Designing a Centralized Student Academic Advising and Early Warning System for Improving Student Retention and Academic Performance at Federal Polytechnic Wannune

Student dropout and poor academic performance remain persistent challenges in Nigerian polytechnic education,
where reactive institutional responses often fail to identify at-risk students in time. This study presents the design
and evaluation of a Centralized Student Academic Advising and Early Warning System (CSAAEWS) developed
for Federal Polytechnic Wannune, Benue State, Nigeria. The system employs a weighted risk-scoring model
integrating academic performance, class attendance, and student engagement to classify students into low,
moderate, and high-risk categories, thereby enabling targeted and tiered interventions. Using a dataset of 30
student records from the institution, the system identified 12 students (40%) requiring academic attention: 3 high
risk students (10%) necessitating immediate intervention and 9 moderate-risk students (30%) requiring continuous
monitoring. The remaining 18 students (60%) were classified as low risk. The system generated structured early
warning alerts and specific intervention recommendations, demonstrating its operational feasibility within
resource-constrained polytechnic environments. This research contributes to the growing body of evidence
supporting data-driven student retention strategies in Nigerian tertiary institutions, offering a scalable framework
that transitions institutional practice from reactive remediation to proactive prevention.

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