Investigating the validity of web-enabled mechanistic case diagramming scores to assess students' integration of foundational and clinical sciences. Ferguson Kristi J,Kreiter Clarence D,Franklin Ellen,Haugen Thomas H,Dee Fred R Advances in health sciences education : theory and practice As medical schools have changed their curricula to address foundational and clinical sciences in a more integrated fashion, teaching methods such as concept mapping have been incorporated in small group learning settings. Methods that can assess students' ability to apply such integrated knowledge are not as developed, however. The purpose of this project was to assess the validity of scores on a focused version of concept maps called mechanistic case diagrams (MCDs), which are hypothesized to enhance existing tools for assessing integrated knowledge that supports clinical reasoning. The data were from the medical school graduating class of 2018 (N = 136 students). In 2014-2015 we implemented a total of 16 case diagrams in case analysis groups within the Mechanisms of Health and Disease (MOHD) strand of the pre-clinical curriculum. These cases were based on topics being taught during the lectures and small group sessions for MOHD. We created an overall score across all 16 cases for each student. We then correlated these scores with performance in the preclinical curriculum [as assessed by overall performance in MOHD integrated foundational basic science courses and overall performance in the Clinical and Professional Skills (CAPS) courses], and standardized licensing exam scores [United States Medical Licensing Exam (USMLE)] Step 1 (following core clerkships) and Step 2 Clinical Knowledge (at the beginning of the fourth year of medical school). MCD scores correlated with students' overall basic science scores (r = .46, p = .0002) and their overall performance in Clinical and Professional Skills courses (r = .49, p < .0001). In addition, they correlated significantly with standardized exam measures, including USMLE Step 1 (r = .33, p ≤ .0001), and USMLE Step 2 CK (r = .39, p < .0001). These results provide preliminary validity evidence that MCDs may be useful in identifying students who have difficulty in integrating foundational and clinical sciences. 10.1007/s10459-019-09944-y

Web-Enabled Mechanistic Case Diagramming: A Novel Tool for Assessing Students' Ability to Integrate Foundational and Clinical Sciences. Ferguson Kristi J,Kreiter Clarence D,Haugen Thomas H,Dee Fred R Academic medicine : journal of the Association of American Medical Colleges PROBLEM:As medical schools move from discipline-based courses to more integrated approaches, identifying assessment tools that parallel this change is an important goal. APPROACH:The authors describe the use of test item statistics to assess the reliability and validity of web-enabled mechanistic case diagrams (MCDs) as a potential tool to assess students' ability to integrate basic science and clinical information. Students review a narrative clinical case and construct an MCD using items provided by the case author. Students identify the relationships among underlying risk factors, etiology, pathogenesis and pathophysiology, and the patients' signs and symptoms. They receive one point for each correctly identified link. OUTCOMES:In 2014-2015 and 2015-2016, case diagrams were implemented in consecutive classes of 150 medical students. The alpha reliability coefficient for the overall score, constructed using each student's mean proportion correct across all cases, was 0.82. Discrimination indices for each of the case scores with the overall score ranged from 0.23 to 0.51. In a G study using those students with complete data (n = 251) on all 16 cases, 10% of the variance was true score variance, and systematic case variance was large. Using 16 cases generated a G coefficient (relative score reliability) equal to 0.72 and a Phi equal to 0.65. NEXT STEPS:The next phase of the project will involve deploying MCDs in higher-stakes settings to determine whether similar results can be achieved. Further analyses will determine whether these assessments correlate with other measures of higher-order thinking skills. 10.1097/ACM.0000000000002184