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Predicting optometry school grades from intellectual and nonintellectual admission variables.

P Kegel-Flom

    American Journal of Optometry and Physiological Optics
    |December 1, 1985
    PubMed
    Summary

    Predicting optometry school success requires more than just academic scores. Combining preprofessional GPA, Optometry College Admission Test (OCAT) physics scores, and personality assessments offers the best prediction for academic achievement.

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    Area of Science:

    • Optometry Education
    • Academic Performance Prediction
    • Psychometrics in Admissions

    Background:

    • Traditional admissions rely on intellectual metrics like preprofessional grades and standardized tests (Optometry College Admission Test - OCAT).
    • Non-intellectual variables are often overlooked in predicting academic success in professional programs.

    Purpose of the Study:

    • To evaluate both intellectual and non-intellectual variables as predictors of optometry school grade point average (GPA).
    • To identify the most effective combination of admission criteria for forecasting academic achievement.

    Main Methods:

    • Utilized preoptometry GPA, OCAT scores (physics and quantitative sections), and California Psychological Inventory (CPI) profile scores.
    • Employed multiple correlation and cross-validation to assess predictive validity for GPA over two years.

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    Main Results:

    • A combination of preoptometry GPA, OCAT physics scores, and CPI profile score strongly predicted two-year GPA (multiple R = 0.66, cross-validated r = 0.56).
    • OCAT quantitative scores were the best single predictor for first-year grades.
    • Adding preoptometry GPA, OCAT physics, and CPI scores improved first-year grade prediction (validity coefficient = 0.61).

    Conclusions:

    • Predicting success in optometry and other professional schools relies on a combination of preprofessional grades, standardized test scores, and personality trait measures.
    • The optimal weighting of these factors may vary by institution, but these three components are key for maximum predictive validity.