Over 60 million tons of E-waste is expected to be generated in 2023, with associated significant impacts on health and the environment. To reduce the number of products sent to landfills, "Right to Repair" (RtR) movements are gaining momentum in many countries, including the UK, USA, and EU member states. While Universities are seen as important stakeholders to drive forward sustainable design practices, there is currently little work looking at training undergraduate design engineers in the principles of designing household products in support of RtR. In particular, the project-based learning (PBL) pedagogy shows promise in engaging and training students with the skills and knowledge required to successfully design products for RtR. In this paper, a pilot-study of teaching engineers is presented to design products compatible with RtR principles, alongside many technical skills, in a first-year PBL course. The key outputs of this paper are the design of the module, which can be used to help inform first-year engineering education, the high engagement of students, with 100% of respondents agreeing that they intend to try to implement sustainable design practices in future, and some of the innovative features that students implement in their projects.
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http://dx.doi.org/10.1002/gch2.202300158 | DOI Listing |
MethodsX
June 2025
Faculty of Design and Art, University of Wuppertal, 42119 Wuppertal, Germany.
Project-based learning, with its emphasis on 'learning by doing', is the dominant teaching method in industrial design. Learners are supposed to be motivated to tackle complex problems such as those in the dynamic field of sustainability. However, it is still unclear how the process of increasing motivation within projects can be systematically targeted for specific sustainability challenges and directed towards potential later pro-environmental behavior.
View Article and Find Full Text PDFJ Health Monit
December 2024
National Institute for Public Health and the Environment (RIVM), Centre for Public Health, Healthcare and Society, Bilthoven, The Netherlands.
Background: The European Core Health Indicators (ECHI) are a set of 88 indicators that provide a compact overview of the extensive field of European public health and healthcare. The ECHI set adds value to European Union health information systems (HIS) for both Member States and EU-associated countries and the European Commission by providing a solid, comparable information base on national public health and healthcare trends and developments. The indicators allow for learning by comparison and the list supports the organisation of national health information systems.
View Article and Find Full Text PDFThe American Heart Association's (AHA) Life's Essential 8 (LE8) metrics provide a framework for assessing cardiovascular health (CVH). This study evaluates the relationship between CVH levels from LE8 and mortality risk, considering biological aging's role. Using data from the NHANES non-CVD adult population, CVH scores were categorized as low (< 50), moderate (50-79), and high (≥ 80) per AHA guidelines.
View Article and Find Full Text PDFJ Educ Health Promot
November 2024
Department of Biostatistics, National Institute of Mental Health and Neuro Sciences, Bengaluru, Karnataka, India.
Background: Agile methodology (AM) is an innovative, active, project-based learning method. The scrum is a popular agile framework widely used in project management and education. This study evaluates the opinions on agile adaptation in nursing curricula among nursing students to identify how AM can be applied in higher education to facilitate learning.
View Article and Find Full Text PDFMayo Clin Proc Digit Health
December 2024
Department Radiology, Stanford University, Stanford, CA.
Artificial intelligence (AI) and machine learning (ML) are driving innovation in biosciences and are already affecting key elements of medical scholarship and clinical care. Many schools of medicine are capitalizing on the promise of these new technologies by establishing academic units to catalyze and grow research and innovation in AI/ML. At Stanford University, we have developed a successful model for an AI/ML research center with support from academic leaders, clinical departments, extramural grants, and industry partners.
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