Students Interviewing Students Worldwide: Building a Global Observatory of Student Life in the Age of AI

Gustave Eiffel/Paris 13

Bilel BENBOUZID, Université Gustave Eiffel Thomas LEFEVRE, Université Paris 13 Victor POTIER, Université Gustave Eiffel

Research (anything related to the use of AI in a research context)

What if sociology classrooms worldwide became a global observatory of student life in the age of AI? In each class, one student trained in qualitative methods interviews another student using a shared ethnomethodological semi-structured interview guide. Each transcribed and anonymized interview is uploaded to a common platform, together with information about its institutional context, creating a crowdsourced research infrastructure for studying how generative AI is reshaping the student role.

Universities still lack robust empirical knowledge about what students are actually doing with these tools in their daily academic work. Public debates often remain abstract or overly focused on regulation and misconduct. Our use case matters because it shifts the focus from speculation to inquiry. It proposes to document how AI reshapes the "student role" (métier d'étudiant): how students redefine what it means to do academic work themselves. By building a shared international corpus of student interviews, this project would make visible the real social transformations currently underway.

Through this Challenge, we want to transform a classroom inquiry already tested in France into an international student-led research infrastructure on AI in higher education. We have already completed a first wave of peer interviews in sociology and now want to expand the project across institutions and countries, while also involving new disciplines, starting with a medical school in Paris. Our objective is to build a network of partner classrooms, refine a shared interview guide, organize peer mentoring, and create a common multilingual platform for anonymized transcripts. We also want to explore how AI tools could support translation, navigation, and comparison across interviews without replacing the interpretive work of inquiry. For us, this Challenge is both a learning opportunity and a launchpad for building an international observatory grounded in student experience.

Our initial contribution is the proposal of a distributed, research-based observatory of student life in the age of AI. Instead of starting from abstract principles or purely technical solutions, we propose to create the conditions for a shared international inquiry into how generative AI is transforming higher education from the perspective of students themselves. This contribution has four components. First, a common methodological kit: a shared ethnomethodological interview guide, basic training resources, and clear ethical procedures for consent, anonymization, and contextual documentation. Second, a multilingual platform where anonymized interviews can be uploaded together with metadata about institutional context, while preserving original languages and enabling translation. Third, a pedagogical model in which participation is embedded in teaching, so that students do not simply report on AI use but learn to investigate their own academic world using social-scientific methods. Fourth, an evidence-to-policy interface: the goal is to produce grounded knowledge that can help universities and public actors think more carefully about AI in higher education. We believe this proposal is realistic because it can begin with a small number of partner classrooms and scale progressively. It is responsible because it prioritizes inquiry, reflexivity, and student agency rather than surveillance or solutionism. It is actionable because it relies on existing teaching settings and transforms them into a collaborative research infrastructure.