The Challenge of GenAI in Thesis Assignments: Tips for Educators
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The thesis assignment is a great way of testing and is a large part of our programs, but it is put under enormous pressure by the advent of Generative AI (GenAI). In this article, we offer focus and tips that you as a teacher can use immediately. The main themes are:
- The student’s learning process: How can you guide and support students during the thesis process so that they gain authentic and valuable learning experiences?
- Authentic testing with the final product: How do you ensure that the final product of the thesis demonstrates the learning objectives validly and reliably, despite the possibilities of GenAI?
- Weighting and grading: How can you adjust the grading of theses to ensure the integrity and originality of the work?
After reading this article, you’ll know how to make GenAI agreements explicit, focus on the process and ask for matching evidence, and rethink your rubric towards reflection, validation, and reasoning. Thus, the thesis remains a powerful learning journey, even in these times of technological advancement.
Introduction
In our education, we make extensive use of large writing assignments. The final thesis is the largest of these and one of the most valuable final assignments we give our students. It is not just a text that is handed in, but an aptitude test; it is a comprehensive process of research in which knowledge and academic skills come together and are applied into one integrated whole. During this process, a wide range of skills are called upon at the highest Bloom level. Students demonstrate critical thinking skills, gain research skills such as academic writing, and increase their problem-solving skills. In addition, they plan and organize their work as project managers of their own project.
This entire process – from formulating a research question to analysing data and writing conclusions – is essential for their academic development. These experiences and skills are difficult to obtain from stand-alone or shorter assignments and form the core of our academic education. In this way, the programme gives students the opportunity to show that they are ready for the professional field.
However, the advent of Generative AI (GenAI) presents us with new challenges. GenAI can generate substantial parts of a thesis using a series of prompts, which increases the risk of unethical use and threatens the authentic learning experience of students. Students can also leave sub-skills to GenAI, such as making data analyses, writing introductions, drawing conclusions, or structuring and improving texts. A study from MIT Media Lab (n.d.) highlights risks when GenAI is used intensively and untargeted (Gerlich, 2025).
The key question is: will the intended learning objectives remain demonstrable when students use GenAI during the thesis process? What exactly do they demonstrate? Can we validly and reliably test those learning objectives with the thesis, and how do we guarantee the authenticity and originality of the submitted work (UNESCO, 2025)?
Instead of eliminating the thesis, as some suggest, this offers an opportunity to take a critical look at the design, structure, supervision, and assessment. Can we revise the thesis process to better reflect current technological realities while preserving its value? By coming up with creative, practical solutions, we ensure that students are still learning the important skills that the thesis provides, while ensuring the integrity of our teaching.
Below are a number of themes with practical tips that you can consider. Check which tips are applicable and useful to your course and discuss these in your team. See what the possibilities are to make changes in the program (think about changing learning objectives or a rubric) or which smaller changes you can apply directly.
Process vs Product
By placing more emphasis on the process instead of just the final product, you maintain the value of the research and the writing assignment and create a meaningful experience for the student. The guidance process offers opportunities for in-depth learning experiences and in-between feedback. By emphasizing the process of reflection and progress, you ensure that students feel and develop authentic involvement and responsibility. You can also make visible which skills the students already have, or what else they may need to be taught. Find tips below.
Have students submit regular reflection reports describing how their research is progressing, what problems they encounter, and how they are solving them. Use such a reflection report in the supervision moments you have with students, to elaborate on this. Think of questions such as:
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- How do you connect the objectives of your thesis with your personal values and plans for the future?
- What impact do you want your research to have, both on yourself and on academic and wider society?
- What research skills have you developed and how will they help you in your further career?
- Which literature and knowledge inspired you most during your research and why?
- What did you discover about yourself in terms of strengths and growth opportunities during this process?
Think of logs, annotation lists of literature read, draft versions of their written work, datasets, or mind maps. Or work with documents in shared folders, with which you can demonstrate progress (make the strategic choice when to use this or not to use it in order not to increase the workload for students or teachers).
In this field, too, the student develops skills that are needed in the future field of work. Have the students make a schedule or timetable, schedule regular ‘check-ins’ with a focus on progress or let them collaborate in (online) collaboration tools. Of course, make sure that there is alignment between the learning objectives and these learning activities (Biggs & Tang, 2007). By dividing the whole process into smaller steps with a focus on good guidance and interim feedback, the student will panic less because of the large amount of work, but will maintain an overview and ownership.
Think about when and how often students receive feedback, and when they can integrate it into their work. Think of feedback from their supervisor, but also peer feedback. Let students justify what they have done with the feedback. Make sure your feedback is in line with the student’s learning process, so that it encourages learning. When you only give feedback at the end of the process, students can’t use this feedback in a revised version of their work.
Use this in conversations to discuss together whether this use is done responsibly. Ensure clarity, mutual trust, and transparency between you as a teacher and your students. Be clear about when or how GenAI may or may not be used by your students (lack of clarity can potentially lead to frustration or unintentional fraud).
End product: More than just text
A thesis does not have to be just a written document. By allowing different types of end products, such as presentations and multimedia projects, you offer students the opportunity to present their research in creative ways. This makes it more difficult to use (or abuse) GenAI and promotes deep understanding and authentic engagement. Check out the tips below for more inspiration. Always make sure the end product is aligned with your learning objectives.
