Semantic networks as a tool for analyzing conceptual organization in active teaching methodologies in Microbiology

Active teaching methodologies have been widely used to promote meaningful learning and student autonomy. In this context, quantitative approaches can help assess how students organize and integrate knowledge throughout the learning process. Among these approaches, semantic co-occurrence networks stand out, as they are capable of identifying relationships between words and revealing the conceptual structure of textual productions. The objective of this study was to investigate whether semantic network analyses can characterize differences in students conceptual organization in Microbiology during their participation in the active teaching methodology "Adopt a Bacterium." To this end, a case study was conducted in the Bacteriology course at the Institute of Biomedical Sciences of the University of Sao Paulo, analyzing the textual productions of two groups of students in the years 2024 and 2025 during their study of the bacterial genus Bacillus. The texts were evaluated using semantic co-occurrence networks, taking into account metrics of structure and conceptual integration. The results showed that both groups covered the microbiological content outlined in the course, though with different thematic focuses and approaches to integrating the concepts. Although both years featured modular structures (a statistical mode of 9 subgraphs), in 2025 the network exhibited greater discursive robustness (2 to 4 times more words with high Betweenness centrality) than in 2024. It is concluded that semantic network analysis allows for the characterization of differences in conceptual organization among students using active learning methodologies, serving as a complementary tool for assessing meaningful learning in Microbiology.