Predictors of Performance in the Licensure Examination for Agriculturists Bases for a Proposed Plan of Action

he present study utilized correlational method to examine the factors that influenced the performance of 45 Bachelor of Agricultural Technology (BAT) graduates in their Licensure Examination for Agriculturists (LEA). SPSS Descriptive statistics, Pearson’s Correlation, and Coefficient of Determination were used to analyse the registration data on scores in LEA, academic, College Admission Test (CAT), and Course Audit. Findings showed that performances in CAT, academic, and course audit were good predictors of the graduates’ achievement in the LEA. Their low performance in these areas, however, accounted for their low LEA scores. This suggests that strict admission policy, quality instruction, and comprehensive course audit are fundamental ways associated with high licensure exam performance. Hence, the agriculture department should benchmark from high performing schools in LEA, establish tests validity and reliability, consider the CAT results in admitting students, regularly assess the effectiveness of the course audit, implement promotion and retention policies, and choose the right faculty to teach a course.

Keywords –Licensure Examination for Agriculturists (LEA), Predictors, College Admission Test, Course Audit, Academic Performance