Artificial Intelligence Literacy and Professional Practice of Post-Secondary Teachers in Quebec: A Mixed-Methods Study of Gaps and Training Priorities

In recent years, artificial intelligence (AI) has become increasingly pervasive, and the field of education is no exception. However, ensuring that AI brings a positive and productive impact to teaching practices requires that AI training for instructors addresses their actual teaching needs. In the present study, the AI training needs post-secondary teachers in Quebec have been identified by simultaneously monitoring their AI usage, AI literacy, and training expectations. Data were collected between October 2024 and October 2025 for 345 teachers in 27 first-level postsecondary institutions (CEGEPS) using an online questionnaire. In-depth interviews were performed for 27 teachers in 10 CEGEPS. An integrated quantitative and qualitative approach was used to analyze the data. The largest majority of responses (94.7%) reveals the utilization of AI in a professional context, with time-saving being the main reason for use among participants. AI literacy exhibits statistically significant differences across gender and discipline groups, suggesting the need for multilevel training courses. While technical understanding is the lowest performing dimension of AI literacy (with an average score of 2.7 out of five points), participating teachers prioritize learning about practical applications, specifically in their own discipline field. Instead of abandoning the teaching of first principles, which are essential for unlocking advanced functionalities that users cannot yet foresee, future research should examine whether multilevel training courses, which embed these concepts within the practical tools that users desire, can foster meaningful professional development.