Exploring AI-based pronunciation tools in Italian higher education: student attitudes and pedagogical implications from a pilot case study

Among Artificial Intelligence (AI)’s numerous applications, educational ones suggest articularly interesting debates. This pilot case study investigates the potential integration of AI-based tools into English as a Foreign Language (EFL) pronunciation teaching, an area that has historically received less attention than other linguistic skills (Celce-Murcia et al. 2010). While recent approaches emphasise intelligibility over native-like performance, and Automatic Speech Recognition has shown positive results in improving pronunciation in English as a Foreign Language environments (Munro 2016), research on AI-supported pronunciation learning in Italian higher education remains limited. This paper investigates students’ use, attitudes, and perceptions of AI-driven pronunciation tools at the University of Milan. Employing a quantitative survey involving a pilot sample of undergraduate and graduate students with varying exposure to phonetics and phonology, it provides insight into tool familiarity, preferences, and perceived pedagogical value. Findings reveal limited adoption and conceptual ambiguity surrounding AI-based pronunciation tools, coupled with cautious optimism towards their potential integration through a flipped learning model. The results underscore the importance of AI literacy and pedagogical guidance in supporting informed use, offering a foundation for future large-scale research and for the development of institutional frameworks that embed AI meaningfully within language education.