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.
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.
Specific approaches are needed to reach and support people with a lower socioeconomic position (SEP) to achieve healthier eating behaviours. There is a growing body of evidence suggesting that digital health tools exhibit potential to address these needs because of its specific features that enable application of various behaviour change techniques (BCTs). The aim of this scoping review is to identify the BCTs that are used in diet-related digital interventions targeted at people with a low SEP, and which of these BCTs coincide with improved eating behaviour. The systematic search was performed in 3 databases, using terms related to e/m-health, diet quality and socioeconomic position. A total of 17 full text papers were included. The average number of BCTs per intervention was 6.9 (ranged 3–15). BCTs from the cluster ‘Goals and planning’ were applied most often (25x), followed by the clusters ‘Shaping knowledge’ (18x) and ‘Natural consequences’ (18x). Other frequently applied BCT clusters were ‘Feedback and monitoring’ (15x) and ‘Comparison of behaviour’ (13x). Whereas some BCTs were frequently applied, such as goal setting, others were rarely used, such as social support. Most studies (n = 13) observed a positive effect of the intervention on eating behaviour (e.g. having breakfast) in the low SEP group, but this was not clearly associated with the number or type of applied BCTs. In conclusion, more intervention studies focused on people with a low SEP are needed to draw firm conclusions as to which BCTs are effective in improving their diet quality. Also, further research should investigate combinations of BCTs, the intervention design and context, and the use of multicomponent approaches. We encourage intervention developers and researchers to describe interventions more thoroughly, following the systematics of a behaviour change taxonomy, and to select BCTs knowingly.
Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low. As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers. To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is: How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems? HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases: I. Highway: non-professional drivers; II. Distribution Centre: professional drivers.
Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low.As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers.To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is:How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems?HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases:I. Highway: non-professional drivers;II. Distribution Centre: professional drivers.Collaborative partners:Bielefeld University of Applied Sciences, Bricklog B.V., Goudappel B.V., HaskoningDHV Nederland B.V., Rhine-Waal University of Applied Sciences, Rijkswaterstaat, Saxion, Sencure B.V., Siemens Industry Software Netherlands B.V., Smits Opleidingen B.V., Stichting Innovatiecentrum Verkeer en Logistiek, TNO Den Haag, TU Delft, University of Twente, V-Tron B.V., XL Businesspark Twente.
Sustainable business decision-making as villagers of the world In making our society resilient and future-proof we are faced with many complex and multi-faceted challenges and opportunities. Many promising sustainable initiatives require the proactive contribution of businesses to be successful, but fail to reach the required decision making level of individuals and companies, and thus fail to reach their positive impact. The result is a multiple waste: in creativity and innovation, in investment of the organisations involved, in opportunities to improve society and in our overall belief that we can make the necessary changes. In this project we focus on the reasons why individuals and thus companies act and decide negatively on new and existing sustainable innovations and projects, starting from the perspective that a professional’s and a company’s inherent sustainable decision making is at the heart of truly improving society. The aim is to create multiple value (economic, social and ecological) of SMEs by increasing the success rate of sustainability initiatives out of an implicit business professional’s choice to do so. Based on the theory of psychological distance, we combine exploratory case studies of successful pilots with exploratory research via interviews with business decision makers, to analyse what drives professional’s and companies’ decision making, and how this affects sustainable initiatives. The aim is to propose ways to increase the quality of sustainable decision making, and thus the likelihood of success. The learnings are translated to practical guidelines a SME should consider for executing their business in the most sustainable way, and form a base for further applied research on sustainable business behaviour towards a circular economy.
