Artificial intelligence in initial teacher training for pre-service primary school teachers in mathematics: a systematic review

Source abstract

Artificial Intelligence (AI) has been progressively integrated into Initial Teacher Training, with UNESCO recognizing, in 2024, the need to prepare teachers for its use in educational contexts. In this regard, it is important to understand how Teacher Training in AI has been developed, particularly concerning the approaches adopted, their characteristics, and the outcomes achieved. This article presents a systematic literature review aimed at investigating how AI has been integrated into Initial Teacher Training Programs for Pre-Service Primary School Teachers, with a particular focus on the types, structure, and monitoring of the training provided. Following the PRISMA 2020 Statement and using the Scopus, Web of Science, and ERIC databases, eleven articles that met the defined eligibility criteria were identified, all published between 2024 and 2026. Across these studies, the interventions were predominantly short-term and embedded within existing courses. The training generally comprised a preparatory phase followed by a practical phase, progressing from guided to autonomous exploration of AI tools and culminating in critical reflection on the developed product. Monitoring relied primarily on records of interactions with the AI tools, while the attitudes and perceptions of Pre-Service Primary School Teachers were, in most cases, assessed at a single point in time. The findings suggest the need for longer-term and continuous training that extends beyond the mere use of AI tools. Such training should prepare Pre-Service Primary School Teachers to evaluate, adapt, and make informed decisions about AI-generated content based on their didactic and mathematical knowledge and critical thinking. Furthermore, it should be supported by monitoring instruments implemented throughout the entire training process and articulated with authentic teaching situations.