Effectiveness of a Numerical Problem-Solving Module in Enhancing Renal Physiology Comprehension

Introduction Renal physiology is integral to medical education but poses challenges due to its abstract and quantitative nature. Traditional didactic teaching methods often do not foster a deep understanding of key concepts. With the advent of competency-based medical education in India, there is a need for innovative approaches to enhance conceptual understanding and analytical reasoning. This study aims to evaluate the effectiveness of a numerical problem-solving module in enhancing first-year medical students' understanding of renal physiology. Methods We conducted a quasi-experimental intervention study with pre- and post-test paired assessments among first-professional medical students in the Department of Physiology at the All India Institute of Medical Sciences, Bhubaneswar, India. The intervention consisted of a small-group discussion of a 20-question renal physiology numerical problem-solving module that followed traditional lectures. The numerical module covered key aspects of renal function, including volume of distribution, clearance, glomerular filtration rate and renal blood flow calculations, tubular processing, and acid-base balance. We administered pre- and post-tests consisting of 17 multiple-choice questions (MCQs) via Google Forms (Google LLC, Mountain View, CA, USA). We used MCQ scores to assess quantitative performance. Item analysis was performed for both pre- and post-test MCQs. We collected students' perceptions using a validated questionnaire. Among 113 students, only 92 students attempted both pre- and post-tests, while 100 students anonymously submitted the complete questionnaire. We used a paired t-test to compare related groups. Statistical significance was set at p ≤ 0.05. Results The post-test score (12.5 ± 2.3; 73.8 ± 13.5%) showed a significant improvement (p < 0.001) compared with the pre-test scores (11.3 ± 2.4; 66.6 ± 14.4%). Item analysis revealed that pre-test low achievers demonstrated significantly higher post-test scores (8.1 ± 1.7 versus 11.8 ± 2.6, p < 0.001), whereas high achievers showed no significant change. Students' feedback strongly supported the incorporation of numerical problem-solving modules into the curriculum, highlighting greater engagement, deeper understanding, and enhanced peer collaboration. Conclusion The numerical problem-solving module significantly enhanced students' understanding of renal physiology, particularly benefiting low achievers. This study underscores the potential for numerical problem-solving to become a standard component of medical education, fostering analytical skills and confidence.