Ashraf Alam2026-03-052026-03-052025-12-1997983373501279798337350141https://doi.org/10.4018/979-8-3373-5012-7.ch003https://gnanaganga.alliance.edu.in/handle/123456789/9874This chapter reframes educational cybersecurity as a neurocognitively orchestrated socio-technical control regime rather than a peripheral IT safeguard. It integrates Cognitive Load Theory, dual-process reasoning, predictive processing, and neuroergonomics with affective computing, behavioral biometrics, and neuro-symbolic AI to explain how workload, vigilance, affect, and habit loops shape susceptibility to phishing, extortion, and configuration drift in digital learning ecologies. Brain-inspired anomaly detection, continuous authentication, and explainable risk analytics are embedded within human-in-the-loop governance, role-specific competency frameworks, and equity centric policy architectures. A staged implementation roadmap aligns identity fabrics, telemetry pipelines, federated learning, and impact audits with cost risk modelling and data protection mandates, yielding a globally relevant blueprint for neuro-intelligent, ethically constrained cyber defenses that preserve autonomy, inclusion, and instructional continuity.enNeuro-Symbolic IntelligenceDigital LearningCybersecurityEcologiesNeurocognitivelybook-chapter