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.
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Criminologists have frequently debated whether offenders are specialists, in that they consistently perform either one offense or similar offenses, or versatile by performing any crime based on opportunities and situational provocations. Such foundational research has yet to be developed regarding cybercrimes, or offenses enabled by computer technology and the Internet. This study address this issue using a sample of 37 offender networks. The results show variations in the offending behaviors of those involved in cybercrime. Almost half of the offender networks in this sample appeared to be cybercrime specialists, in that they only performed certain forms of cybercrime. The other half performed various types of crimes on and offline. The relative equity in specialization relative to versatility, particularly in both on and offline activities, suggests that there may be limited value in treating cybercriminals as a distinct offender group. Furthermore, this study calls to question what factors influence an offender's pathway into cybercrime, whether as a specialized or versatile offender. The actors involved in cybercrime networks, whether as specialists or generalists, were enmeshed into broader online offender networks who may have helped recognize and act on opportunities to engage in phishing, malware, and other economic offenses.
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Learning objects are bits of learning content. They may be reused 'as is' (simple reuse) or first be adapted to a learner's particular needs (flexible reuse). Reuse matters because it lowers the development costs of learning objects, flexible reuse matters because it allows one to address learners' needs in an affordable way. Flexible reuse is particularly important in the knowledge economy, where learners not only have very spefic demands but often also need to pay for their own further education. The technical problems to simple and flexible are rapidly being resolved in various learning technology standardisation bodies. This may suggest that a learning object economy, in which learning objects are freely exchanged, updated and adapted, is about to emerge. Such a belief, however, ignores the significant psychological, social and organizational barriers to reuse that still abound. An inventory of these problems is made and possible ways to overcome them are discussed.
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Door producten en diensten inclusief te ontwerpen kunnen ontwerpers een belangrijke bijdrage leveren aan een inclusievere samenleving, waarin iedereen op eigen wijze kan participeren. In AID gaan negen mkb-ontwerpbureaus Afdeling Buitengewone Zaken (A/BZ), theRevolution, Design Innovation Group, Greenberry, Ideate, Keen Public, Muzus, Netrex Internet Solutions (Leer Zelf Online) en Vrienden van verandering) die rijke maar uiteenlopende ervaring hebben met inclusief ontwerpen op zoek naar antwoorden op de vraag hoe hun vermogen voor inclusief ontwerpen kan worden versterkt. Ze doen dit middels actie-onderzoek in hun eigen beroepspraktijk en door hun ervaringen te delen met onderzoekers, docenten en co-ontwerpers in een ‘learning community’.
Studenten in het beroepsonderwijs leren op de werkplek om een goede beroepsuitoefenaar te worden. Beoordeling van het werkplekleren gebeurt vaak op de werkplek en door de werkplek. Dit promotieonderzoek wil in kaart brengen hoe werkplekopleiders de student beoordelen.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.