Dear Reader,
In 2024, the Media & Learning newsletter featured 31 articles exploring the use of AI in higher education. From these, we have spotlighted the 5 most-read articles that resonated most with our community. These five articles delve into aspects of AI in education, each offering insights that provoke reflection and dialogue. Together, they highlight the opportunities and challenges AI brings to learning and teaching.
The first article warns of the danger of over-reliance on AI, emphasising the need for balance to preserve creativity and originality. The second article underlines the importance of professionalisation. The third article extends this theme, not only emphasising professionalisation but also addressing the extensiveness of AI’s impact and raising a fundamental curriculum question: what are we preparing students for? The fourth article shifts focus to the need for long-term thinking in how AI shapes self-regulated learning. This bridges seamlessly to the fifth article, which sets a research agenda, advocating for a structured approach to tackling AI’s challenges and opportunities in education.
These articles are dynamic contributions to a debate that is far from complete. Let’s hope they inspire thought-provoking questions and deeper discussions. For further exploration, consider joining the upcoming Staff Exchange Week organised by M&L members. Enjoy the read!
-Andy Thys, KU Leuven, SIG AI in Higher Education chair
10 ways my students used AI while writing a 6000-word research report
by Zac Woolfitt, Inholland University, The Netherlands
In a recent reflection, Zac Woolfitt, a lecturer at Inholland University in the Netherlands, explores how students in his tourism branding course used AI tools while working on a 6000-word research report. Over the course of the semester, students employed AI for tasks like grammar enhancement, paraphrasing, translation, and even generating ideas for slogans and logos. While AI helped improve efficiency, Woolfitt notes that excessive reliance on these tools often led to reports that lacked originality and depth. He found that students who used AI selectively produced stronger work, while those who leaned too heavily on it created generic, less engaging reports. One notable example was the use of AI to generate logos, which often resulted in unoriginal designs that required substantial reworking. Looking ahead, Woolfitt considers the challenges AI poses to academic integrity and the future of assessments. As AI tools continue to improve, he believes educators must adapt by developing clear guidelines and promoting real-world, hands-on tasks to ensure meaningful learning outcomes.
AI in education for self-regulated learning
by S. Kazem Banihashem, Open University, the Netherlands
The integration of AI into education is reshaping how students learn, but there are growing concerns that AI tools like ChatGPT and Gemini might lead to dependency, impeding students’ self-regulation skills. Research at the intersection of AI and Self-Regulated Learning (SRL) is exploring how AI can be used to support students’ independence and learning regulation, while also examining challenges in this area. A systematic review of AI-SRL research highlights a few key issues: most studies focus on higher education, while the role of AI in K-12 education remains underexplored; many studies lack solid theoretical foundations; and while AI is widely used for adaptive learning, motivational factors are often overlooked. To fully leverage AI for SRL, future research should focus on long-term impacts, motivational aspects of learning, and the ethical design of AI tools. By addressing these gaps, AI could become a powerful tool in fostering independent, self-regulated learners.
E-learning modules for lecturers and students on impact of GenAI in higher education
by Emma Wiersma, University of Amsterdam, The Netherlands
In response to the growing use of generative AI (GenAI) by students, the University of Amsterdam (UvA) launched an e-learning module in September 2023 to educate students on the responsible use of tools like ChatGPT, addressing concerns over privacy and security as UvA policy prohibits their use in teaching and assessments. The module, which takes 45-60 minutes to complete, covers how GenAI works, its ethical implications, and offers tips for responsible use. In February 2024, UvA introduced a second module for lecturers and teaching assistants, providing guidance on assessment strategies, course adaptations, and prompt engineering. These efforts are part of a broader pilot project at the UvA Faculty of Science, where ChatGPT is being integrated into teaching through a secure Microsoft Azure cloud environment. The project aims to explore how GenAI can enhance student learning while addressing privacy concerns, informing future educational innovations and the responsible integration of AI into higher education.
AI for continuing education, staff and teacher training at Oulu University of Applied Sciences
by Janne Länsitie & Lotta Pakanen, Oulu University of Applied Sciences, Finland
Oulu University of Applied Sciences (Oamk) is actively training its staff and teachers to adapt to the growing role of AI in higher education. The university has developed policies that encourage AI use while emphasising transparency and ethical considerations. Training programmes cover a range of topics, including AI in media production and personalised learning, and are offered in flexible formats like workshops, lectures, and peer learning. Oamk also uses digital badges to motivate staff to explore AI tools. The goal is to equip teachers with the skills to use AI in their specific fields and ensure that all students have equal opportunities to learn and apply AI for their future careers. By investing in AI training, Oamk aims to improve teaching practices and better prepare students for the demands of the modern workforce.
AI in education: challenges & opportunities for research
by Ann Fastré & Rani Van Schoors, KU Leuven, Belgium
The integration of Artificial Intelligence (AI) into education presents a unique blend of challenges and opportunities for researchers, educators, and policymakers. In their recent positioning paper, Ann Fastré and Rani Van Schoors, researchers at itec (an imec research group at KU Leuven), explore the evolving connection between AI technologies and educational practices. Addressing both the potential and the pitfalls of AI in teaching and training, the authors offer a comprehensive overview of the current landscape, grounded in a detailed literature review.
The paper not only examines the practical applications of AI in education but also considers its ethical, practical, and pedagogical implications. With a focus on empowering educators and learners, it emphasises the importance of explainability, privacy, and ethical considerations in AI systems. By bridging the gap between theoretical research and practical use cases, Fastré and Van Schoors invite various groups involved in education to engage with the possibilities of AI to enhance both formal and informal education.
This work calls for a thoughtful and collaborative approach to integrating AI in education—one that respects the humanity of the teaching-learning process while leveraging technological advancements.
