Learning by creating qualitative representations is a valuable approach to learning. However, modelling is challenging for students, especially in secondary education. Support is needed to make this approach effective. To address this issue, we explore automated support provided to students while they create their qualitative representation. This support is generated form a reference model that functions as a norm. However, the construction of a reference models is still a challenge. In this paper, we present the reference model that we have created to support students in learning about the melatonin regulation in the context of the biological clock.
DOCUMENT
We need mental and physical reference points. We need physical reference points such as signposts to show us which way to go, for example to the airport or the hospital, and we need reference points to show us where we are. Why? If you don’t know where you are, it’s quite a difficult job to find your way, thus landmarks and “lieux de memoire” play an important role in our lives.
LINK
Peak oxygen uptake (V'O2peak) is recognised as the best expression of aerobic fitness. Therefore, it is essential that V'O2peak reference values are accurate for interpreting a cardiopulmonary exercise test (CPET). These values are country specific and influenced by underlying biological ageing processes. They are normally stratified per paediatric and adult population, resulting in a discontinuity at the transition point between prediction equations. There are currently no age-related reference values available for the lifespan of individuals in the Dutch population. The aim of this study is to determine the best-fitting regression model for V'O2peak in the healthy Dutch paediatric and adult populations in relation to age. In this retrospective study, CPET cycle ergometry results of 4477 subjects without reported somatic diseases were included (907 females, age 7.9-65.0 years). Generalised additive models were employed to determine the best-fitting regression model. Cross-validation was performed against an independent dataset consisting of 3518 subjects (170 females, age 6.8-59.0 years). An additive model was the best fitting with the largest predictive accuracy in both the primary (adjusted R2=0.57, standard error of the estimate (see)=556.50 mL·min-1) and cross-validation (adjusted R2=0.57, see=473.15 mL·min-1) dataset. This study provides a robust additive regression model for V'O2peak in the Dutch population.
LINK
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Mode heeft een cruciale functie in de samenleving: zij maakt diversiteit en inclusiviteit mogelijk en is een middel voor individuen om zich uit te drukken. Desalniettemin is mode ook een raadsel op het gebied van duurzaamheid, zowel aan de sociale als aan de milieukant. Er bestaan echter alternatieven voor de huidige praktijken in de mode. Dit project heeft tot doel de ontwikkeling van een van die initiatieven te ondersteunen. In samenwerking met twee Nederlandse MKB bedrijven in de mode-industrie, willen we een of meer business modellen co-designen voor het vermarkten van circulair ontworpen laser geprinte T-shirts. Door lasertechnologie te introduceren in plaats van traditionele inktopties, kunnen de T- shirts hun CO2 voetafdruk verder verkleinen en een verstandig alternatief zijn voor individuen, die op zoek zijn naar duurzame modekeuzes. Maar hoewel de technologische haalbaarheid vaststaat, vereist het vermarkten sterke, schaalbare, bedrijfsmodellen. Via een haalbaarheidsstudie willen we dergelijke businessmodellen ontwikkelen en de commercialisering van deze producten ondersteunen. Wij zijn van plan de reacties van de consument op een dergelijke innovatie te bestuderen, evenals de belemmeringen en stimulansen vanuit het oogpunt van de consument, en de inkoop-, toeleveringsketen- en financiële kwesties die kunnen voortvloeien uit de schaalbaarheid van een potentieel bedrijfsmodel. Om praktische relevantie voor de bredere industrie te verzekeren, streven we ernaar om de resultaten te presenteren op evenementen georganiseerd door een van de consortiumpartners (in 2023), als ook om een teaching case en een wetenschappelijk artikel te ontwikkelen op basis van de resultaten van het project.
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
