GENERATIVE ARTIFICIAL INTELLIGENCE IN MATHEMATICS EDUCATION: POSSIBILITIES, CHALLENGES AND PEDAGOGICAL IMPLICATIONS

Abstract

The expansion of Generative Artificial Intelligence (GAI) has broadened the possibilities for using digital technologies in Mathematics education, while also creating challenges related to learning, assessment, teacher training, and the ethical use of these tools. This study aims to analyze the main possibilities and challenges associated with the use of GAI in Mathematics education, based on an integrative review of the literature published between 2022 and 2026. The research is characterized as bibliographic, with a qualitative approach, and uses studies identified through a search environment integrated with scientific sources from Elsevier. NotebookLM was employed as an auxiliary tool for organizing and synthesizing the material, while the interpretation and categorization of the studies remained the responsibility of the researchers. The results indicate potential benefits related to the production of explanations, personalization of interactions, development and adaptation of activities, comparison of strategies, and support for pedagogical planning. On the other hand, the findings highlight risks such as incorrect responses, superficial learning, reduced cognitive effort, technological dependence, assessment difficulties, academic integrity issues, privacy concerns, and the need for teacher training. It is concluded that the contribution of GAI depends less on the technology itself than on its intended purpose, pedagogical mediation, and the critical engagement of students.