Assessment in higher education (HE) is often focused on concluding modules with one or more tests that students need to pass. As a result, both students and teachers are primarily concerned with the summative function of assessment: information from tests is used to make pass/fail decisions about students. In recent years, increasing attention has been paid to the formative function of assessment and focus has shifted towards how assessment can stimulate learning. However, this also leads to a search for balance between both functions of assessment. Programmatic assessment (PA) is an assessment concept in which their intertwining is embraced to strike a new balance. A growing number of higher education programmes has implemented PA. Although there is consensus about the theoretical principles that form the basis for the design of PA, programmes make various specific design choices based on these principles, fitting with their own context. This paper provides insight into the design choices that programmes make when implementing PA and into the considerations that play a role in making these design choices. Such an overview is important for research purposes because it creates a framework for investigating the effects of different design choices within PA.
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A growing number of higher education programmes in the Netherlands has implemented programmatic assessment. Programmatic assessment is an assessment concept in which the formative and summative function of assessment is intertwined. Although there is consensus about the theoretical principles of programmatic assessment, programs make various specific design choices, fitting with their own context. In this factsheet we give insight into the design choices Dutch higher education programmes make when implementing programmatic assessment.
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AbstractDue to the crisis of 2008 the construction and real estate market became more demand-driven. Architects, builders and developers are looking for high-quality solutions for the realization of sustainable buildings. Supplying SMEs experience an increasing demand for bio-based materials with lower environmental impact and additional functionality including smart functions. The development of sustainable products with higher added value is required to increase the innovation potential of the building and construction industries.Polypyrrole is a biopolymer with very interesting and yet relatively unexplored features for construction. By applying PPY to bio-based carrier materials, like wood, bamboo or bio-composites, environmentally friendly building products can be realized with multiple features. In this paper an inventory will be given of potential (smart) functions that can be added to bio-based building materials treated with PPY. Functions discussed will be the protection against micro-organisms and UV-radiation. It will allow the realization of biological multifunctional building façades without using environmentally harmful substances.Finally the adding of (smart) functions will be discussed as strategy to introduce new bio-based building components to the market. Here they will have to compete with existing products already known by the different building professionals.
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In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
Automation is a key enabler for the required productivity improvement in the agrifood sector. After years of GPS-steering systems in tractors, mobile robots start to enter the market. Localization is one of the core functions for these robots to operate properly on fields and in orchards. GNSS (Global Navigation Satellite System) solutions like GPS provide cm-precision performance in open sky, but buildings, poles and biomaterial may reduce system performance. On top, certain areas do not provide a dependable grid communication link for the necessary GPS corrections and geopolitics lead to jamming activities. Other means for localization are required for robust operation. VSLAM (Visual Simultaneous Localization And Mapping) is a complex software approach that imitates the way we as humans learn to find our ways in unknown environments. VSLAM technology uses camera input to detect features in the environment, position itself in that 3D environment while concurrently creating a map that is stored and compared for future encounters, allowing the robot to recognize known environments and continue building a complete, consistent map of the environment covered by its movement. The technology also allows continuous updating of the map in environments that evolve over time, which is a specific advantage for agrifood use cases with growing crops and trees. The technology is however relatively new, as required computational power only recently became available in tolerable cost range and it is not well-explored for industrialized applications in fields and orchards. Orientate investigates the merits of open-source SLAM algorithms on fields - with Pixelfarming Robotics and RapAgra - and in an orchard - with Hillbird - preceded by simulations and initial application on a HAN test vehicle driving in different terrains. The project learnings will be captured in educational material elaborating on VSLAM technology and its application potential in agrifood.
