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
To adequately deal with the challenges faced within residential care for older people, such as the increasing complexity of care and a call for more person-centred practices, it is important that health care providers learn from their work. This study investigates both the nature of learning, among staff and students working within care for older people, and how workplace learning can be promoted and researched. During a longitudinal study within a nursing home, participatory and democratic research methods were used to collaborate with stakeholders to improve the quality of care and to promote learning in the workplace. The rich descriptions of these processes show that workplace learning is a complex phenomenon. It arises continuously in reciprocal relationship with all those present through which both individuals and environment change and co-evolve enabling enlargement of the space for possible action. This complexity perspective on learning refines and expands conventional beliefs about workplace learning and has implications for advancing and researching learning. It explains that research on workplace learning is itself a form of learning that is aimed at promoting and accelerating learning. Such research requires dialogic and creative methods. This study illustrates that workplace learning has the potential to develop new shared values and ways of working, but that such processes and outcomes are difficult to control. It offers inspiration for educators, supervisors, managers and researchers as to promoting conditions that embrace complexity and provides insight into the role and position of self in such processes.
From the article: "The educational domain is momentarily witnessing the emergence of learning analytics – a form of data analytics within educational institutes. Implementation of learning analytics tools, however, is not a trivial process. This research-in-progress focuses on the experimental implementation of a learning analytics tool in the virtual learning environment and educational processes of a case organization – a major Dutch university of applied sciences. The experiment is performed in two phases: the first phase led to insights in the dynamics associated with implementing such tool in a practical setting. The second – yet to be conducted – phase will provide insights in the use of pedagogical interventions based on learning analytics. In the first phase, several technical issues emerged, as well as the need to include more data (sources) in order to get a more complete picture of actual learning behavior. Moreover, self-selection bias is identified as a potential threat to future learning analytics endeavors when data collection and analysis requires learners to opt in."
