The project had three primary objectives: 1. Innovative digital tools: Develop tools to predict dropout and early school leaving by identifying risks and indicators. Using artificial intelligence (AI) to help allocate guidance, counselling, and social services proactively. 2. Preventive measures: Implement new methods to act on identified risks at an early stage. These services and tools will be available to students regardless of time and place, ensuring continuous support. 3. Active student participation: Engage students in quality assurance processes, allowing them to evaluate and provide feedback on new services. This approach ensures that even typically non-participating students have a voice in the development process.
The dropout rate in vocational education and training (VET) has been a persistent challenge in Europe for decades. Despite numerous projects and studies, dropout prevention methods have largely remained local or national. To address this, we needed innovative solutions to identify students at higher risk of dropping out and develop low-threshold services to support their well-being and commitment. The COVID-19 pandemic highlighted the need for digital solutions to provide continuous support to students, making it essential to integrate digital environments into guidance and counselling services. The use of artificial intelligence is nothing new but using it in such a concrete and practical way in educational institutions could offer an opportunity to support students and allocate human resources preventively and effectively. The participants of the What about then - project have been active in this field and wanted to learn more about the topic. However, a mere system is not enough, functional and innovative ways of acting are also needed when an alarm about the increased risk of a student dropping out appears.