Education have shifted into digital environments, where algorithm-driven platforms intensify extremist discourse and weaken tolerance among students. Previous studies highlight the limitations of conventional deradicalization programs, which rely on offline seminars or punitive measures and fail to address the digital and cognitive mechanisms of radicalization. To address this gap, this study investigates whether integrating Artificial Intelligence (AI), Internet of Things (IoT), blockchain, and cognitive science can provide an effective and ethical counter-radicalization framework for universities. Guided by the hypothesis that a multidisciplinary approach combining technological detection with cognitive restructuring yields measurable psychosocial impact, a Research and Development (R&D) design was applied across six stages, involving students, faculty mentors, and expert validators in Aceh, Indonesia. The AI–NLP module, fine-tuned with local data, achieved high accuracy (precision 0.94; recall 0.89), while CBT-based cognitive microlearning increased tolerance scores by 28% (p < 0.01) and reduced risky online interactions by 40%. Findings demonstrate that integrating disruptive technologies with cognitive-behavioral methods produces both technical and attitudinal benefits. The study contributes theoretically to technology-mediated deradicalization and practically to policy-driven curriculum design, with implications for cross-cultural scalability and longitudinal research..