Active Learning of Biostatistics in Medical Education: An Educational Intervention Using Algorithms, Article Analysis and SPSS Simulation.

Introduction Although biostatistics is a core component of medical education, traditional lecture-based teaching methods can limit students' understanding of, and ability to apply, statistical concepts in practice. Active, multimodal pedagogical strategies can improve learning outcomes and student engagement. Objective The objective of this study is to evaluate the effect of an active, multimodal pedagogical intervention (algorithms, SPSS simulation and article analysis) on the following among medical students: academic performance, the perceived mastery of course content, importance attributed to parametric and nonparametric tests and satisfaction with the teaching method. Methods A parallel-group intervention study was conducted among third-semester medical students enrolled in a biostatistics course between October 2025 and March 2026. The participants were randomly assigned using simple randomisation to either the intervention group (n = 22) or the control group (n = 39). While the control group attended traditional lectures, the intervention group participated in an active, multimodal programme incorporating algorithm-based instruction, the critical analysis of scientific articles and practical SPSS software simulations. Academic performance was assessed using a written biostatistics examination, while perceptions of importance, mastery and satisfaction were measured using Likert scales. Group comparisons were performed using Student's t-test, a Mann-Whitney U test and a chi-square test, with a significance level of p < 0.05. Results The intervention group achieved significantly higher examination scores than the control group (13.00 ± 3.84 versus 9.44 ± 4.10, p = 0.001). A greater proportion of students in the intervention group obtained a favourable result (≥14 points). The odds ratio (OR) (OR = 0.107; 95% confidence interval {CI}: 0.013-0.891) reflects the reduced odds of failure in the intervention group, indicating a significant association between group membership and academic success. Additionally, the intervention group reported attributing significantly greater importance to statistical tests (p = 0.036), perceiving themselves as having a significantly greater mastery of the course content (p = 0.017) and being significantly more satisfied with the pedagogical method (p = 0.015). Conclusion The active, multimodal pedagogical intervention had a significant positive effect on academic performance and students' perceptions of learning in biostatistics. These findings support the incorporation of algorithm-based instruction, the critical appraisal of scientific literature and statistical software simulation as effective strategies to enhance biostatistics education in medical training.