threshold (i.e., has more capacity available).A community battery system can be used to increase the local consumption of produced electricity within theneighborhood. Such a system can also be complemented by charging EV during surplus production hours.However, due to the relatively high cost of batteries at present, and losses due to inefficiencies, such a systemwill not be financially feasible without some form of subsidy and/or unless it can provide an energy service whichthe grid operator is willing to pay for (e.g. regulating power quality or line voltage, prolonging the lifetime of gridinfrastructure, etc.).A community battery may be most useful as a temporary solution when problems on the grid begin to occur, untila more cost-effective solution can be implemented (e.g. reinforcing the grid, implementing an EV charge controlsystem). Once a more permanent solution is implemented, the battery could then be re-used elsewhere.The neighborhood of Houtlaan in Assen, the Netherlands, has ambitious targets for reducing the neighborhood’scarbon emissions and increasing their production of their own, sustainable energy. Specifically, they wish toincrease the percentage of houses with a heat pump, electric vehicle (EV) and solar panels (PV) to 60%, 70%and 80%, respectively, by the year 2030. However, it was unclear what the impacts of this transition would be onthe electricity grid, and what limitations or problems might be encountered along the way.Therefore, a study was carried out to model the future energy load and production patterns in Houtlaan. Thepurpose of the model was to identify and quantify the problems which could be encountered if no steps are takento prevent these problems. In addition, the model was used to simulate the effectiveness of various proposedsolutions to reduce or eliminate the problems which were identified
