AI-Powered Personalization in Learning

Abstract

The digital transformation of education through Artificial Intelligence (AI) parallels a paradigm shift akin to that observed in precision healthcare. This monograph explores the integration of AI-powered personalization in learning environments, demonstrating how intelligent systems can tailor pedagogy, content, and assessment based on learner behavior, preferences, and performance. Through a multidisciplinary lens, the work evaluates adaptive technologies, ethical challenges, algorithmic bias, and the evolving role of educators. It presents a policy-informed roadmap for scalable and equitable AI implementation in education. Drawing inspiration from personalized diagnostics and treatment models in healthcare, the monograph advocates for a learner-centered, data-informed, ethically grounded, and future-ready framework. Rich with case studies, conceptual frameworks, and evidence-based recommendations, it serves as a comprehensive guide for educators, policymakers, researchers, and AI technologists committed to shaping the future of learning. Keywords: Artificial Intelligence, Personalized Learning, Educational Technology, Adaptive Learning Systems, Learning Analytics, Algorithmic Fairness, Ethical AI, Intelligent Tutoring Systems, AI Literacy, Educational Equity, Precision Healthcare, Scalable Implementation, Policy Frameworks, Emotional AI, Augmented Reality, Virtual Reality, Human-AI Collaboration, Digital Transformation