Een korte Nederlandse uitleg over het concept 'Whole Systems Approach' op basis van het promotie onderzoek van Anu Manickam van het Lectoraat Duurzaam Coöperatief Ondernemen
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This chapter focuses on how pupil’s scientific understanding can be studied. The principles of a complex dynamic systems approach are highlighted.
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This chapter provides insights into the complex and adaptive nature of systems and illustrates key characteristics of such systems. These contribute to an understanding of the challenges in health promotion and imply a need for more context-specific research to evaluate the health promotion interventions. CARA can address this need as it can be used to evaluate and support change in complex adaptive systems. To support and inspire other health promotion researchers who want to adopt CARA as their research approach, we have discussed our experiences and provided some guiding principles. Overall, complexity thinking can help to understand the challenges in health promotion, whereby CARA provides a possible strategy for health promotion researchers when dealing with the challenges of evaluating health promotion interventions in complex adaptive systems.
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In the wake of neo-liberal informed global trends to set performance standards and intensify accountability, the Dutch government aimed for ‘raising standards for basic skills’. While the implementation of literacy standards was hardly noticed, the introduction of numeracy standards caused a major backlash in secondary schools, which ended in a failed introduction of a high stakes test. How can these major differences be explained? Inspired by Foucault’s governmentality concept a theoretical framework is developed to allow for detailed empirical research on steering processes in complex systems in which many actors are involved in educational decision-making. A mixed-methods multiple embedded case-study was conducted comprising nine school boards and fifteen secondary schools. Analyses unveil processes of responsibilisation, normalisation and emerging dividing practices. Literacy standards reinforced responsibilities of Dutch language teachers; for numeracy, school leadership created entirely new roles and responsibilities for teachers. Literacy standards were incorporated in an already used instrument which made implementation both subtle and inevitable. For numeracy, schools distinguished students by risk of not passing the new test affirming the disciplinary nature of schools in the process. While little changed to address teachers main concerns about students’ literacy skills, the failed introduction of the numeracy test usurped most resources.
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Energy Valley cluster and internationalisation.There is a need for more dynamic approaches to strategy development for clusters due to the complex internal and external environments that are part of clusters. The research introduced complex adaptive systems (CAS) approach to cluster theory where contextual analysis of clusters are an essential part of understanding cluster development. In-depth analyses of cluster dynamics and drivers of change in the context of the cluster would provide deeper understanding of cluster developments that will then feed into strategy development processes.
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Studying real-time teacher-student interaction provides insight into student's learning processes. In this study, upper grade elementary teachers were supported to optimize their instructional skills required for co-constructing scientific understanding. First, we examined the effect of the Video Feedback Coaching intervention by focusing on changes in teacher-student interaction patterns. Second, we examined the underlying dynamics of those changes by illustrating an in-depth micro-level analysis of teacher-student interactions. The intervention condition showed significant changes in the way scientific understanding was co-constructed. Results provided insight into how classroom interaction can elicit optimal co-construction and how this process changes during an intervention.
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Over the last years a large growth in Electric Vehicles (EV) and charging infrastructure (CI) development has been observed. Particularly in metropolitan areas this growth has led to a system in which multitudes of interactions between EV users take place. While many researchers have focused on EV user charging behavior and deployment strategies for CI, little attention has been paid to conceptualizing the problem domain. This research provides a brief overview of complex systems theory, and derives six characterizing elements of complex systems that may be applicable for CI. The paper investigates both theoretically but also empirically how these characterizing elements apply for CI and provides implications for the further roll-out of CI for both policy makers and researchers. We illustrate our findings with preliminary results form ongoing research. Recommendations include the further development of simulation tools that are capable of exploring effects of e.g. non-linear behavior, feedback loops and emergence of new patterns on CI performance. In the end this paper aims to provide directions to enable policy makers to be better prepared for the anticipated exponential growth of EVs and CI.
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We live in an increasingly complex world, characterised by interconnected and intractable wicked problems. Systems mapping offers a visual approach for collectively understanding and envisioning how to coordinate the addressing of these problems. The agri-food sector is facing severe problems and systems mapping could be particularly instrumental in helping it navigate these difficulties.
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The Heating Ventilation and Air Conditioning (HVAC) sector is responsible for a large part of the total worldwide energy consumption, a significant part of which is caused by incorrect operation of controls and maintenance. HVAC systems are becoming increasingly complex, especially due to multi-commodity energy sources, and as a result, the chance of failures in systems and controls will increase. Therefore, systems that diagnose energy performance are of paramount importance. However, despite much research on Fault Detection and Diagnosis (FDD) methods for HVAC systems, they are rarely applied. One major reason is that proposed methods are different from the approaches taken by HVAC designers who employ process and instrumentation diagrams (P&IDs). This led to the following main research question: Which FDD architecture is suitable for HVAC systems in general to support the set up and implementation of FDD methods, including energy performance diagnosis? First, an energy performance FDD architecture based on information embedded in P&IDs was elaborated. The new FDD method, called the 4S3F method, combines systems theory with data analysis. In the 4S3F method, the detection and diagnosis phases are separated. The symptoms and faults are classified into 4 types of symptoms (deviations from balance equations, operating states (OS) and energy performance (EP), and additional information) and 3 types of faults (component, control and model faults). Second, the 4S3F method has been tested in four case studies. In the first case study, the symptom detection part was tested using historical Building Management System (BMS) data for a whole year: the combined heat and power plant of the THUAS (The Hague University of Applied Sciences) building in Delft, including an aquifer thermal energy storage (ATES) system, a heat pump, a gas boiler and hot and cold water hydronic systems. This case study showed that balance, EP and OS symptoms can be extracted from the P&ID and the presence of symptoms detected. In the second case study, a proof of principle of the fault diagnosis part of the 4S3F method was successfully performed on the same HVAC system extracting possible component and control faults from the P&ID. A Bayesian Network diagnostic, which mimics the way of diagnosis by HVAC engineers, was applied to identify the probability of all possible faults by interpreting the symptoms. The diagnostic Bayesian network (DBN) was set up in accordance with the P&ID, i.e., with the same structure. Energy savings from fault corrections were estimated to be up to 25% of the primary energy consumption, while the HVAC system was initially considered to have an excellent performance. In the third case study, a demand-driven ventilation system (DCV) was analysed. The analysis showed that the 4S3F method works also to identify faults on an air ventilation system.
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Since the first release of modern electric vehicles, researchers and policy makers have shown interest in the deployment and utilization of charging infrastructure. Despite the sheer volume of literature, limited attention has been paid to the characteristics and variance of charging behavior of EV users. In this research, we answer the question: which scientific approaches can help us to understand the dynamics of charging behavior in charging infrastructures, in order to provide recommendations regarding a more effective deployment and utilization of these infrastructures. To do so, we propose a conceptual model for charging infrastructure as a social supply–demand system and apply complex system properties. Using this conceptual model, we estimate the rate complexity, using three developed ratios that relate to the (1) necessity of sharing resources, (2) probabilities of queuing, and (3) cascading impact of transactions on others. Based on a qualitative assessment of these ratios, we propose that public charging infrastructure can be characterized as a complex system. Based on our findings, we provide four recommendations to policy makers for taking efforts to reduce complexity during deployment and measure interactions between EV users using systemic metrics. We further point researchers and policy makers to agent-based simulation models that capture interactions between EV users and the use complex network analysis to reveal weak spots in charging networks or compare the charging infrastructure layouts of across cities worldwide.
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