This study examines completion rate for a self-assessment survey designed to assess employees' digital skills levels in the workplace. The aim is to improve data quality by investigating completion of the survey. The study reviews the theoretical background related to self-assessment surveys and completion rate, and explores the influence of survey length and format in survey design on completion rate. The research design and data analysis are described in detail, with a focus on identifying factors that may influence completion rate. Results suggest that survey designers should consider using Likert scales to optimize completion rate and completion time. However, this study did not find a significant increase in completion rate as a result of motivation, which was claimed from the literature. The study concludes with implications for the design and implementation of self-assessment surveys in the workplace, including the importance of reducing length and complexity of survey items and questions.
What skills do people need that would like to trade with countries all over the world?
Neoliberal discourse often conceptualizes nature in relation to its market utility and economic development. This article will address the role of metaphors in shaping neoliberal discourse in business education. The aim of this article is to reveal reasoning patterns about environmental problems and economic development in students of sustainable business minor. The case study described in this article involves business students at The Hague University in The Netherlands. This case study aimed to explore a shift in student understanding of environmental problems and economic development before and after the intervention. The results suggest that critical curriculum can inform students about the alternative conceptions as well as instruct them about potential solutions to the sustainability challenges. The article culminates with the argument that without goal-oriented education for sustainability; neoliberal education may not permit transcendence from unsustainable practices. https://doi.org/10.3390/su6117496 https://www.linkedin.com/in/helenkopnina/
MULTIFILE
In the past decades, we have faced an increase in the digitization, digitalization, and digital transformation of our work and daily life. Breakthroughs of digital technologies in fields such as artificial intelligence, telecommunications, and data science bring solutions for large societal questions but also pose a new challenge: how to equip our (future)workforce with the necessary digital skills, knowledge, and mindset to respond to and drive digital transformation?Developing and supporting our human capital is paramount and failure to do so may leave us behind on individual (digital divide), organizational (economic disadvantages), and societal level (failure in addressing grand societal challenges). Digital transformation necessitates continuous learning approaches and scaffolding of interdisciplinary collaboration and innovation practices that match complex real-world problems. Research and industry have advocated for setting up learning communities as a space in which (future) professionals of different backgrounds can work, learn, and innovate together. However, insights into how and under which circumstances learning communities contribute to accelerated learning and innovation for digital transformation are lacking. In this project, we will study 13 existing and developing learning communities that work on challenges related to digital transformation to understand their working mechanisms. We will develop a wide variety of methods and tools to support learning communities and integrate these in a Learning Communities Incubator. These insights, methods and tools will result in more effective learning communities that will eventually (a) increase the potential of human capital to innovate and (b) accelerate the innovation for digital transformation
Under the umbrella of artistic sustenance, I question the life of materials, subjective value structures, and working conditions underlying exhibition making through three interconnected areas of inquiry: Material Life and Ecological Impact — how to avoid the accumulation of physical materials/storage after exhibitions? I aim to highlight the provenance and afterlife of exhibition materials in my practice, seeking economic and ecological alternatives to traditional practices through sustainable solutions like borrowing, reselling, and alternative storage methods that could transform exhibition material handling and thoughts on material storage and circulation. Value Systems and Economic Conditions —what do we mean when we talk about 'value' in relation to art? By examining the flow of financial value in contemporary art and addressing the subjectivity of worth in art-making and artists' livelihoods, I question traditional notions of sculptural skill while advocating for recognition of conceptual labour. The research considers how artists might be compensated for the elegance of thought rather than just material output. Text as Archive and Speculation— how can text can store, speculate, and circulate the invisible labour and layers of exhibition making? Through titles, material lists, and exhibition texts, I explore writing's potential to uncover latent structures and document invisible labor, considering text both as an archiving method and a tool for speculating about future exhibitions. Using personal practice as a case study, ‘Conditions for Raw Materials’ seeks to question notions of value in contemporary art, develop alternative economic models, and make visible the material, financial, and relational flows within exhibitions. The research will manifest through international exhibitions, a book combining poetic auto-theoretical reflection with exhibition speculation, new teaching formats, and long-term investigations. Following “sticky relations," of intimacy, economy and conditions, each exhibition serves as a case study exploring exhibition making from emotional, ecological, and economic perspectives.
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.
