Hoe kan je met studenten onderwijskwaliteit versterken met behulp van de methodiek participatief actieonderzoek? In deze rapportage lees je hoe studenten van verschillende opleidingen in domein Gezondheid Sport en Welzijn van Hogeschool Inholland hun onderwijs ervaren, met welke acties ze hun onderwijs zouden willen verbeteren, hoe de methode participatief actieonderzoek dit proces vormt en welke kansen en uitdagingen deze methode hierbij biedt. Participatief actieonderzoek; PAO; PAR; participatory action research; student als partner; onderwijskwaliteit; kwaliteitscultuur; studentparticipatie.
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The benefits of having a high indoor environmental quality (IEQ) for a healthy life and optimal performance are well known. In addition, research has been executed on the effects of indoor environmental parameters such as (day)light, sound/ acoustics, temperature, and air quality on people living with dementia.
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De zachte stad. Een term die steeds vaker terugkomt in het debat over de ontwikkeling van onze steden. Een term met een hoog aaibaarheidsgehalte, maar die tegelijkertijd nog veel vragen oproept. In dit magazine van Platform Stad en Wijk duiken we daarom dieper in dit concept. Maar we werpen er ook een kritische blik op: welke blinde vlekken kent dit gedachtegoed en hoe kunnen we de zachte stad in de praktijk brengen?
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Ervaringskennis zijn persoonlijke ervaringen die gebruikt kunnen worden als kennisbron voor persoonlijke ontwikkeling en beroepsontwikkeling. In het bijzonder gaat het om ervaringen die de kwaliteit van leven beïnvloeden. Denk daarbij aan trauma, ziekte, beperkingen of armoede. Dit project gaat over ervaringskennis in mensgerichte beroepen zoals sociaal werk en verpleegkunde.
Lack of physical activity in urban contexts is an increasing health risk in The Netherlands and Brazil. Exercise applications (apps) are seen as potential ways of increasing physical activity. However, physical activity apps in app stores commonly lack a scientific base. Consequently, it remains unknown what specific content messages should contain and how messages can be personalized to the individual. Moreover, it is unknown how their effects depend on the physical urban environment in which people live and on personal characteristics and attitudes. The current project aims to get insight in how mobile personalized technology can motivate urban residents to become physically active. More specifically, we aim to gain insight into the effectiveness of elements within an exercise app (motivational feedback, goal setting, individualized messages, gaming elements (gamification) for making people more physically active, and how the effectiveness depends on characteristics of the individual and the urban setting. This results in a flexible exercise app for inactive citizens based on theories in data mining, machine learning, exercise psychology, behavioral change and gamification. The sensors on the mobile phone, together with sensors (beacons) in public spaces, combined with sociodemographic and land use information will generate a massive amount of data. The project involves analysis in two ways. First, a unique feature of our project is that we apply machine learning/data mining techniques to optimize the app specification for each individual in a dynamic and iterative research design (Sequential Multiple Assignment Randomised Trial (SMART)), by testing the effectiveness of specific messages given personal and urban characteristics. Second, the implementation of the app in Sao Paolo and Amsterdam will provide us with (big) data on use of functionalities, physical activity, motivation etc. allowing us to investigate in detail the effects of personalized technology on lifestyle in different geographical and cultural contexts.
Lack of physical activity in urban contexts is an increasing health risk in The Netherlands and Brazil. Exercise applications (apps) are seen as potential ways of increasing physical activity. However, physical activity apps in app stores commonly lack a scientific base. Consequently, it remains unknown what specific content messages should contain and how messages can be personalized to the individual. Moreover, it is unknown how their effects depend on the physical urban environment in which people live and on personal characteristics and attitudes. The current project aims to get insight in how mobile personalized technology can motivate urban residents to become physically active. More specifically, we aim to gain insight into the effectiveness of elements within an exercise app (motivational feedback, goal setting, individualized messages, gaming elements (gamification) for making people more physically active, and how the effectiveness depends on characteristics of the individual and the urban setting. This results in a flexible exercise app for inactive citizens based on theories in data mining, machine learning, exercise psychology, behavioral change and gamification. The sensors on the mobile phone, together with sensors (beacons) in public spaces, combined with sociodemographic and land use information will generate a massive amount of data. The project involves analysis in two ways. First, a unique feature of our project is that we apply machine learning/data mining techniques to optimize the app specification for each individual in a dynamic and iterative research design (Sequential Multiple Assignment Randomised Trial (SMART)), by testing the effectiveness of specific messages given personal and urban characteristics. Second, the implementation of the app in Sao Paolo and Amsterdam will provide us with (big) data on use of functionalities, physical activity, motivation etc. allowing us to investigate in detail the effects of personalized technology on lifestyle in different geographical and cultural contexts.
