Development of teachers’ professional judgment in an experience with generative artificial intelligence

Abstract

This study explores how Generative Artificial Intelligence (GAI), through a customized model designed to support lesson planning, contributes to the development of professional judgment among prospective preschool teachers. The research employed a qualitative, exploratory, and longitudinal approach. Four sixth-semester students from a teacher training college in northwestern Mexico were selected as cases. Semi-structured interviews were conducted at two different points in time. Content analysis was carried out deductively, based on seven categories associated with professional judgment: efficiency, contextualization, creativity, logical sequencing, innovation, recognition of one’s own learning, and agency. The findings indicate that GAI does not replace pedagogical thinking; rather, it activates and challenges it. Professional judgment was strengthened in two ways: by critically evaluating the relevance of the model’s responses and by incorporating new elements to enrich the lesson plans. In practice, GAI did not replace the pedagogical authority of the classroom mentor teacher, but was integrated as a complementary support that reinforced student-teachers’ confidence when implementing their plans. The development of customized models is shown to be a practical solution for fostering the critical use of GAI in education, and such tools should be oriented primarily toward personalized learning. In conclusion, the integration of customized models represents a promising pathway for strengthening professional judgment in pre-service teacher education.