In this study, we address the function of role models for entrepreneurship students. By using entrepreneurs as role models, students can get a better and realistic picture of the complexity of the entrepreneurial path. Choosing whom to interview as role model can be diverse, but it can be problematic if, as a result of that choice, the learning effect in the same group of students is different.
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Background: The dynamics of maternal and newborn care challenge midwifery education programs to keep up-to-date. To prepare for their professional role in a changing world, role models are important agents for student learning. Objective: To explore the ways in which Dutch and Icelandic midwifery students identify role models in contemporary midwifery education. Methods: We conducted a descriptive, qualitative study between August 2017 and October 2018. In the Netherlands, 27 students participated in four focus groups and a further eight in individual interviews. In Iceland, five students participated in one focus group and a further four in individual interviews. All students had clinical experience in primary care and hospital. Data were analyzed using inductive content analysis. Results: During their education, midwifery students identify people with attitudes and behaviors they appreciate. Students assimilate these attitudes and behaviors into a role model that represents their ‘ideal midwife’, who they can aspire to during their education. Positive role models portrayed woman-centered care, while students identified that negative role models displayed behaviors not fitting with good care. Students emphasized that they learnt not only by doing, they found storytelling and observing important aspects of role modelling. Students acknowledged the impact of positive midwifery role models on their trust in physiological childbirth and future style of practice. Conclusion: Role models contribute to the development of students’ skills, attitudes, behaviors, identity as midwife and trust in physiological childbirth. More explicit and critical attention to how and what students learn from role models can enrich the education program.
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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.
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In our in-depth case study on two circular business models we found important roles for material scouts and networks. These key partners are essential for establishing circular business models and circular flow of materials. Besides, we diagnose that companies are having difficulties to develop viable value propositions and circular strategies. The paper was presented at NBM Nijmegen 2020 and will be published at a later date
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Abstract Introduction: In 2017, the role of coordinating practitioner was introduced in the Netherlands in order to improve quality of care for patients who receive treatment in specialized mental health care. Psychiatric-mental health nurse practitioners (PMHNPs) can fulfil this role. Aim/Question: The aim was to obtain insight into how PMHNPs fulfil the coordinating practitioner role and what is needed to improve fulfilment of this role. Method: A survey among PMHNPs in the Netherlands was conducted between July-September 2018. In total, 381 PMHNP filled out the questionnaire; the response rate was 47.6%. Descriptive analyses were performed using SPSS 22® (IBM). Results: 92% Of the PMHNPs fulfilled the coordinating practitioner role and were generally satisfied with their role performance. The following conditions were formulated to improve this role: 1) recognition and trust in the expertise of PMHNPs, 2) a clear description of their role as coordinating practitioner, 3) strengthening multidisciplinary collaboration, and 4) sufficient training budget and opportunities. Discussion: In Dutch mental health care, PMHNPs have strengthened their position as coordinating practitioner in a short period of time. Follow-up research should be conducted to obtain further insights into elements that contribute to an optimal role as coordinating practitioner. Implications for Practice: Having PMHNPs act as coordinating practitioners can contribute to solving the challenges in mental health care regarding coordination of care and effective multidisciplinary collaboration.
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This report describes the Utrecht regio with regard to sustainability and circular business models.
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Paper presented at the International Sustainability Transitions conference 2018 (12-14 june) Manchester, UK. The Dutch agrifood regime is grinding to a halt. International economic pressures force Dutch farmers to further scale up and intensify their businesses, while food scandals and calamities as well as many and varied negative environmental impacts have led to an all-time low societal acceptance of the agrifood regime as well as a host of legislative measures to stifle further growth. Such a situation, in which regime pressures increasingly undermine the regime, represents a strong call for transition of the Dutch agrifood system.At the same time, new business models emerge: new players arrive, new logistical pathways come to the fore and innovative consumer and farmer relationships – food co-operatives – are forged. In a sense, the transition is already under way (cf. Hermans et al., 2010), with new business models forming an important backbone. However, the way forward is still a matter of great uncertainty and controversy: How do new business models relate to reconfiguring the Dutch agrifood system? We explore the hypothesis that different transition pathways put specific demands on the role of new business models. We studied various new business models in the Dutch agrifood system and their relations to three different transition pathways. Our research combines future exploration (backcasting) and analysis of new business models. In this research, we approach this question from two angles. First, we introduce a transition-oriented business model concept, in order to effectively link new business models to transition. Then we shortly touch upon the transition pathway typology introduced by Geels et al. (2016) and describe three different transition pathways for the Dutch agrifood system. We report on XX business models in each of these transition pathways. The paper ends with a discussion of the role of business models for different types of transition pathways.
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Although near-peer role modeling (NPRM) has been suggested as an effective pedagogical intervention for boosting confidence, motivation, and self-efficacy, few studies have examined its connection with learner needs and well-being utilizing an established psychological framework. The present study investigates the pedagogical role of NPRM within English classes in Japanese higher education from the perspective of basic psychological need (BPN) satisfaction and frustration. In this two-phase explanatory mixed methods study, two quantitative scales were utilized to assess the significance of the connections between NPRM and six subcategories of BPN satisfaction or frustration. Subsequently, a qualitative investigation with a more limited sample size was conducted to elucidate and expand upon these associations. The quantitative findings revealed NPRM to be a significant predictor of students’ autonomy and relatedness satisfaction and exhibited a negative correlation with students' autonomy and relatedness frustration. However, no discernible association was observed between NPRM and competence satisfaction or frustration. The qualitative data revealed that the students’ mixed feelings of competence may have stemmed from low confidence and L2 self-concept with some students comparing themselves unfavorably to near-peer role models. The study highlights the need for NPRM interventions to be accompanied by instruction related to learner beliefs or growth mindsets.
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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/
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This paper describes a research about the changing role and competences of teachers and the willingness of the teachers to change. The researchers developed and conducted a survey at Fontys University of Applied Sciences department engineering to find out how teachers teach and how they would want to teach. The conclusion drawn from this research results in five subjects of attention: 1 To investigate new teaching competences 2 To investigate new teaching strategies 3 To develop collaborating professional environments for teachers 4 To develop a formal declaration of how companies can participate effectively in the process of the transition of youngsters to professional practitioners 5 To investigate how the organization should change their culture and structure towards a professional learning environment for students and teachers. The above mentioned items will be subject of further research in the coming study year. The main goal is to develop a business case or strategic plan on how to implement change in teaching engineering education.
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