Voortdurende maatschappelijke veranderingen en uitdagingen vragen om samenwerking en een leven lang ontwikkelen. Vaak gebeurt dit in learning communities (innovatieve leerwerkomgevingen) waar organisaties grensoverstijgend samenwerken aan complexe vraagstukken. Bruggenbouwers (brokers) hebben een sleutelpositie in het ontwikkelen van deze learning communities om mensen en organisaties met elkaar te verbinden. Een veelzijdige rol die zich moeilijk laat definiëren. Bovendien voorzien organisaties niet altijd bewust in ondersteuning en ontwikkeling van deze bruggenbouwers. Op basis van een mixed-methodsbenadering voorziet dit onderzoek in de behoefte van een generieke rolbeschrijving met zeven vaardigheden. Hierbij wordt de invloed van kennis, ervaring en persoonskenmerken belicht. Bruggenbouwers werken intersectoraal over grenzen van organisaties heen en ondersteunen betrokken professionals en organisaties in hun samenwerking door politiek bewust en strategisch te handelen. Zij stimuleren kennisdeling en vertalen kennis naar diverse betrokkenen en contexten en onderzoeken daarbij de beroepspraktijk systematisch. Deze rolbeschrijving en de gewenste ondersteuning hierin biedt concrete handvatten om bruggenbouwers beter te selecteren, te waarderen en ook gerichter te investeren in hun professionele ontwikkeling. Deze investering is van cruciaal belang omwille van de katalyserende werking van de rol als bruggenbouwer om het voortdurend leren en ontwikkelen bij organisaties mogelijk te maken
Extended Reality (XR) technologies—including virtual reality (VR), augmented reality (AR), and mixed reality (MR)—offer transformative opportunities for education by enabling immersive and interactive learning experiences. In this study, we employed a mixed-methods approach that combined systematic desk research with an expert member check to evaluate existing pedagogical frameworks for XR integration. We analyzed several established models (e.g., TPACK, TIM, SAMR, CAMIL, and DigCompEdu) to assess their strengths and limitations in addressing the unique competencies required for XRsupported teaching. Our results indicate that, while these models offer valuable insights into technology integration, they often fall short in specifying XR-specific competencies. Consequently, we extended the DigCompEdu framework by identifying and refining concrete building blocks for teacher professionalization in XR. The conclusions drawn from this research underscore the necessity for targeted professional development that equips educators with the practical skills needed to effectively implement XR in diverse educational settings, thereby providing actionable strategies for fostering digital innovation in teaching and learning.
MULTIFILE
Post-earthquake structural damage shows that wall collapse is one of the most common failure mechanisms in unreinforced masonry buildings. It is expected to be a critical issue also in Groningen, located in the northern part of the Netherlands, where human-induced seismicity has become an uprising problem in recent years. The majority of the existing buildings in that area are composed of unreinforced masonry; they were not designed to withstand earthquakes since the area has never been affected by tectonic earthquakes. They are characterised by vulnerable structural elements such as slender walls, large openings and cavity walls. Hence, the assessment of unreinforced masonry buildings in the Groningen province has become of high relevance. The abovementioned issue motivates engineering companies in the region to research seismic assessments of the existing structures. One of the biggest challenges is to be able to monitor structures during events in order to provide a quick post-earthquake assessment hence to obtain progressive damage on structures. The research published in the literature shows that crack detection can be a very powerful tool as an assessment technique. In order to ensure an adequate measurement, state-of-art technologies can be used for crack detection, such as special sensors or deep learning techniques for pixel-level crack segmentation on masonry surfaces. In this project, a new experiment will be run on an in-plane test setup to systematically propagate cracks to be able to detect cracks by new crack detection tools, namely digital crack sensor and vision-based crack detection. The validated product of the experiment will be tested on the monument of Fraeylemaborg.
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
Post-earthquake structural damage shows that wall collapse is one of the most common failure mechanisms in unreinforced masonry buildings. It is expected to be a critical issue also in Groningen, located in the northern part of the Netherlands, where human-induced seismicity has become an uprising problem in recent years. The majority of the existing buildings in that area are composed of unreinforced masonry; they were not designed to withstand earthquakes since the area has never been affected by tectonic earthquakes. They are characterised by vulnerable structural elements such as slender walls, large openings and cavity walls. Hence, the assessment of unreinforced masonry buildings in the Groningen province has become of high relevance. The abovementioned issue motivates engineering companies in the region to research seismic assessments of the existing structures. One of the biggest challenges is to be able to monitor structures during events in order to provide a quick post-earthquake assessment hence to obtain progressive damage on structures. The research published in the literature shows that crack detection can be a very powerful tool as an assessment technique. In order to ensure an adequate measurement, state-of-art technologies can be used for crack detection, such as special sensors or deep learning techniques for pixel-level crack segmentation on masonry surfaces. In this project, a new experiment will be run on an in-plane test setup to systematically propagate cracks to be able to detect cracks by new crack detection tools, namely digital crack sensor and vision-based crack detection.
