Related Experiment Videos
Pre-matriculation indicators of academic difficulty during veterinary school
Bonnie R Rush1, Michael W Sanderson, Ronnie G Elmore
1Career Development and Professor of Equine Internal Medicine, College of Veterinary Medicine, Kansas State University, Manhattan, KS, 66506, USA. brush@vet.k-state.edu
Journal of Veterinary Medical Education
|January 20, 2006
Summary
Veterinary student academic difficulty is linked to lower prerequisite GPAs, GRE scores, and prior college experiences. Admissions data can help identify at-risk students for early intervention.
Area of Science:
- Veterinary Education
- Academic Performance Analysis
- Student Admissions
Background:
- Identifying at-risk veterinary students is crucial for improving retention and graduation rates.
- Pre-matriculation data offers potential predictors of academic success or difficulty.
Purpose of the Study:
- To assess pre-matriculation academic and demographic factors associated with academic difficulty and graduation failure in veterinary students.
- To identify specific risk factors for early intervention strategies.
Main Methods:
- Analysis of admissions data for 1,098 veterinary students admitted between 1989 and 2000.
- Classification of students into 'academic success' and 'academic difficulty' groups.
- Statistical assessment of demographic and academic predictors.
Main Results:
- Low prerequisite GPA, low GRE scores, poor undergraduate institutional selectivity, and older age (>35) were associated with academic difficulty.
- Attending multiple undergraduate institutions or two-year colleges increased the likelihood of academic difficulty and failure to graduate.
- 84.7% of students achieved academic success, while 15.3% experienced academic difficulty (including delay or dismissal).
Conclusions:
- Pre-matriculation cognitive criteria (GRE, GPA) and undergraduate institutional history are significant predictors of veterinary student success.
- Early identification of at-risk students is possible using admissions data.
- Admissions processes could be refined to consider these identified risk factors for improved student outcomes.