Affective Computing and Neuro-Symbolic Intelligence in the Protection of Digital Learning Ecologies

This 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.