AUTOMATED NDPA COMPLIANCE TOOLKIT FOR ARTIFICIAL INTELLIGENCE-DRIVEN STUDENT MANAGEMENT SYSTEMS IN NIGERIAN UNIVERSITIES

Abstract

Artificial intelligence has become a central pillar of institutional management in Nigerian higher education, processing massive volumes of student data for admissions, predictive analytics, and attendance management. However, this data-intensive transformation operates under the strict oversight of the Nigeria Data Protection Act (NDPA) of 2023. Despite these legal obligations, empirical evidence reveals a systemic governance deficit, characterized by bundled consent, unlawful cross-border data transfers, and automated decision-making without human oversight. This project aimed to design, develop, and evaluate an Automated NDPA Compliance Toolkit to systematically detect and remediate compliance violations within artificial intelligence-driven Student Management Systems. Design Science Research was adopted as the primary methodology, supported by documentary analysis and comparative technology assessment. The developed toolkit features a three-layer architecture utilizing Python, FastAPI, PostgreSQL, and React.js, operationalizing the NDPA into 25 executable checks across six compliance modules. Testing was conducted using a simulated non-compliant institution and a compliant control system. The toolkit successfully identified all planted violations in the non-compliant system, assigning a compliance health index of 12 percent, while accurately passing all checks for the compliant system with a 100 percent score. The confusion matrix indicated 100 percent detection accuracy and specificity. The findings establish that software can effectively bridge the gap between statutory requirements and practical implementation by translating legal provisions into verifiable technical controls.