Explainable AI for STEAM Personalization and Ethical Assessment

Artificial intelligence is rapidly transforming educational environments, creating new opportunities to personalize learning, enhance student engagement, and support more effective assessment practices. Within Science, Technology, Engineering, the Arts, and Mathematics (STEAM) education, intelligent systems are increasingly being used to adapt learning experiences to individual needs, provide real-time feedback, and generate insights that help educators better support student success. At the same time, the growing use of AI in educational decision-making has raised important concerns regarding transparency, fairness, accountability, and trust. As learning environments become more data-driven and technologically sophisticated, there is a pressing need to ensure that intelligent systems remain understandable, ethical, and aligned with educational goals. Explainable Artificial Intelligence (XAI) has emerged as a promising approach for addressing these challenges by making AI-driven processes more transparent and interpretable for learners, educators, and institutions. Explainable AI for STEAM Personalization and Ethical Assessment examines the role of explainable and trustworthy AI technologies in shaping the future of smart education. Emphasizing both innovation and responsibility, this book highlights the importance of transparency, ethics, and human-centered design in the development of AI-enabled educational ecosystems. Through theoretical perspectives, empirical research, system frameworks, and practical applications, this book contributes to the advancement of intelligent learning environments that support both educational excellence and ethical decision-making. Covering topics such as dropout risk assessment, adaptive recommender systems, and verifiable synthetic generation, this book is an excellent academic resource for graduate and doctoral students, school leaders, curriculum designers, instructional technologists, assessment specialists, educational evaluators, AI developers, software engineers, policymakers, and more.