Employment Outcomes and Course Alignment of NEUST Papaya Off-campus Graduates: A Secondary Analysis of Administrative Graduate Tracer Records, FY 2018-FY 2026

Abstract

Aims: To describe recorded graduate employment outcomes, course alignment, data completeness, and selected programme-level patterns at NEUST Papaya Off-Campus, while distinguishing administrative employment indicators from conventional graduate employment rates. Study Design: Retrospective secondary analysis of administrative graduate tracer records organised as a fiscal-year cohort series. Place and Duration of Study: NEUST Papaya Off-Campus, General Tinio, Nueva Ecija, Philippines; FY 2018-FY 2026 records were consolidated and analysed in June 2026. Methodology: A census of 992 graduates listed in nine Campus Alumni Office reports was analysed. Frequencies, percentages, missing-data sensitivity bounds, chi-square diagnostics, Cramer's V, and aggregated binomial trend models were used where data were sufficiently complete and comparable. Missing values were not imputed; source inconsistencies were retained and disclosed. Results: Across FY 2018-FY 2024, 630 of 747 graduates were recorded as employed (administrative employment percentage, 84.34%). Among fully coded FY 2018-FY 2022 cohorts, recorded employment did not differ materially by cohort (chi-square(4) = 2.24, P = .691; Cramer's V = .068), and no linear trend was detected (OR = 1.08 per cohort year, 95% CI 0.89-1.30, P = .456). FY 2025-FY 2026 were highly incomplete, with 90 and 74 blank status fields. Among employed graduates with known alignment in FY 2022-FY 2024, 174 of 345 (50.43%) held course-related work; an exploratory linear trend suggested increasing course-related alignment (OR = 1.35, 95% CI 1.02-1.79, P = .036). Conclusion: The historical records show substantial employment absorption, but course-to-job alignment was nearly evenly divided and recent cohort estimates are dominated by incomplete tracking. The findings support standardised follow-up intervals, mutually exclusive coding, stronger data validation, labour-market feedback, and a richer primary tracer instrument. Results are campus-specific and should not be generalised beyond the administrative records analysed.