This paper aims to explore AIED tools (Artificial Intelligence Technologies in Education) use and perception in academia context. Forty-three semi-structured interviews have been conducted with professors at the University of Florence from different scientific fields. Three dimensions of analysis have been identified: i) the digitalization paths during and after the Covid-19 pandemic; ii) the opportunities, limits and risks of introducing AI tools in teaching and learning practices; iii) the institutional support and future solutions. Results show that AI tools application to teaching practices are still nascent at the University of Florence. A small number of professors interviewed use AI tools in their didactics. A slight difference exists among the diverse scientific fields. Hence, professors who are more favorable in introducing these tools in didactics, especially with experienced students, are those belonging to STEM areas (Science, Technology, Engineering and Mathematics). The paper highlights that crucial institutional issues need to be considered before a more substantial use of AI tools by both professors and students.
The potential of artificial intelligence-related technologies in university teaching: a case study from the University of Florence / Sara De Martino, Agnese Desideri, Alessandro Latterini. - In: STUDI DI SOCIOLOGIA. - ISSN 0039-291X. - ELETTRONICO. - STUDI DI SOCIOLOGIA - 2025 - 1. 60 anni di Studi di Sociologia. Persona, Società, Futuro. La nuova frontiera della conoscenza: le sfide dell’intelligenza artificiale:(2025), pp. 0-0. [10.26350/000309_000213]
The potential of artificial intelligence-related technologies in university teaching: a case study from the University of Florence
Sara De Martino
;Agnese Desideri
;Alessandro Latterini
2025
Abstract
This paper aims to explore AIED tools (Artificial Intelligence Technologies in Education) use and perception in academia context. Forty-three semi-structured interviews have been conducted with professors at the University of Florence from different scientific fields. Three dimensions of analysis have been identified: i) the digitalization paths during and after the Covid-19 pandemic; ii) the opportunities, limits and risks of introducing AI tools in teaching and learning practices; iii) the institutional support and future solutions. Results show that AI tools application to teaching practices are still nascent at the University of Florence. A small number of professors interviewed use AI tools in their didactics. A slight difference exists among the diverse scientific fields. Hence, professors who are more favorable in introducing these tools in didactics, especially with experienced students, are those belonging to STEM areas (Science, Technology, Engineering and Mathematics). The paper highlights that crucial institutional issues need to be considered before a more substantial use of AI tools by both professors and students.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



