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Gifted students in Flanders often fall behind despite emphasis on excellence. This project creates a new way to measure their well-being. It combines surveys with sensor data (e.g., app) for a more accurate picture, avoiding limitations of self-reporting. Advanced analysis (AI) will help understand their needs better.

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Quick facts

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    Project with HIT Lab

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    PWO project

In Flemish education, there is often talk of working excellently and maximizing talent, but at the same time, the least attention is paid to those who have the most potential and, as a result, they are at risk of dropping out.

This two-year study focuses on objectively assessing the well-being of intellectually gifted students within secondary education. An objective well-being measurement method is developed by combining various subjective research methods and linking them with objective physiological data. This approach largely mitigates the disadvantages (and therefore potential inaccuracies and criticisms) associated with subjective well-being data, typically gathered through self-reporting. To collect data, various sensors and an app are used, and the data is analyzed utilizing today's technological capabilities, including AI and DML.


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    Gilles Depypere, Research Manager AI Lab

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    Lore Leenknegt, Applied AI Researcher

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