From AI-generated podcasts to advanced assessment and feedback tools: In this article, three teachers from Erasmus University Rotterdam (EUR) share how they each use Generative AI (GenAI) in education.
“Experimenting with GenAI is essential to elevate education to the next level, but make sure to do it responsibly and involve the right people at EUR from the start.”
Generative AI at EUR
Generative AI (GenAI) is a form of artificial intelligence capable of actively creating new content, such as text, images, music, or videos, based on the data it has been trained on. The rapid developments in GenAI in recent years have had a significant impact on (higher) education. Within universities, the debate (rightly) focuses on the challenges: for example, how do we ensure the validity of assessments and how do we make sure that students continue to develop essential basic skills, such as critical thinking and academic writing? At the same time, we see another movement emerging: teachers and educational support staff are increasingly experimenting with GenAI tools to enrich their teaching and support their daily work.
At EUR, this development is clearly visible in initiatives such as the recently launched AI Teaching Fellowship (CLI), the Generative AI for Research Programme (ERS), and numerous events, including the GenAI Monthly Meetups (CLI). On an individual level as well, an increasing number of EUR teachers are using GenAI, on a small or large scale, within their educational practice.
Within this context, we highlight three concrete AI applications: GenAI as a feedback and assessment tool, an AI-generated podcast, and AI-driven prototyping. These examples are by no means representative of all the possibilities GenAI offers in higher education. Our main aim is therefore to inspire teachers and educational support staff and encourage reflection.
Application 1: GenAI as a feedback and assessment Tool
Since 2023, dr. Nick Koning (ESE), teacher of the course Introduction to Programming, has been using GenAI as a feedback and assessment tool. Initially, Nick experimented with the idea of having students work with GenAI in his course, but this focus quickly shifted to using GenAI for assessment after early experiments yielded promising results.
The development of such an application requires a rigorous process, with a lot of experimentation and continuous refinement of the prompt. "It involved a lot of puzzling and testing to get the prompt to produce a meaningful outcome and ensure the assessment level is accurate. Of course, the intention is not for AI to assess students as if they were professional programmers," Nick explains. The experiments also revealed, for instance, that it is important for AI to provide feedback first before assigning points. Otherwise, AI uses the feedback to justify the points awarded.
The examination and assessment process has changed significantly in the Introduction to Programming course since the introduction of GenAI as a feedback and assessment tool. Students submit their exams or assignments via Canvas and receive a (provisional) grade and detailed AI-generated feedback within minutes. Afterwards, Nick or the TAs assess the assignment themselves, with the AI-generated feedback mainly serving as a double-check to ensure important information is not overlooked. "Overall, the quality [of AI-generated feedback and assessment] is incredibly good. There are occasionally small errors, often because it assesses too strictly, but they are not real mistakes," says Nick. He also noticed that AI assesses much more objectively, partly because systematic differences between TAs or lecturers, and other human errors, are eliminated. "The quality of assessment certainly does not deteriorate."
Impression of GenAI as feedback and assessment tool - Prompts and AI Feedback
Nick points out that the efficiency and time savings offered by GenAI can allow teachers to refocus on the core of education. These advantages also give teachers more freedom in choosing assessment methods, making it possible to use (alternative) forms of assessment that may provide a more accurate picture of students’ progress and knowledge. The benefits for students are equally clear: “Experience shows that students do not attend exam reviews. By that time, the exam was already three weeks ago, and students often no longer remember exactly what it was about,” Nick explains. Using GenAI as a feedback tool ensures that every student receives immediate, detailed, qualitative, and personalized feedback. Even with practice exams, students have the opportunity to receive AI-generated feedback, gaining early insight into their progress. According to Nick, this application can therefore make an important contribution to enhancing the learning process.
Application 2: AI-generated podcast
Nine months ago, Prof. Dr. Klaus Heine (ESL), with the support of student assistant Jennifer Groot (ESL), launched the AI-generated podcast Digital Governance. In this podcast, scientific research articles are discussed that focus on the legal and institutional frameworks shaping digitalization. The project has a clear objective: to make complex scientific insights accessible to students and the broader public.
