Study preferences and exam outcomes in medical education: insights from renal physiology

Abstract

Background: Efficient learning strategies and resource utilization are critical in medical education, especially for complex subjects like renal physiology. This is increasingly important given the rise in chronic renal diseases and the decline in nephrology fellowships. However, the correlations between study time, perceived utility of learning resources, and academic performance are not well-explored, which led to this study.

Methods: A cross-sectional survey was conducted with second-year medical students at the University of Bergen, Norway, to assess their preferred learning resources and study time dedicated to renal physiology. Responses were correlated with end-of-term exam scores.

Results: The study revealed no significant correlation between time spent studying and overall academic performance, highlighting the importance of study quality over quantity. Preferences for active learning resources, such as Team-Based Learning, interactive lessons and formative assignments, were positively correlated with better academic performance. A notable correlation was found between students' valuation of teachers' professional competence and their total academic scores. Conversely, perceived difficulty across the curriculum and reliance on self-found online resources in renal physiology correlated negatively with academic performance. 'The Renal Pod', a locally produced renal physiology podcast, was popular across grades. Interestingly, students who listened to all episodes once achieved higher exam scores compared to those who listened to only some episodes, reflecting a strategic approach to podcast use. Textbooks, while less popular, did not correlate with higher exam scores. Despite the specific focus on renal physiology, learning preferences are systematically correlated with broader academic outcomes, reflecting the interconnected nature of medical education.

Conclusion: The study suggests that the quality and strategic approaches to learning significantly impact academic performance. Successful learners tend to be proactive, engaged, and strategic, valuing expert instruction and active participation. These findings support the integration of student-activating teaching methods and assignments that reward deep learning.

Keywords: Academic achievement; Active learning; Learning resources; Medical school; Medical students; Renal physiology; Teaching methods.

Fig. 1

Comparison of exam grades and scores between the whole class and the sample population. Left panel: Grades are categorized into AB (n = 24/n = 41), C (n = 24/n = 71), and DEF (n = 24/n = 77). Right panel: Scores, represented as fractions of the total obtainable score, are plotted in ascending order against the cumulative fraction of students for the whole class (n = 189) and the sample population (n = 72), with values ranging from 1/n to n/n

Fig. 2

Comparison of the perceived usefulness of active learning methods and academic performance. The left panel shows the distribution of students’ preferences across different grade categories; high (AB), mid (C), and low (DEF) performers. The bars are divided into segments representing preference-cohorts as indicated by the legends. The right panels depict exam scores sorted from low to high as a function of the cohort-normalized number of students. Upper panel. Significant differences in exam scores were observed among the preference cohorts for ‘TBL’. Mean exam scores for the three cohorts (right panel): ‘Very useful/useful’; 74.6% ± 9.7%, n = 40), ‘Somewhat useful’; 72.8% ± 10.0%, n = 20, ‘Not very useful/not useful’; 63.4% ± 9.5%, n = 12. ANOVA: F (2, 69) = 6.121, p = 0.0036. Post hoc tests: **p = 0.0024 between the ‘Very useful/useful’ and ‘Not very useful/not useful’ cohorts, and *p = 0.0286 between the ‘Somewhat useful’ and ‘Not very useful/not useful’ cohorts. Middle and lower panels. No significant differences in exam scores were seen among the preference-cohorts for ‘Interactive lessons’ or ‘Renal physiology lab’

Fig. 3

Comparison of perceived usefulness of indicated learning methods and academic performance (p > 0.05). See Fig. 2 for a detailed explanation of the panel structure

Fig. 4

Comparison of perceived difficulty of renal physiology and academic performance. See Fig. 2 for a detailed explanation of the panel structure. Upper panel. Significant differences in exam scores were observed based on the perceived difficulty of renal physiology. Mean exam scores for the three cohorts (right panel): ‘Easy/moderate’; 75.1% ± 9.7%, n = 32, ‘Hard’; 71.8% ± 10.3%, n = 33, ‘Very hard’; 64.3% ± 10.8%, n = 8. ANOVA: F (2, 70) = 3.793, p = 0.0273. Post hoc tests: *p = 0.0228 between the ‘Easy/moderate’ and ‘Very hard’ cohorts. Lower panel: Significant differences in exam scores were observed based on the perceived difficulty of endocrinology. Mean exam scores for the three cohorts (right panel): ‘Very easy/easy’; 79.5% ± 7.8%, n = 13, ‘Moderate’; 73.8% ± 9.2%, n = 39, ‘Hard/very hard’; 64.9% ± 9.7%, n = 21. ANOVA: F (2, 70) = 11.49, p < 0.0001. Post hoc tests: ****p < 0.0001 between the ‘Very easy/easy’ and ‘Hard/very hard’ cohorts, and **p = 0.0017 between the ‘Moderate’ and ‘Hard/very hard’ cohorts

Fig. 5

Comparison of time spent preparing for active learning sessions and academic performance. See Fig. 2 for a detailed explanation of the panel structure. Upper and middle panel. No overall significant difference for TBL and Interactive lessons (p > 0.05). Lower panel. Mean exam scores for the four cohorts (right panel) based on time spent preparing for the ‘Renal Physiology lab’: ‘Not prepared’; 72.4% ± 7.9%, n = 10, ‘Less than 30 min’; 75.1% ± 8.9%, n = 31, ‘More than 1 h’; 67.2% ± 12.5%, n = 19, ‘Anything more than 2hurs’; 73.0% ± 9.7%, n = 14. ANOVA: F (3, 70) = 2.498, p = 0.0667. Post hoc tests: *p = 0.0400 between the ‘Less than 30 min’ and ‘More than 1 h’ cohorts

Fig. 6

The impact of study time and podcast engagement on academic performance. See Fig. 2 for a detailed explanation of the panel structure. Upper panel. No significant difference in academic performance based on time spent studying renal physiology (p > 0.05). Lower panel. Significant differences in performance based on podcast usage. Mean cohort exam scores (right panel): ‘All the episodes multiple times’; 71.4% ± 10.0%, n = 13 ‘All episodes once’; 76.3% ± 8.7%, n = 22 compared to those who listened to only some episodes: 66.2% ± 8.7%, n = 16. ANOVA, F (4, 67) = 2.958, p = 0.0259) post hoc test: *p = 0.0217

Fig. 7

Comparison of academic performance and recommendations for the formative assignment, showing significant differences in exam scores based on students’ perceptions of the formative assignment. See Fig. 2 for a detailed explanation of the panel structure. Mean exam scores for the three cohorts (right panel): ‘Should be expanded or continued’; 73.2% ± 10.3%, n = 33, ‘Should be discontinued’; 63.4% ± 10.4%, n = 12, and ‘Other’; 75.0% ± 8.7% n = 27. ANOVA: F (2, 69) = 6.136, p = 0.0035. Post hoc tests: *p = 0.0117 between the ‘Should be expanded or continued’ and ‘Should be discontinued’; **p = 0.0029 between ‘Other ' and ‘Should be discontinued’ cohort