DEMOGRAPHIC AND INSTITUTIONAL PREDICTORS OF ACADEMIC PERFORMANCE AMONG GRADUATES OF THE FEDERAL UNIVERSITY OF AGRICULTURE, ABEOKUTA (FUNAAB): EVIDENCE FROM THE 2024 NYSC MOBILIZATION LIST

  • A. D. Ayorinde Department of Statistics, Federal University of Agriculture, Abeokuta
  • S. I. Adebayo, Department of Statistics, Federal University of Agriculture, Abeokuta
  • T. D Omoyeni Department of Statistics, Federal University of Agriculture, Abeokuta
  • I. O. Oke
Keywords: Academic Performance, Age, Gender Differences, Chi-square Test of Independence, Multinomial Logistic Regression, College Affiliation, Federal University of Agriculture, Abeokuta.

Abstract

Growing evidence points to the increasing need for higher institutions of learning to produce graduates who can not only lead innovations but also compete globally. As a measure of potential, academic performance has become a subject of scrutiny, with growing attention directed towards the factors influencing the academic outcomes of graduates.

This study employed a cross-sectional study approach to assess the association and effect of gender, age, and college affiliation on academic performance using the chi-square test of independence and multinomial logistic regression on secondary data from the 2024 FUNAAB NYSC mobilization list.

The results revealed a strong association between gender and academic performance (p < 0.01). Similarly, a strong association was found between college affiliation and academic performance (p < 0.01). Furthermore, the study revealed that age has a negative but insignificant effect on academic performance, while gender and college affiliation both exert significant effects on academic performance.

Based on the findings of this study, there is  a need for targeted support programs to assist male students. Likewise, the university body should strengthen academic resources and review instructional practices in all colleges except COLVET.

 

Author Biographies

A. D. Ayorinde, Department of Statistics, Federal University of Agriculture, Abeokuta

Department of Statistics, Federal University of Agriculture, Abeokuta

S. I. Adebayo,, Department of Statistics, Federal University of Agriculture, Abeokuta

Department of Statistics, Federal University of Agriculture, Abeokuta

T. D Omoyeni, Department of Statistics, Federal University of Agriculture, Abeokuta

Department of Statistics, Federal University of Agriculture, Abeokuta

I. O. Oke

Department of Mathematics, Federal University of Agriculture, Abeokuta

Published
2025-11-24
Section
Articles