Date & Time:
🗓️ 19 June 2025 | 14:00 CET
🕐 1-hour webinar
🌐 Free | In English
Register for the webinar here.
Description:
How can AI and data help us better support students and reduce dropout?
In this webinar, two experienced professionals from the Netherlands and Belgium share their perspectives on using data and predictive AI to identify students in need before problems escalate. We’ll hear practical examples from vocational and higher education contexts, and explore the possibilities and limitations of data-driven student support.
🎙 Speakers:
Tom Madou – Researcher & Lecturer, VIVES University of Applied Sciences & KU Leuven (BE)
“Exploring the Potential of Explainable AI in Supporting Student Learning”
Tom’s research focuses on using predictive AI and learning analytics to improve student outcomes. His work explores how logs of student activity can be used to spot early signs of academic risk.
Arno den Otter – Team Leader, Student Affairs Office, Zuid-Holland Oost (NL)
“Dropout prevention through the use of data in the Netherlands”
With 10+ years of experience in student support in vocational education (MBO), Arno leads a team focused on dropout prevention, attendance monitoring, and re-engagement of students who have left education.
Who should join?
This session is for professionals in vocational and higher education working with student success, guidance, well-being, or institutional development 👉 Register now!