AI-generated podcasts offer an accessible way to make academic research more approachable for society. Research articles are often difficult to read due to both technical barriers, such as limited access, and the use of complex language and academic jargon. Klaus illustrates the latter with an example: “The research I do is highly fundamental. The articles are often very abstract and hardly suitable for a wider audience. Even students and colleagues outside my field struggle with them.”
The podcast medium helps increase this accessibility, while the analytical power of AI ensures that scientific insights are presented in a comprehensible and digestible way. AI generates each episode as a structured conversation with a clear narrative thread. Jennifer explains: “It goes step by step, making the episode easy to understand and follow. The two voices also create a smooth, spontaneous conversation that remains clear.” Unlike traditional podcasts, AI avoids digressions and focuses solely on the main points. This also provides benefits for students: the podcasts offer an initial overview of an article and a first transfer of its core message. They are not a replacement for scientific articles, but a valuable complement to traditional course materials.
Application 3: AI-driven prototyping
For several years, Dr. Maurice de Rochemond (RSM) has been enthusiastically experimenting with GenAI in education, aiming to contribute to more innovative and impactful learning. As a lecturer in the Strategic Management & Entrepreneurship department, he regularly explores how GenAI can help visualize ideas quickly, for example through an AI-generated website or a simple prototype. Maurice explains: “In just a few minutes, you can create an interactive sketch or an early version of an idea without technical knowledge; purely through effective prompting.”
In his teaching, he frequently encourages students to explore the possibilities AI offers in prototyping and to reflect critically on it. This approach is generally received positively. As one student summarized: “The encouragement to explore AI, for example to create an early prototype, was really helpful. It made me continue experimenting with this after the course as well.”
At the same time, he emphasizes the importance of critical thinking: “Keep thinking critically: who is your target audience, what do you want to achieve? AI can be a helpful tool, but it starts with your own brain.” Therefore, Maurice advises students and teachers to first write down or sketch their concept on paper. “This way, you retain your own creativity, after which AI can help bring that initial idea to life.”
Impressions from the GenAI Monthly Meetup (23 October)
Responsible Experimentation
The examples in this article represent only the tip of the iceberg when it comes to the potential of AI to enrich education and support lecturers. Continuous exploration and experimentation therefore remain essential, emphasizes Shen Liu from the AI cluster at CLI: “GenAI offers countless opportunities, from small adjustments to major changes in teaching and working methods. In particular, GenAI can save time and simplify tasks, giving lecturers more space to focus on improving the quality of education.”
At the same time, it is crucial to always consider the ethical, social, and economic implications to ensure that AI is used responsibly and safely. “Although CLI values and encourages educational innovation, we also believe it must be done responsibly. Education professionals and students should critically consider for each application whether GenAI is the right and safest solution. Experiments should always be conducted in consultation with the relevant faculty. Involve the right colleagues early on for a successful experiment,” says Shen.
More information and guidelines on the use of GenAI can be found on this page.
- More information
Do you want to learn more about the possibilities of AI in your teaching? Visit the TeachEUR AI theme page or the AI@EUR page, participate in a MicroLab on AI, or join one of the monthly Gen-AI Meetups.
Or perhaps this article has inspired you to start an (AI) project with the support of the CLI? In that case, visit this page and get in touch with us.
Disclaimers:
- GenAI tools often store user data. Therefore, do not enter persona and/or confidential information about yourself, students, or EUR, and always consult the general Guidelines for Generative AI as well as your faculty’s AI policies/guidelines.
- Since the AI tools used in some AI applications are not aligned with the AI systems recommended by EUR, no specific GenAI tool names are mentioned in this article.
- The use of GenAI (tools) is entirely voluntary and is the sole responsibility of the user. This article is solely intended for informational purposes and does not imply that experimenting with GenAI or using specific GenAI tools is mandatory.
- Under the AI Act, the use of GenAI for assessments is classified as “high risk.” If you are considering using GenAI for assessment, always consult an EUR AI expert and ensure full compliance with the AI Act guidelines.
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