This paper describes a project to explore the possibilities of virtual worlds in educating Green IT. In the project a virtual world has been created with various assignments which are meant to create awareness on sustainability aspects of IT. The world (and the assignments) will be incorporated in a course for first-year IT students. In order to measure the effects of the course, a questionnaire has been developed which can be used before and after the course to measure the attitude towards green IT.
DOCUMENT
In the course of our supervisory work over the years, we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called frequently asked questions (FAQs). This series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By ‘novice’ we mean Master’s students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of qualitative research papers. The second article focused on context, research questions and designs, and referred to publications for further reading. This third article addresses FAQs about sampling, data collection and analysis. The data collection plan needs to be broadly defined and open at first, and become flexible during data collection. Sampling strategies should be chosen in such a way that they yield rich information and are consistent with the methodological approach used. Data saturation determines sample size and will be different for each study. The most commonly used data collection methods are participant observation, face-to-face in-depth interviews and focus group discussions. Analyses in ethnographic, phenomenological, grounded theory, and content analysis studies yield different narrative findings: a detailed description of a culture, the essence of the lived experience, a theory, and a descriptive summary, respectively. The fourth and final article will focus on trustworthiness and publishing qualitative research.
DOCUMENT
Within paediatric palliative care, it is essential for families and providers to have open, equal, and trusting relationships. In practice, however, building relationships can be challenging. Investing in better understanding the differences in each other's frames of reference and underlying values seems important. Wonder Lab practices provide a space to explore these differences by focusing together on life phenomena in curious and Socratic ways. Wonder Labs were organised with parents, healthcare professionals, and students involved in Dutch paediatric palliative care. The aim of this study was to develop an understanding of how participants experienced participating in Wonder Labs. We conducted twenty in-depth interviews with Wonder Lab participants and used inductive thematic analysis for data interpretation. Five themes were identified: Slowing down, Appreciating stories, Becoming vulnerable, Opening up and diving in, and Reframing perspectives. Participating in Wonder Labs allowed mothers, healthcare professionals, and students to contribute to deepening experiences and gain an expanded understanding of what is at play in caring for children with life-limiting and life-threatening conditions. Through working in pluralised groups, frames of reference and understandings complemented each other and could change. Participants often adopted a more open attitude towards others involved in care after participating and adapted day-to-day practices. Deliberating within paediatric palliative care on sensitive issues and their underlying personal and professional beliefs and values must be part of working together, without specific care situations being the catalyst. This may foster the mutual understanding needed in searching for quality of life, death, and bereavement.
MULTIFILE
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.