Aarhus University
Large Language Models (LLMs) provide students with new opportunities for problem-solving, knowledge synthesis, programming assistance, and data visualization.
Aarhus University decided early on that students should be allowed to use Generative AI (GAI) in their studies and exams unless explicitly prohibited in the course description. This decision reflects the reality that AI is already widely used in workplaces, making it essential for students to understand both its potential and limitations.
To support this approach, the Center for Education and Learning (CED) has developed workshops and courses to help educators integrate AI effectively into teaching.
While AI presents challenges in assessment, Aarhus University believes that embracing the technology rather than banning it is the right approach.
TalTech
AI advancements have led TalTech to rethink how written assignments are structured and assessed. Teaching staff have access to support materials on adapting courses and assessments to AI tools.
The university encourages designing teaching methods and exams that allow students to use AI while ensuring they demonstrate their own knowledge and skills. The focus is shifting from simply evaluating final solutions to assessing students’ problem-solving processes and critical thinking abilities.
In 2024, TalTech established the AI Center of Excellence to provide academic staff with training on AI applications in education. AI has also enabled the development of course-specific chatbots that assist students in their learning by offering additional clarification and support.
Tampere University
The most significant impact of AI has been on thesis writing and academic reporting. Students are encouraged to use AI tools like ChatGPT, provided they disclose its usage in their work.
Tampere University has established clear guidelines to ensure AI is used responsibly and transparently. Faculty members actively guide students in using AI wisely, with a strong focus on AI literacy to enhance learning while upholding academic integrity.
Åbo Akademi University
Two faculty perspectives on AI integration:
- AI is being used in assignment and exam planning, as well as for reviewing student responses. Exam formats, particularly for BSc students, have shifted towards closed-book exams with shorter time limits.
- To prevent students from submitting AI-generated answers without modifications, exams now include pen-and-paper formats.
While AI has improved the language quality of student theses, the content often lacks depth and coherence, prompting discussions about the importance of original writing.
University of Turku
Students’ reports and theses are now longer, more grammatically correct, and better structured. However, these improvements do not necessarily reflect deeper thinking—if anything, the opposite.
There is no definitive answer on how AI should be used in education; universities are still navigating its role.
University of Oulu
The University of Oulu has established clear policies on AI usage in education, outlining permitted and prohibited uses. More details can be found in their guidelines: University of Oulu AI Guidelines.
Within technology degree programs, AI is actively shaping teaching methods. Best practices for educational AI use are being shared, and faculty training needs have been identified. Key topics include AI-based evaluation, self-assessment, and responsible AI integration.
AI is being incorporated into learning tasks, such as discussion-based exercises where students engage with ChatGPT in different roles or use AI to brainstorm thesis topics.
Overall, AI has accelerated the development of teaching methods and ethical guidelines, requiring significant effort but also creating new opportunities for education.
Lappeenranta University of Technology
LUT takes a positive approach to AI while ensuring clear guidelines and regulations are in place for a shared understanding of its use.
Teaching methods have been partially redesigned, and thesis requirements have evolved. Beyond concerns of plagiarism, there is a growing need to verify that students possess a deep understanding of their subjects.
Reykjavik University
Reykjavik University (RU) and other Icelandic universities prioritize the ethical and practical use of artificial intelligence (AI) in both research and teaching. This commitment is a core element of RU’s 2030 strategy, ensuring the responsible integration of AI into education.
To align with these objectives, RU has reviewed its teaching strategy and is updating study and assessment regulations. Guidelines on AI usage in assessments are available internally, specifying how students may use AI in their studies. Faculty members have access to resources on AI misuse and assessment redesign via the university’s teaching development platform.
RU offers a broad range of AI-focused courses, including an advanced undergraduate course on AI, which is also available at the MSc level. Master’s students can specialize in AI and language technology, preparing for careers in the growing field. A new MSc in Artificial Intelligence program will launch in fall 2025. AI integration extends beyond computer science—departments like Sport Science incorporate AI while emphasizing ethical considerations.
AI research at RU is led by the Center for Analysis and Design of Intelligent Agents (CADIA), which explores AI applications in virtual environments, search and planning, and human-machine interaction. The Language and Voice Lab (LVL), part of CADIA, specializes in speech and language processing, providing master’s students with opportunities for collaborative research and conference publications.
In summary, while AI and LLMs present challenges—particularly in helping students understand when and how to use these tools—RU emphasizes critical thinking, ethical AI use, and academic integrity as core principles in AI integration.
Riga Technical University
The traditional education model is evolving rapidly in the AI era. Riga Technical University (RTU) anticipates a shift from conventional lectures and exams toward more dynamic approaches that emphasize creativity, critical thinking, and skill development beyond rote memorization. RTU sees AI integration not as an optional enhancement but as a fundamental transformation of higher education.
