Integration of Artificial Intelligence in Health Numeracy: A Case Study on Nutritional Label Analysis in Secondary Mathematics Education

This study investigates how an instructional sequence facilitated by artificial intelligence (AI) can enhance the development of proportional reasoning in health numeracy. Using a design-based research approach, an activity was implemented with secondary school students, focusing on analyzing nutrition labels and structured around five tasks that involved ratios, proportions, scaling, product comparison, and solving inverse problems. The intervention incorporated an AI-based tutoring system that operated through differentiated functions: technical assistance, adaptive feedback, criterion validation, and discursive support. The theoretical framework drew on situated abstraction, understood as the contextual reorganization of mathematical meanings within practical settings. The results show that AI can play a formative role when its use is aligned with tasks that require interpretation, argumentation, and decision-making. Students who engaged with AI strategically could construct more stable and well-justified proportional relationships, whereas superficial use tended to reproduce procedures without understanding. The experience suggests that technology, rather than serving merely to solve tasks, can expand the conditions under which mathematical thinking emerges in socially relevant contexts. The article concludes with a reflection on the implications of integrating AI into mathematics education from a situated, critical, and judgment-oriented perspective.