Leveraging AI-driven predictive analytics to enhance cognitive assessment and early intervention in STEM learning and health outcomes

Taiwo, Kamorudeen Abiola and Busari, Isiaka Olayinka (2025) Leveraging AI-driven predictive analytics to enhance cognitive assessment and early intervention in STEM learning and health outcomes. World Journal of Advanced Research and Reviews, 27 (1). pp. 2658-2671. ISSN 2581-9615

The integration of artificial intelligence (AI) and predictive analytics in educational and healthcare settings represents a paradigm shift in how we assess cognitive abilities and implement early interventions for STEM learning difficulties. This article examines the current landscape of AI-driven cognitive assessment tools in the United States, their applications in identifying at-risk students, and their potential for improving both educational outcomes and broader health implications. Through analysis of recent implementations across American academic institutions and healthcare systems, we demonstrate that AI-powered predictive models can identify learning difficulties with 85-92% accuracy while reducing assessment time by up to 60%. The findings suggest that early intervention programs guided by AI analytics show significant improvements in STEM performance metrics and long-term cognitive health outcomes.