Generative artificial intelligence as a catalyst for equity in mathematics education

Abstract

The right to quality mathematics education for all is not limited to access to schooling; it also requires pedagogical conditions that promote understanding, participation, and situated learning. The objective of this article is to analyze how generative artificial intelligence may contribute to equity and pedagogical transformation in mathematics education. To this end, a narrative literature review was conducted and organized into categories related to theoretical foundations, technological evolution, pedagogical applications, teacher roles, computational thinking, and equity. The analysis shows that these tools can support task personalization, resource generation, the use of multiple representations, and feedback during problem solving. However, their formative value depends on teacher mediation, critical review of generated responses, and institutional conditions of access. As a limitation, the review does not include a meta-analysis or statistical comparison of effects. It is concluded that generative artificial intelligence can expand opportunities for mathematics learning when integrated into didactic designs oriented toward reasoning and validation.