AI & education at Maastricht University
Artificial Intelligence (AI) and data-driven technologies have the potential to address some of the biggest needs in education today and innovate teaching and learning practices. However, rapid technological developments inevitably bring multiple risks and challenges.
Maastricht University recognises the importance of tapping into the opportunities of AI technologies while ensuring a safe and effective integration of such technologies into the PBL curriculum in alignment with the core learning principles Contextual, Collaborative, Constructive and Self-directed (CCCS).
EDLAB is currently running a Community of Practice on AI & education open to all staff members. Please join the conversation on Teams!
This page examines the educational implications of AI applications.
Contact
For more information, please contact:
Walter Jansen, Senior Coordinator Innovation at EDLAB
Spoorti Ramesh, Student assistant at EDLAB
For specific questions about the AI policy framework, please contact:
Lars Nabuurs.

Disclaimer
The information on this webpage presents information about and examples of GenAI usage for educational design, delivery and assessment practices. Certain GenAI practices in education may not be encouraged or allowed within your faculty’s policy framework and/or rules and regulations. When in doubt, please check the recent faculty rules on the use of GenAI in education.
UM doesn’t recommend to use GenAI for assessment of students since the EU AI-act flags such practices as high risk. More specifically the following assessment practices with the help of GenAI should be avoided:
- Determining access or admission of students to educational institutions or programmes
- Evaluating students' learning outcomes
- Assessing the appropriate educational level for a student
- Monitoring and detecting unauthorised behaviour by students during exams