Latvian universities are developing internal regulations for the use of Large Language Models (LLMs) like ChatGPT in education. These guidelines focus on responsible, ethical, and effective AI integration for both students and faculty. Key principles include:
- Responsible AI use: Students and staff must follow established AI usage policies, including proper citation of AI-generated content.
- Risk awareness: Universities emphasize potential risks such as data security concerns, embedded biases, content accuracy, and copyright issues.
RTU has actively addressed AI’s role in education through various initiatives, including discussions on AI’s impact and hackathons to explore AI-driven solutions. The university continues to refine its approach to ensure AI supports rather than compromises academic integrity.
Kaunas University of Technology
Kaunas University of Technology (KTU) has seen significant shifts in student learning habits, teaching methods, and research due to the integration of AI tools like ChatGPT and other LLMs. While AI has enhanced accessibility to information and streamlined academic tasks, concerns about over-reliance on AI persist.
To address these challenges, KTU is considering:
- Reintroducing oral examinations to ensure students can independently demonstrate their understanding.
- Emphasizing critical thinking in assessments, requiring students to explain their work beyond AI-generated responses.
Rather than banning AI, KTU seeks to integrate it meaningfully into the curriculum. In April 2024, the university approved the Policy on the Ethical Use of Generative Artificial Intelligence in the Study Process, which outlines ethical AI use, citation requirements for AI-generated content, and responsibilities for both students and faculty.
Additionally, KTU has established an expert working group to guide AI integration and ensure its responsible use across academic disciplines.
NTNU
The initial response to the rise of Large Language Models (LLMs) was “anxiety”—how could universities ensure that students were writing their theses independently? To address this, NTNU introduced a declaration form that students must submit alongside their theses, documenting whether and how they used LLMs in their work.
Over time, NTNU has recognized the practical benefits of LLMs in both teaching and problem-solving. For non-computer science students, AI tools have proven particularly useful in helping them apply coding to engineering challenges.
In computer science programs, students are encouraged to use LLMs to generate large-scale software systems. They are then required to analyze and evaluate these systems in terms of quality and robustness. This approach simulates real-world collaborative environments, where teams of computer scientists develop complex systems and conduct peer reviews.
By integrating LLMs into coursework in a structured way, NTNU ensures that students not only benefit from AI’s capabilities but also develop the critical skills needed to assess and refine AI-generated outputs.
University of Stavanger
The adoption of AI has led to significant changes in exam formats, student assignments, and assessment methods. Traditional home exams in the form of written reports are no longer as relevant, as AI tools make it easier for students to generate content.
One of the biggest challenges has been detecting and handling AI-assisted cheating, which has become increasingly difficult and has placed a greater workload on faculty. As a result, the university is exploring alternative assessment methods that ensure academic integrity while adapting to AI-driven changes in education.
Uppsala University
Uppsala University has been actively working on defining policies and procedures for AI use in education. This process is ongoing at multiple levels within the institution.
One clear trend observed during the annual course syllabus revisions at the Faculty of Science and Technology is a shift in examination formats. While the changes remain gradual, there is a move away from hand-in assignments towards more oral examinations and in-person hall exams to maintain assessment integrity.
For further details on Uppsala University’s approach to AI in teaching and learning, visit: AI in Teaching and Learning at Uppsala University.
Umeå University
AI language models have primarily influenced examination formats at both undergraduate and graduate levels. The university has observed a notable increase in in-person exams, with a growing preference for oral assessments as a means to verify students’ understanding.
At the same time, Umeå University is actively exploring how to better utilize AI tools in education. There is a recognized need for faculty to further develop their AI skills, and ongoing discussions focus on optimizing AI integration in teaching and learning. While both students and educators are already using AI, there is still uncertainty about whether these tools are being leveraged in the most effective way.
Mälardalen University
The introduction of Large Language Models (LLMs) has sparked a wider discussion on alternative examination formats among faculty. This has been beneficial, prompting a reevaluation of learning assessments, legal considerations, and allowed examination aids.
A significant shift has been the move away from written home exams in favor of oral examinations. Many teachers see this as a positive change, as it allows for more direct interaction with students and often requires less time to assess than reading lengthy written submissions. However, transitioning to oral exams has also required considerable effort in designing clear assessment frameworks, selecting appropriate questions, and structuring the process effectively.
LLMs are widely used among faculty for lesson preparation and by students for academic work. A key skill in AI-enhanced learning is the ability to ask effective questions, enabling students to fully leverage AI’s potential. AI tools help students quickly gather and synthesize information, allowing for more in-depth analysis. In computer science and related fields, LLMs assist with code generation, debugging, and algorithm improvement, accelerating project development and enhancing learning through instant feedback and alternative solutions.
However, concerns remain about unequal access to AI knowledge among students. Some students effectively utilize AI to improve their work, while others either use it incorrectly or fail to engage with it at all, potentially creating an unfair learning environment and widening the gap in academic performance.