Uit het vooronderzoekvan het project Duurzamelearning communities: Oogstenin de Greenportblijkt dat12 factorenhierbijvan belangrijk zijn. Deze succesfactoren staan centraal in de interactieve tool Seeds of Innovation. Ook komen uit het vooronderzoek, aangevuld met inzichten uit de literatuur en tips om de samenwerking door te ontwikkelen en meer gebruik te maken van de opbrengsten 12 succesfactoren met toelichting, belangrijkste bevindingen en tips voor ‘hoe nu verder’, Poster, Walk through, De app die learning communities helptde samenwerkingnaareenhogerplan te tillenen innovatieveopbrengstenoptimaalte benutten.
MULTIFILE
Educational programs teaching entrepreneurial behaviour and knowledge are crucial to a vital and healthy economy. The concept of building a Communities of Practice (CoP) could be very promising. CoP’s are formed by people who engage in a process of collective learning in a shared domain of human endeavour (Wenger, McDermott and Snyder, 2002). They consist of a group of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly. Normally CoP’s are rather homogeneous. Saxion institute Small Business & Retail Management (SB&RM) started a CoP with entrepreneurs September 2007. Typical in the this community, are the differences between the partners. The Community consists of students, entrepreneurs and members of an institution for higher education. They have different characteristics and they don’t share the same knowledge. Thus, building long-lasting relations can be complicated. Solid relations for longer periods are nevertheless inevitable in using CoP as a mean in an educational concept that takes approximately 4 years. After one year an evaluation took place on the main aspects of a lasting partnership. The central problem SB&RM in Deventer faces is to design the CoP in a way possible members will join and stay for a longer period and in a way it ensures entrepreneurial learning. This means important design characteristics have to be identified, and the CoP in Deventer has to be evaluated to assess whether it meets those design characteristics in an effective and efficient way. The main target of the evaluation is to determine which key factors are important to make sure continuity in partnership is assured and entrepreneurial learning is best supported. To solve the problem, an investigation on how a CoP works, what group dynamics take place, and how this can be measured has to be conducted. Furthermoreusing the CoP as a tool for entrepreneurship means key aspects of entrepreneurial learning have to be identified. After that the CoP in Deventer has to be examined on both aspects. According to literature CoP’s define themselves along three dimensions: domain (indicating what is it about), community (defining how it functions), and practice (indicating what capabilities it has produced) (Wenger, 1998). This leads to meaningful, shared and coordinated activities (Akkerman et al, 2007): Key aspects of a successful CoP lie in both hard and soft sides of creating a partnership. It means on one hand a CoP has to deal with defining their own overall vision, formulating long term goals and targets on the short term. They have to formulate how to achieve those targets and create meaningful activities (reification). On the other hand a CoP has to deal with relations, trust, norms and values (participation). Reification and participation as design characteristic can provide indicators on which the CoP in Deventer can be evaluated. A lasting partnership means joining the CoP and staying. Weick provides us with a suitable model that enables us to do research and evaluate whether the CoP in Deventer is successful or not, Weick’s model of means convergence. To effectively ensure entrepreneurial learning the process in the CoP has to provide or enable actionoriented forms through Project-based activity, accompanied by reflection, with high emotional exposure (or cognitive affection) preferably caused by discontinuities to be suitable as a tool in entrepreneurial learning. Furthermore it should be accompanied by the right preconditions to work effectively and efficiently. The evaluation of the present CoP in Deventer is done by interviewing all participants at the end of the first year of the partnership. In a structured interview, based on literature studies, all participants were separately questioned
MULTIFILE
Just what and how eight experienced teachers in four coaching dyads learned during a 1-year reciprocal peer coaching trajectory was examined in the present study. The learning processes were mapped by providing a detailed description of reported learning activities, reported learning outcomes, and the relations between these two. The sequences of learning activities associated with a particular type of learning outcome were next selected, coded, and analyzed using a variety of quantitative methods. The different activity sequences undertaken by the teachers during a reciprocal peer coaching trajectory were found to trigger different aspects of their professional development.
DOCUMENT
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
