AI & education at Maastricht University
Source: https://www.maastrichtuniversity.nl/education/edlab/ai-education-maastricht-university Parent: https://www.maastrichtuniversity.nl/
Artificial Intelligence (AI) and other 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.
Maastricht University has created a policy framework for generative artificial intelligence (GenAI). This document explains UM's position on GenAI and provides guidelines for its responsible use in education, research and business.
Large Language Models & education
What are the benefits and limitations of integrating Large Language Model (LLM) functionalities into our education and assessment practices?
GenAI training activities offered by UM
EDLAB and UM offer training programmes for efficient and ethical use of GenAI tools.
Precautions and risks of GenAI
Using GenAI tools can have data privacy and other risks.
GenAI for students
GenAI tools can be beneficial for educational and study-related tasks.
AI Prompt Library
The AI Prompt Library launched in October 2024, provides basic tips on what to consider while prompting.
Resources
Explore our curated collection of resources on GenAI.
Latest news
How does AI affect how we learn?
Artificial intelligence is changing how students approach learning but does it actually help us understand more deeply? In this article, cognitive psychologist Dan Quinn explains why real learning happens when the work feels effortful, and how relying too heavily on AI tools might limit long-term understanding.
Jean Baudrillard predicted today’s AI, 30 years before ChatGPT
Long before ChatGPT and generative AI, French philosopher Jean Baudrillard explored the idea of simulated realities and the blurring of truth and illusion. This piece revisits his theories through the lens of modern AI, showing how his work anticipated the challenges we face in distinguishing human expression from machine-generated content.
Voxweb: “Children with a chainsaw” – a cautionary view on AI
In a recent interview, Dutch AI expert Pim Haselager compared our current use of AI to “children with a chainsaw,” urging stronger regulation of tech giants like OpenAI and Google. He supports Europe’s cautious approach through the AI Act and GDPR, which prioritise human rights and ethics which offers a path to global leadership if universities remain well supported.
A Dutch LLM for higher education: EduGenAI enters pilot phase
The Dutch Npuls programme is piloting EduGenAI, a secure, education-specific AI platform set to transform learning across higher education. Designed with privacy and academic integrity at its core, EduGenAI offers universities a powerful alternative to commercial AI tools, and 30+ institutions are already testing it.
GenAI4EU: Europe’s campaign for homegrown Generative AI
The GenAI4EU initiative funds trusted, European-made generative AI for sectors like education and healthcare. With nearly €700 million available, it supports LLM development, public sector use, and collaboration between universities, startups, and EU states, offering ethical, homegrown alternatives to non-European AI tools.
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.
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Disclaimer
The information on this page presents examples to UM students and staff on how to make better use of Generative AI (GenAI) in the educational process. Maastricht University does not recommend the use of any specific GenAI tool. However, you are strongly advised to opt-out of allowing your content to be used to (further) train the GenAI tool of your choice. This can usually be done in Settings.
Given that all information entered into an AI tool will be stored and can be reused by the GenAI tool provider as they deem fit, one should not feed: UM- data, confidential information and trade secrets; personal data and sensitive data relating to you or other people; copyrighted materials (such as books, academic articles e.t.c.), but also materials for which the UM is the copyright holder, such as educational materials including coursebooks, syllabi, ppt, e.t.c.
Certain GenAI practices in education may not be allowed or encouraged within your faculty’s policy framework and/or rules and regulations. Please check first any relevant rules on the use of GenAI in education, applicable to you, and defined at activity, course/module, study programme and faculty level.
GenAI can only be employed for high-risk practices under strict conditions set out in the EU AI Act. UM currently refrains from employing GenAI in relation to student assessment, selection and admission procedures, monitoring and detection of prohibited behaviour during exams, pending further thorough investigation of the conditions.