Examination of the Roles of Learning Style and Learning Strategy on the Academic Performance of First Year Medical Students

Background A diverse student population can present a challenge when designing a medical educational curriculum to meet the learning needs of all the students. Many factors, such as attendance, use of technology, and student learning style, have been investigated in the hope of predicting medical student performance. Learning style, based on Kolb's learning theory, proposes that learning is a combination of how one approaches a task and responds to the experience, whereas learning strategy measures if deep or surface learning tactics are used when learning new material. While previous studies have categorized medical students’ learning styles and used them to predict performance on standardized exams, there has not been a thorough investigation of how a student's learning style or learning strategy influences his/her academic performance throughout medical school. Objective Assess whether a student's preferred learning style and/or learning strategy influences his/her academic performance throughout the first year of medical school. Hypotheses 1) Converging learners, who learn by abstract conceptualization and active experimentation, will perform better in the anatomical sciences compared to other learning styles because these components utilize practical application of knowledge in labs. 2) Surface learners will perform better than deep learners on lab exams because these focus more on recognition and less on conceptualization. Methods First year medical students were recruited for the IRB approved study and took Kolb's Learning Style Inventory 3.1 to determine their preferred learning style: Accommodating (n=9), Assimilating (n=35), Converging (n=26), or Diverging (n=9). Learning strategy was determined using the Modified Archer's Health Professions Motivation Survey, which categorized students as Deep (n=68) or Surface (n=8) learners. Academic performance was measured using scores on graded assignments. Mean scores were compared among Kolb learning style groups using ANOVA & Tukey's HSD to adjust for multiple comparisons. Mean scores were compared among learning strategy groups using two‐sample t‐tests. Results Results showed that Convergers performed significantly higher than Assimilators in Development (87.9% vs. 83.3%; p=0.02) and Histology (90.9% vs. 88.2%; p=0.02), but not in other components. There was no significant difference in academic performance between other learning styles. When analyzing learning strategies, surface learners performed better than deep learners in Anatomy overall (87.9% vs. 83.4%; p=0.03), as well as in the Anatomy (89.0% vs. 84.0%; p=0.02) and Neuroscience labs (90.0% vs. 84.2%; p<0.05). Conclusions Interestingly, learning style and learning strategy are related to academic performance in certain components, but not others. Factors specific to components (e.g., identification vs. integration and level of self‐directed learning) may play a role in why some are affected more than others. Surface learners performed significantly better than deep learners on lab exams, but not on written exams. Since lab exams rely more on identification, a strength of surface learners, this may explain why students performed better. Continuing to explore the relationship between learning style, learning strategy, and academic performance may provide a tool to enhance medical school curricula, help faculty identify at‐risk students and provide interventional tools focused on helping these students succeed.