This volume, the result of four years of work performed by the combined research groups of Utrecht University (Faculty of Humanities) and the HU Utrecht University of Applied Sciences (Faculty of Education), focuses on the central theme of 'Normative Professionalization'. Drawing on a wide variety of scholars including Hannah Arendt, Gert Biesta, Harry Kunneman, Donald SchOn and Chris Argyris, and engaging with professionalism, ethics, virtue and morality, this book builds the argument that learning to deal with complexity supports not only education but the personal development of teachers and the improvement of society and democracy as well. This volume presents research on a broad range of topics such as worldview education, co-teaching, moral authorship, traditional-reform perspectives on education, the discourse on citizenship, teacher education, and the question how to link religion and education. The research chapters explain the theoretical lenses and methodological approaches which have been employed to get a grip on complexity.
Abstract Despite the numerous business benefits of data science, the number of data science models in production is limited. Data science model deployment presents many challenges and many organisations have little model deployment knowledge. This research studied five model deployments in a Dutch government organisation. The study revealed that as a result of model deployment a data science subprocess is added into the target business process, the model itself can be adapted, model maintenance is incorporated in the model development process and a feedback loop is established between the target business process and the model development process. These model deployment effects and the related deployment challenges are different in strategic and operational target business processes. Based on these findings, guidelines are formulated which can form a basis for future principles how to successfully deploy data science models. Organisations can use these guidelines as suggestions to solve their own model deployment challenges.
Nederland zet koers richting een open vorm van wetenschapsbeoefening, getuige onder andere de lancering van het Nationaal Plan Open Science (NPOS) afgelopen februari en het nieuwe regeerakkoord dat stelt dat open access en open science de norm worden in wetenschappelijk onderzoek. Open science heeft als doel om wetenschappelijke kennis op transparante wijze en voor een breed publiek te publiceren. Dat vergt een herijking van onderzoek doen, samenwerking tussen onderzoekers en de wijze waarop kennis wordt gedeeld en de wetenschap wordt georganiseerd. Informatieprofessionals kunnen hierbij een rol van betekenis spelen, zoals blijkt uit cases van de Universiteit Utrecht, Hogeschool van Arnhem en Nijmegen en KNMI. Maar eerst een korte toelichting op open science en het NPOS. http://www.informatieprofessional.nl
Intelligent technology in automotive has a disrupting impact on the way modern automobiles are being developed. New technology not only has brought complexity to already existing information in the car (digitization of driver instruments) but also brings new external information to the driver on how to optimize the driving style amongst others from the perspective of communicating with infrastructures (Vehicle to Infrastructure communication (V2I)). The amount of information that a driver has to process in modern vehicles is increasing rapidly due to the introduction of multiple displays and new external information sources. An information overload lies awaiting, yet current Human Machine Interface (HMI) designs and the corresponding legal frameworks lag behind. Currently, many initiatives (Pratijkproef Amsterdam, Concorda) are being developed with respect to V2I, amongst others with Rijkswaterstaat, North Holland and Brabant. In these initiatives, SME’s, like V-Tron, focus on the development of specific V2I hardware. Yet in the field of HMI’s these SME’s need universities (HAN University of Applied Science, Rhine Waal University of Applied Science) and industrial designers (Yellow Chess) to help them with design guidelines and concept HMI’s. We propose to develop first guidelines on possible new human-machine interfaces. Additionally, we will show the advantages of HMI’s that go further than current legal requirements. Therefore, this research will focus on design guidelines averting the information overload. We show two HMI’s that combine regular driver information with V2I information of a Green Light Optimized Speed Advise (GLOSA) use case. The HMI’s will be evaluated on a high level (focus groups and a small simulator study). The KIEM results in two publications. In a plenary meeting with experts, the guidelines and the limitations of current legal requirements will be discussed. The KIEM will lead to a new consortium to extend the research.
Globalization has opened new markets to Small and Medium Enterprise (SMEs) and given them access to better suppliers. However, the resulting lengthening of supply chains has increased their vulnerability to disruptions. SMEs now recognize the importance of reliable and resilient supply chains to meet customer requirements and gain competitive advantage. Data analytics play a crucial role in developing the insights needed to identify and deal with disruptions. At the company level, this entails the development of data analytic capability, a complex socio-technical process consisting of people, technology, and processes. At the supply chain level, the complexity is compounded by the fact that multiple actors are involved, each with their own resources and capabilities. Each company’s data analytic capability, in combination with how they work together to share information and thus create visibility in the supply chain will affect the reliability and resilience of the supply chain. The proposed study therefore examines how SMEs can leverage data analytics in a way that fits with their available resources and capabilities to improve the reliability and resilience of their supply chain. The consortium for this project consists of Breda University of Applied Sciences (BUas), Logistics Community Brabant (LCB), Transport en Logistiek Nederland (TLN), Logistiek Digitaal, Kennis Transport, Smink and Devoteam. Together, the partners will develop a tool to benchmark SMEs’ progress towards developing data analytic capability that enhances the reliability of their supply chain. Interviews will be conducted with various actors of the supply chain to identify the enablers and inhibitors of using data analytics across the supply chain. Finally, the findings will be used to conduct action research with the two SMEs partners, Kennis and Smink to identify which technological tools and processes companies need to adopt to develop the use of data analytics to enhance their resilience in case of disruptions.
Vulnerable pregnant women are an important and complex theme in daily practice of birth care professionals. Vulnerability is an important risk factor for maternal and perinatal mortality and morbidity. Providing care for these women is often complex. First, because it is not always easy to identify vulnerability. Secondly, vulnerable women more often cancel their appointments with midwives and finally, many professionals are involved while they do not always know each other. Even though professionals are aware of the risks of vulnerability for future mothers and their (unborn) children and the complexity of care for these women, there is no international definition for ‘vulnerable pregnancies’. Therefore, we start this project with defining a mutual definition of vulnerability during pregnancy. In current projects of Rotterdam University of Applied Sciences (RUAS) we define a vulnerable pregnant woman as: a pregnant woman facing psychopathology, psychosocial problems, and/or substance abuse combined with lack of individual and/or social resources (low socioeconomic status, low educational level, limited social network). In the Netherlands, care for vulnerable pregnant women is fragmented and therefore it is unclear for birth care professionals which interventions are available and effective. Therefore, Dutch midwives are convinced that exchanging knowledge and best practices concerning vulnerable pregnancies between midwifery practices throughout Europe could enhance their knowledge and provide midwives (SMB partners in this project) with tools to improve care for vulnerable pregnant women. The aim of this project is to exchange knowledge and best practices concerning vulnerable pregnancies between midwifery practices in several European countries, in order to improve knowledge and skills of midwives. As a result, guidelines will be developed in order to exchange selected best practices which enable midwives to implement this knowledge in their own context. This contributes to improving care for vulnerable pregnant women throughout Europe.
