Presentation Description
Kent Hecker1
Courtney Vengrin2, Janine Hawley2 and Heather Case2
1 International Council for Veterinary Assessment/University of Calgary
2 International Council for Veterinary Assessment
Courtney Vengrin2, Janine Hawley2 and Heather Case2
1 International Council for Veterinary Assessment/University of Calgary
2 International Council for Veterinary Assessment
Background:
As a requirement for licensure in both the United States and Canada, the North American Veterinary Licensing Examination (NAVLE) is of critical interest to veterinary medical education. While there are a multitude of factors that can relate to candidate performance on the NAVLE, identifying factors that can be addressed through educational interventions provides both candidates and educators with direction and actionable information (1).
As a requirement for licensure in both the United States and Canada, the North American Veterinary Licensing Examination (NAVLE) is of critical interest to veterinary medical education. While there are a multitude of factors that can relate to candidate performance on the NAVLE, identifying factors that can be addressed through educational interventions provides both candidates and educators with direction and actionable information (1).
One such source of information is the Veterinary Educational Assessment (VEA). The VEA is a 240-item web-based multiple-choice examination covering basic veterinary medical sciences and includes five main content areas of anatomy, physiology, pharmacology, microbiology, and pathology. Linkages between the VEA and NAVLE have been demonstrated previously (2,3). By further examining the content areas of the VEA as well as other factors we will identify potential areas of focus for veterinary medical education.
Summary: Data were collected across 14 VEA administrations spanning from January 2019 to May 2023 representing students at 20 institutions. These data were matched to candidates taking the NAVLE between Fall 2020 and Spring 2023 (n= 4436). Factors from the VEA that were investigated included overall VEA score and scores in the five content areas. NAVLE scores from first-time test taker were utilized. A regression analysis was performed to determine predictive factors for NAVLE scores from VEA content area scores.
Results:
The VEA content area scores predicted NAVLE score, F(5,4430)=889.339, p<.0005, R2 =.501. All content area scores added significantly to the prediction (p<.001) with the strongest predictors being anatomy, physiology, and pathology.
The VEA content area scores predicted NAVLE score, F(5,4430)=889.339, p<.0005, R2 =.501. All content area scores added significantly to the prediction (p<.001) with the strongest predictors being anatomy, physiology, and pathology.
Discussion:
By identifying content areas within the basic veterinary medical sciences that are predictive of the NAVLE, educational interventions and decisions could be made with greater clarity.
By identifying content areas within the basic veterinary medical sciences that are predictive of the NAVLE, educational interventions and decisions could be made with greater clarity.
Conclusion:
The VEA remains a predictor of NAVLE scores, and separate investigation of the subscores provided greater insight.
The VEA remains a predictor of NAVLE scores, and separate investigation of the subscores provided greater insight.
References (maximum three)
1.Roush, J. K., Rush, B. R., White, B. J., & Wilkerson, M. J. (2014). Correlation of pre- veterinary admissions criteria, intra-professional curriculum measures, AVMA-COE professional competency scores, and the NAVLE. Journal of Veterinary Medical Education, 41(1), 19-26.
2.Danielson JA, Wu TF, Molgaard LK, Preast VA. Relationships among common measures of student performance and scores on the North American veterinary licensing examination. J Am Vet Med Assoc. (2011) 238:454–61. 10.2460/javma.238.4.454
3.Danielson JA, Burzette RG. GRE and Undergraduate GPA as Predictors of Veterinary Medical School Grade Point Average, VEA Scores and NAVLE Scores While Accounting for Range Restriction. Front Vet Sci. 2020 Oct 28;7:576354. doi: 10.3389/fvets.2020.576354. PMID: 33195578; PMCID: PMC7655731.