We want to understand what AI actually does to higher education.
Students and instructors use GoSchool's systems on real courses. That lets us study not only what people say about AI, but how they actually use it.
We don't ask whether AI is being used. We study how.
AI is already part of the everyday toolkit for students and instructors. The questions that matter are less about whether it shows up, and more about how it changes learning, teaching and the way an institution runs.
Student AI use
What do students actually use AI for?
When do they ask for an explanation, when do they practise, when do they hand the task over — and how does that shift from course to course, or over time?
The learning process
How does AI change learning strategies, help-seeking, and independent problem-solving?
The instructor's role
How does an instructor's role change when students have continuous access to AI support?
What control, and what new pedagogical practice, does that call for?
Human–AI interaction
How does the working relationship between a person and an AI develop over a longer period?
When does the AI become an explainer, a practice partner, a search tool — or simply a way to hand the work off?
Institutional AI
How can AI systems be introduced at a university so that they genuinely fit the teaching, organisational and technical environment already in place?
Not a lab. Not a one-off survey.
What matters most about this setting is that we can study real use, on real courses, over an extended period.
- analysing natural student interactions
- following use across weeks or months
- comparing across courses
- studying different instructor configurations
- combining qualitative and quantitative methods
- connecting the student and instructor perspectives
Research data is handled under appropriate ethical, privacy and anonymisation frameworks.
Current research directions
Student AI use on real courses
From GoSchool's interactions we study what kinds of task students bring to a course-bound AI.
- whether they are after understanding or a finished answer
- how use changes over the course
- what differs between courses
- what role the AI takes in the learning process
AI and instructor adaptation
We study how instructors reshape their courses, their assignments and their own work as AI spreads.
AI in higher-education infrastructure
Beyond teaching use cases, we study how AI agents, skills and integrations fit a university's existing technical and organisational environment.
Publications and conferences
- Rethinking University Learning: Course-Based Human–AI Interaction in a Controlled Educational Environment
M. Szabó, Á. Tamási, R. Németh, A. TátraiAISEER @ ECAI 2025
The paper studies course-bound AI use on real university courses, and how different patterns of student interaction emerge in a controlled educational environment.
What we learn, we build back into the system.
Research is not after-the-fact validation for us. What comes out of real use directly shapes how we design the next AI solutions.
- what help a student actually needs
- where more instructor control is required
- which prompts and interfaces work
- which AI features genuinely get used
- what works technically but creates no value in practice
Let's work together.
We look for collaborations with universities, research groups and individual instructors on questions where real higher-education AI use can be studied.
Possible collaboration: Joint research project · Course pilot · Institutional AI pilot · Data collection · Joint publication · Research infrastructure