AI for Teaching and Learning: Reimagining Education brings together multidisciplinary case studies and research-informed practices across different disciplines to shed light on how Artificial Intelligence, particularly Generative Artificial Intelligence (GenAI), is reshaping higher education and workplace learning. Not merely a productivity tool, GenAI is rapidly becoming a transformative force in curriculum design, pedagogy, assessment, and learner engagement.
The volume situates AI's rise within broader technological, organizational, and societal transformations before examining how GenAI is influencing curriculum design, pedagogy, assessment redesign, and institutional strategy. It explores Large Language Models (LLMs) in computing education, personalized and adaptive learning systems, inquiry-based teaching, AI literacy development, and collaborative Human-GenAI classroom models. Its contributors critically examine misconceptions about AI, evolving academic practices, and the shifting relationship between human expertise and machine intelligence. Case studies span AI-supported teaching workflows, assessment practices, AI-enhanced exam preparation and evaluation, conversational agents in smart cities, climate education, and cultural heritage preservation, alongside immersive innovations such as Extended Realities (XR) for experiential and systems-level learning.
Across disciplines, the central argument is clear: AI must augment and compliment, not replace, human cognition. By positioning educators and institutions as architects of Human-AI collaboration, this book offers an integrated, practice-grounded framework that bridges theory and implementation, equipping leaders and educators with concrete models for responsible, future-ready transformation.