Fostering AI Literacy in Teacher Education: A Case Study of Pre-Service and In-Service Teachers’ Perceptions

Abstract

This case study examines changes in participants’ educational perceptions and technology acceptance following a targeted, short-term training intervention based on the Technological Pedagogical Content Knowledge (TPACK) framework. Utilizing a quasi-experimental longitudinal pre-test/post-test design, the study examined the perceptions of 476 pre-service and in-service teachers at a major public university in Italy before and after a 10 h training course covering AI architecture, Large Language Models (LLMs), and practical pedagogical applications. Data were collected using a validated 4-point Likert-scale questionnaire, with relevant items subsequently mapped onto Technology Acceptance Model (TAM) constructs for the present analysis. Inferential analyses identified statistically significant positive shifts in perceptions of AI’s educational usefulness and practical application, although effect sizes varied across constructs. Increased variability in perceptions of automated tutoring suggested continuing divergence among participants rather than uniform acceptance. The findings suggest that structured technical and pedagogical AI literacy may support a shift from generalized concerns or uncertainty toward more informed and reflective engagement with AI, providing a useful foundation for the integration of AI literacy into teacher education frameworks.