The rise of generative AI offers great opportunities for education, but it also comes with challenges. How can we support educators in using AI responsibly and effectively in their teaching? Erasmus University Rotterdam (EUR) has developed a range of resources to help, including practical training sessions, tools, knowledge sharing, and collaboration. In this article, you can learn more about these initiatives.
Collaborating on AI in Education
The rapid rise of AI presents new challenges for education. There are risks, such as issues with assessment and data usage, but there are also opportunities to enhance education. For example, AI can save time for teachers or provide personalised learning experiences for students. At EUR, various teams are working together with faculties to support educators in using AI. This is done in line with the strategic impact domain 'The responsible use of technologies'.
- Community for Learning & Innovation (CLI): organises training sessions (in collaboration with Risbo) and provides support for teachers.
- Universiteitsbibliotheek (UB): offers information about AI.
- AI@EUR: officially launches in April and will contribute to the support available, for example through its recently launched website.
- ECDA: provides space to learn and experiment with Generative AI.
A wide range of resources for teachers
To support teachers, EUR offers a broad selection of tools, training sessions, and collaboration opportunities. These initiatives are organised around three key themes: training, tools, and knowledge sharing.
1. Training
A great starting point for teachers is the TeachEUR AI theme page, which provides practical AI strategies, examples, and teaching methods for the responsible use of AI in education. Additionally, the CLI offers short, practical training sessions, such as MicroLabs:
For teachers who prefer to learn at their own pace, e-modules are also available: the e-learning course 'Integrating GenAI into your classroom', offered by the University Library, and three self-study modules on Canvas covering academic questioning, designing AI-based assignments, and ensuring validity, developed by the CLI in collaboration with Risbo.
2. Tools
At EUR, educators and students work with Erudite, a secure AI tool that offers similar functionalities to ChatGPT but operates within a privacy-protected environment. Additionally, a Prompt Library is available, featuring a growing collection of prompts that teachers can use to integrate AI into their teaching practices. Jonathan Flores Minuesa, learning innovator at the CLI and the creator of the Prompt Library, explains: "The idea for the prompt library came from the fact that useful prompts are often created in isolation, stored in personal notes, and hardly ever reused. With the library, we try to centralize prompts that work in real higher-education contexts, so others can start from proven examples, adapt them to their own setting, and iterate faster." The Prompt Library is designed for everyone in higher education, not just teachers and students. Jonathan: "We decided to structure prompts based on what you are trying to achieve, rather than who you are. A student doesn't only learn, they also do research, might teach occasionally, and definitely are also focused on getting things done. So in practice, any role in higher education will be able to use prompts from all of the four categories on the prompt library."
3. Knowledge Sharing
The CLI facilitates various opportunities for inspiration and exchange around (Gen)AI. For example, a recent exchange session on AI chatbots was held in the Education Lab for everyone at EUR involved in chatbot development. The strong interest in this topic highlights the significant activity within the university. This group is working on the safe and efficient development of chatbots. The CLI newsletter regularly shares practical examples, such as this article, where teachers explain how they use AI for podcasts, advanced feedback and assessment tools, and AI-driven prototyping. Other great examples of knowledge sharing include the AI Teaching Fellowship and the monthly GenAI Meetups.
Knowledge Sharing | AI Teaching Fellowship
Within the AI Teaching Fellowship, teachers are supported in expanding their AI knowledge and acting as ambassadors within their faculty. Dr Maurice de Rochemont, lecturer at Rotterdam School of Management (RSM) and AI Teaching Fellow, explains that AI is being explored in various ways at RSM. For instance, there is a GenAI EdTech group focused on research, developing best practices, and sharing insights. Additionally, workshops are organised at the programme level and within departments to share knowledge and examples of AI use in education. By collaborating with AI Teaching Fellows from other faculties, Maurice has gained valuable insights. "It gave me new perspectives on AI and broadened my thinking. It also reinforced that AI has both opportunities and risks: for example, it can support faster idea generation and early experimentation, but if used without clear guidance and incentives, it risks reducing students’ critical thinking through cognitive offloading."
Knowledge Sharing | GenAI Monthly Meetups
Each month, the CLI organises a GenAI Meetup. Kira van de Berg, student assistant at the CLI, is involved in coordinating these monthly sessions and highlights their value. Kira explains: "During the GenAI Monthly Meetups, we look at how you can use AI responsibly; how do you write a good prompt, and how do you check whether your AI output is factually correct?" In addition to gaining practical skills, the meetups also offer a unique opportunity to explore new perspectives together with others. "This is what makes learning about GenAI with others (like we do during the GenAI Meetups) so valuable: you are encouraged to discover new perspectives, which happens more easily and naturally when you discuss GenAI with others."
National Collaboration through Npuls
Through the national growth fund programme Npuls, EUR collaborates with other educational institutions (universities, universities of applied sciences, and vocational schools) to create a future-proof education sector. One of the ambitions is ethical and effective use of AI and data. This involves developing a shared vision, frameworks, and facilities, as well as working together on AI and data literacy for both teachers and students. There are many opportunities for exchange, knowledge sharing, and collaboration in the AI domain, which is new and constantly evolving. Npuls helps facilitate this. A concrete example is the tool EduGenAI: a shared environment for the safe use of AI, ensuring user privacy.
New projects
At EUR, we continue to work on new initiatives to support teachers. Some examples include:
- Through a Npuls incentive grant, the CLI is developing a new MicroLab on AI and learning, focused on the smart and meaningful use of AI in education. This MicroLab will be launched after the summer.
- The CLI will soon launch a podcast series on AI and writing. This offers a less time-intensive way of sharing knowledge, aiming to enhance teachers' understanding of AI in relation to writing.
- CLI is also conducting research into grading with AI, exploring how AI can make the grading process more efficient. Other institutions are addressing this issue as well, so coordination and collaboration (within Npuls) are logical next steps.
- Finally, CLI is working on a clear AI learning pathway for teachers, based on good examples from other universities and the AI-GO framework for AI literacy. This allows us to leverage the growing knowledge infrastructure in higher education.
- More information
EUR offers a great range of resources for teachers who want to enrich their teaching responsibly with AI. In collaboration with faculties and other partners, we continue to expand this offering. Hopefully, the resources mentioned in this article provide you with the tools to get started. Do you have any questions? Feel free to reach out via cli@eur.nl or npuls@eur.nl.
- Related links
- Teach with AI
News, events, professional development, and projects via CLI
Npuls and EUR
