Abstract Issue

Volume 13 Issue 4 (April) 2024

Original Articles

Exploring Educational Strategies: Evaluating Case-Based Learning versus Didactic Lectures in Antimicrobial Resistance for Phase 2 MBBS Students
Dr. Loveleena Agarwal, Dr. Aarushi Agarwal, Dr. Mridulesh Kumar Yadav, Dr. Rajesh Kumar Yadav

Background:While antibiotics transformed the field of medicine during the 20th century, their misuse has resulted in the rise of bacteria and other pathogens that are resistant to these drugs. This research tackles the urgent problem of antimicrobial resistance, which the World Health Organization has identified as a major global health concern. The study explores how effective case-based learning and traditional lectures are in educating phase 2 MBBS students about antimicrobial resistance.Materials & Methods:The research was carried out at the Department of Microbiology, Dr. Sone Lal Patel Autonomous State Medical College, Pratapgarh, Uttar Pradesh among phase 2 MBBS students. The research design incorporated a computer-based simple randomization process to impartially allocate students into group I and group II. Group I actively participated in case-based discussions on Antimicrobial Resistance whereas Group II adhered to a traditional didactic lecture format aligning with the Competency-Based Medical Education guidelines.Post-tests administered to both groups after lecture and case-based discussions immediately and another 6 weeks later.Results: The mean test score for first test scores for Case based learning (CBL) was 6.73 and for lecture was 6.65. The difference was non- significant (P> 0.05). The mean second test score conducted 6 weeks later for CBL was 6.39 and for lecture was 6.86. The difference was non- significant (P> 0.05). When analysing CBL method separately, the p-value is high (0.739), indicating no significant difference in mean scores between the first and second tests for CBL. For the Lecture method, the p-value is also high (0.64), suggesting no significant difference in mean scores between the first and second tests.Conclusion: A conclusion of no effect in statistical terms signifies that the observed impact is indistinguishable from a variation that could occur randomly. Essentially, it suggests that a program may be equally effective when compared to the program it was pitted against. Reflecting on the potential reasons for a lack of effect can offer valuable input for enhancing the program and generating hypotheses for future research endeavours

 
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