When one teaches, two learn: The bidirectional learning process supervisor-PhD student

The Institute of Economics will hold a seminar meeting as part of its Seminar Series on Tuesday, April 30, 2024: Pierre Boutros will present the paper “When one teaches, two learn: The bidirectional learning process supervisor-PhD student".

Abstract:

In contexts involving teachers and students, knowledge transfer is commonly assumed from the former to the latter. However, what if teachers learn from students? This paper investigates the bidirectional knowledge transfer between PhD students and their supervisors. We consider the entire population of 66,588 PhDs who graduated in the STEM fields in France between 2010 and 2018. Focusing on the domain of Artificial Intelligence (AI) as our empirical framework, we identify AI students and AI supervisors as those using AI-related keywords in their theses and publications, respectively. We find evidence that student-supervisor pairs characterized by an AI supervisor are 11 percentage points more likely to show a student writing a thesis in AI than in pairs with no AI supervisors, denoting an AI knowledge transfer from supervisors to students. Restricting to student-supervisor pairs in which the supervisor has no AI knowledge before mentoring the student, we find evidence that pairs characterized by an AI student are 17 percentage points more likely to show a supervisor publishing an AI article after the student’s training, denoting an AI knowledge transfer from students to supervisors. Those results confirm the bi-directionality of the learning process.

The Seminar will be held in Aula 5.

For online partecipation use this link.