INQUIRY-BASED LEARNING AND ARTIFICIAL INTELLIGENCE IN THE TEACHING OF PARASITIC DISEASES: A PROPOSED DIDACTIC SEQUENCE ON CHAGAS DISEASE

Abstract

This article described and analyzed a didactic sequence with an investigative approach for teaching human parasitic diseases, focusing on Chagas disease, applied to second-year high school classes at a public school in Ceará as part of the Biology course assessment. The sequence was structured in stages aligned with the Pedaste investigation cycle, involving a fictitious case study, laboratory test simulations, and a synthesis activity in the form of a brochure. Generative AI was used to accelerate the production and diversification of teaching materials, with teacher curation to ensure didactic-scientific coherence. Data collection followed a teacher/researcher observation protocol, as well as written products from the groups, such as hypotheses, diagnoses, and synthesis activities in brochure format. The analysis of the material and data collected was carried out through thematic content analysis guided by dimensions of inquiry-based teaching, such as the use of evidence, the participants' capacity for argumentation, and communication. The findings pointed to signs of pedagogical viability and increased participation, with explicit justifications in the collective discussion and appropriation of key concepts such as transmission, cycle, and prophylaxis, although recurring difficulties with technical vocabulary and disparities between teams were observed. It is concluded that the integration of inquiry-based teaching and AI can be promising, as long as it is accompanied by teacher mediation and critical validation of the material, with recommendations for lexical support strategies such as thematic glossaries and future investigations with more analytical and systematic discursive records.