Master thesis progress through peers and AI
The project develops a peer-support framework for Master’s thesis students, including group matching, meeting templates and AI support. It aims to reduce isolation, increase completion rates, prevent delays and ease supervisors’ workload, while supporting collaboration and student well-being.
Project context
Many Master’s students struggle with isolated degree project work, which leads to delays and incomplete degree projects. At the same time, there are several shortcomings in the Master’s degree project process. The current process lacks support from other students, clear milestones, and accountability. There is also a lack of good process support and tools for teachers and students (ranging from templates, checklists, and guidelines to system support). A growing number of degree projects also places pressure on faculty resources. Taken together, this situation directly affects both KTH’s academic reputation and resource allocation.
A peer support framework would be needed, including group matching, meeting templates, and AI tools, to improve completion rates and reduce supervisors’ workload.
Purpose (outcome)
The purpose of the project is to improve the Master’s degree project process by developing a peer support framework for Master’s students’ degree projects, including group matching, meeting templates, and AI support. the intended outcomes are to:
- reduce isolation among students;
- increase the completion rate of degree projects;
- counteract delays in Master’s degree projects;
- effectively relieve supervisors.
Project results (output)
The project will deliver the following concrete results:
- an analysis document reviewing the current degree project process;
- a student matching protocol (a framework for peer support with a protocol for group matching);
- structured meeting schedules and templates;
- checklists and questions for critical stages of the degree project;
- guidelines for AI-based tools for transcription and summaries;
- an evaluation framework that measures completion rates and supervisors’ workload;
- a final report on the pilot implementation, with programme-wide recommendations.
Time plan
Start date: 2026-04-01
End date: 2026-12-31
Project documentation
If you have a KTH ID, you can read the documents when logged in:
- Poster: The project’s first poster (in Swedish) will be available at the ”Storträffen” meetup autumn 2026
- Project directive (Swedish): Projektdirektiv_FrU26_2618-EECS_TP2AI.pdf