PREDICTIVE ANALYTICS AND EDUCATIONAL PLANNING: EXAMINING THE ROLE OF ARTIFICIAL INTELLIGENCE IN STUDENT ENROLMENT FORECASTING IN NIGERIAN UNIVERSITIES
Keywords:
Artificial Intelligence, Data-Driven Decision-Making, Educational Planning, Predictive Analytics, Student Enrolment ForecastingAbstract
ABSTRACT
Artificial Intelligence (AI) and predictive analytics are transforming educational planning by providing data-driven solutions that enhance institutional decision-making and strategic resource management. This paper examined the role of AI in student enrolment forecasting and its implications for educational planning in Nigerian universities. It was reported that AI-powered predictive analytics offers significant opportunities for improving the accuracy of enrolment projections, optimizing resource allocation, supporting evidence-based policy formulation, strengthening institutional competitiveness and promoting sustainable university development. Relying on the Data-Driven Decision-Making Theory, the paper discussed the application of AI in forecasting admission demand, programme preferences, student retention, graduation rates, staffing requirements, infrastructure development, financial planning and institutional strategic management. Despite these prospects, the paper identified critical challenges confronting Nigerian universities including poor data quality, inadequate digital infrastructure, shortages of AI experts, poor funding and resistance to technological change. To address these challenges, the paper presented strengthening institutional data governance, developing AI-ready digital infrastructure, building the capacity of educational planners, establishing predictive analytics units and integrating AI into national higher education planning policies as suggestions to mitigate the challenges. The paper concludes that the strategic adoption of AI-driven predictive analytics is essential for improving the effectiveness, efficiency and sustainability of educational planning in Nigerian universities.
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