Have them present their research question and findings to a panel of teachers. Have teachers question the students about their findings, respond flexibly to comments, and in this way let them test whether the student has mastered the learning objectives. But also think of presenting in symposium form, or giving a presentation in the company where they worked on their research. More information about oral assessments is found in this article.
Encourage the use of other types of media or forms in or as the final product, which should be used to check whether you can still test the same learning objectives. And thus the same content is covered. For example, consider the following options:
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- Include other media such as videos, podcasts, interactive websites, or infographics (indicate whether or not students are allowed to use GenAI for this).
- Students design a virtual exhibition in which they can share their work, and visitors navigate through it. For an extensive version of this, see the virtual exhibition ‘Rooswijk’. Students keep a blog throughout their research to share their progress and findings.
- Students develop their own teaching materials based on their research.
- Students design and develop simulations to explain relevant processes or systems.
- Have the students develop a mobile app with practical search functions that really work for users.
Think about the possibility of making the end-product ‘form-free’, where students choose for themselves how they can demonstrate competencies. This makes the assessment form meaningful to the student, for which the student will be more motivated, and you take into account the context in which the student learns (is this an internship, research, part of programming education, etc.). (Baartman, Bastiaens, Kirschner, & Van der Vleuten, 2007).
Revision of the numerical weighting
A revision of the weighting of the grade is essential to adapt the thesis process to GenAI’s timeliness. By emphasizing the process and creative assignments, you ensure that students learn and grow, rather than just getting a grade. How could this look like? Read the tips below.
Weigh progress reports, reflections, and peer feedback more heavily in the final grade, and make sure it still matches your learning goals. There may be a shift towards more affective learning goals. Please visit the Visible Learning Trajectory website to find more information about affective learning goals and how they might look in practice.
Introduce assignments that need to be submitted at different times during the project, e.g. the research design or their literature study.
Take a critical look at the assessment form or the rubric; the weighting of aspects in which the potential (mis)use of GenAI could be high should be assessed with a lower weighting or only as an admissibility requirement. Think, for example, of language and structure.
Determine how you assess students’ professional attitudes. Ensure that the thesis is not the first time students practice and are assessed on this; instead, build this up gradually throughout the program.
Set a GO / NO-GO checkpoint halfway through the thesis project and attach certain requirements to it. This is also a good time to link the reflections or progress reports mentioned above.
According to Boud and Cohen (2014), peer learning is about sharing knowledge, ideas, and experiences between students, which is of added value for both parties. This creates a human connection in a thesis project that can sometimes feel alone. Think about how you will include this in your assessment, but also think about the application of peer learning in the project, for example, when there are feedback moments, how and when do students work together (e.g. in ‘graduation groups’) and when peer learning is or is not supervised. For a convenient integration of peer learning, use the Peerceptiv tool.
Thesis assignment for large cohorts of students
Many of the above tips can also be applied when you have a large cohort of students, but some do not: you want to find a balance between ensuring the reliability and validity of the learning objectives and managing the workload for teachers (and students). Here are some extra tips for supervising large groups of students in the thesis process:
- Make sure you have a rubric that all your supervisors can work with. Consider calibration sessions or training, or info sessions for both internal and external supervisors.
- A larger cohort lends itself well to peer feedback or peer review. This can be done under the supervision of TAs or junior teachers, with the examiner as the person ultimately responsible.
- Add some kind of oral assessment, which doesn’t always have to be at the end of the process. Also, an oral assessment does not have to take long.
- You can randomly check some (interim) products for improper use of GenAI. Be transparent about this with your students.
- See if more emphasis can be placed on the process versus the product in thesis assignments carried out by external companies/supervisors. Think of making interim products or conversations more formal to find out what the student’s contribution is.
Finally
Supervising and assessing the thesis process are an essential part of academic learning. This is not only about awarding a final grade that is as fair and careful as possible, but especially about the broader role of the teacher and supervisor. Your added value lies not only in transferring knowledge, but also in personal guidance, giving targeted feedback, brainstorming about different choices, human interaction, and acting as a role model. This makes a difference in the education of students, far beyond the assessment alone.
So get started right away. Start by making explicit agreements about the use of GenAI in your thesis assignment. Revise your rubric to put more emphasis on reflection and validation, and schedule regular check-ins to monitor your students’ progress. By following these steps, you can ensure that the thesis remains a valuable and authentic learning journey for your students.
Would you like more information about unsupervised writing assignments? Then read more in this TLC article.
Or would you like more information about assessment in general? Then check the TLC Assessment page for more information.
Credentials
Baartman, L.K.J., Bastiaens, T.J., Kirschner, P.A., & Vleuten, C.P.M. van der (2007). Evaluating assessment quality in competence-based education: A qualitative comparison of two frameworks.
Biggs, J., & Tang, C. (2007). Teaching for Quality Learning at University. In J. Biggs, & C. Tang, Teaching for Quality Learning at University. Maidenhead: Open University Press.
Boud, D., & Cohen, R. (2014). Peer learning in higher education: Learning from and with each other. Routledge.
Gerlich, M. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006
Huygens Institute for the History of the Netherlands. (s.d.). #Rooswijk1740. Huygens Institute for the History of the Netherlands. https://www.rooswijk1740.nl
MIT Lab. (n.d.). Your Brain on ChatGPT, Retrieved from MIT Media Lab Website: https://www.media.mit.edu/projects/your-brain-on-chatgpt/overview/
UNESCO. (2025) AI and the future of education, UNESCO Publishing