Order your copies:  Print Hardcover  |  ebook  |  Amazon  |  Google Books | Other Distributors Reimagining STEAM: AI, Art, and Technology for Creative Learning examines the evolving intersections of artificial intelligence, art, technology, and interdisciplinary learning within contemporary STEAM education. Bringing together theoretical perspectives, empirical research, classroom practices, and critical inquiry, the volume explores how emerging technologies and arts-based approaches can support creativity, human agency, interdisciplinary thinking, and innovative pedagogy. Across diverse educational contexts, the chapters address human–AI interaction, visual metaphor, science communication, storytelling, media arts, sustainability, game design, creative identity, and AI-integrated art education. The volume also considers the ethical, cultural, and pedagogical implications of emerging technologies, emphasizing the importance of human-centered and reflective approaches to technological integration. Collectively, the contributions position the arts as central to STEAM education and offer educators, researchers, and practitioners perspectives and practices for developing creative, inclusive, and future-oriented learning environments. Table of Contents Introduction Reimagining STEAM through AI, Art, and Technology Sahar Aghasafari & Jeremy Blair Section I: Foundations and Theoretical Perspectives Conceptual frameworks, pedagogy, human–AI interaction, and theoretical grounding Chapter 1 Empowering Human Agency in Transdisciplinary STEAM through Artificial Intelligence Guey-Meei Yang Chapter 2 Human–Machine Interplay: Visual Metaphor in STEAM Pedagogy Hsiao-Ping Chen & Guey-Meei Yang Section II: Interdisciplinary Learning, Science Communication, and Applied STEAM Practices Empirical research, interdisciplinary projects, storytelling, design-based learning, and science communication Chapter 3 Structuring Science Through Story: Visual and Animated Narratives of Protein Folding in Undergraduate STEAM Research Sahar Aghasafari, Li Cai, Mark Malloy, Sara Luis, Earl Jasper Gerona & Sergio González-Eulogio Chapter 4 Designing Tomorrow: Empowering Youth to Build Sustainable Futures through Storytelling, Media Arts, and Minecraft Sahar Aghasafari & Mark Malloy Section III: Creativity, Identity, and Classroom Innovation Creative pedagogy, identity, classroom experimentation, reflective practice, and AI in art education Chapter 5 Resonant Pedagogies: Craft, Care, and Creative Risk in STEAM Classrooms Krystian K. Ramlogan Chapter 6 (Re)Playing Self: Autoethnographic Game Design in the Art Classroom Jeremy Blair Chapter 7 Art Meets AI: Opportunities and Challenges in the Art Classroom Jeremy Blair Section IV: Global and Critical Futures in STEAM Global perspectives, ethics, speculative futures, critical inquiry, and emerging directions in AI-integrated education Chapter 8 Global Perspectives on AI-Driven STEAM Pedagogy Ambika Hanchate Chapter 9 Imagining Futures: Art, Algorithms, and the Weight of Inherited Worlds Jeremy Blair & Sahar Aghasafari Conclusion Future Directions for AI, Art, and Technology in STEAM Education Sahar Aghasafari & Jeremy Blair  

Order Print Copies | Amazon | Hardcover | eBook | Google Books This volume examines the intersection of digital learning, learning analytics, and student success systems in contemporary higher education. Nine chapters written by scholars and practitioners from multiple geographic contexts analyze how artificial intelligence, institutional automation, faculty role transformation, and inclusive access technologies reshape higher education practice and outcomes. The volume combines theoretical frameworks with case evidence from national systems, disciplinary fields, and individual institutions. Core themes include the tension between digitalization and equity, the evolution of immersive and hybrid learning models, the role of data-informed decision-making in institutional performance, and the imperative to design digital transformations that serve all students, not only the advantaged. Intended for researchers, institutional leaders, faculty, graduate students, and policymakers, the volume argues that higher education can become simultaneously more efficient and more humane through thoughtful implementation and critical attention to context.

This volume investigates the future of digital pedagogy, curriculum, assessment, and quality assurance across rapidly changing higher education systems. Twelve chapters address decentralized and hybrid learning, personalized and adaptive education, smart institution roadmaps, teaching efficiency, fragmented quality frameworks, accreditation and research excellence, Faculty 4.0, the faculty role as a human safeguard in AI-rich environments, hospitality employability, and assessment integrity. The contributors draw on international contexts to examine how institutional design, faculty capability, technology, and governance influence learning outcomes and public trust. The volume gives particular attention to the tension between flexibility and coherence, innovation and quality, automation and human judgment. It also considers how graduate attributes and assessment practices must evolve as artificial intelligence becomes embedded in learning and professional work. Intended for researchers, curriculum designers, faculty, institutional leaders, quality assurance professionals, graduate students, and policymakers, the volume argues that credible digital futures require pedagogical purpose, ethical assessment, inclusive access, and sustained investment in human expertise.

This volume examines how digital learning, analytics, and student success systems are quietly rewriting the inner grammar of higher education. It looks beyond platforms as tools and asks what happens when learning becomes traceable, adaptive, and continuously interpreted through data. The chapters explore online and hybrid learning, predictive analytics, advising systems, student engagement, retention, and the ethical use of educational data. At its core, the volume asks a difficult question: can institutions use digital intelligence to support students without reducing them to dashboards? The answer, unsurprisingly, is complex, hopeful, and sometimes unsettling.

This volume examines how artificial intelligence, automation, blockchain, and data-informed governance are changing decision-making in higher education. Ten chapters move from academic credentials and learning records to educator roles in open and distance learning, university digital transformation strategies, faculty capability development, smart teaching governance, AI-supported teaching tools, disability inclusion, and digital-age policy. Contributions from multiple national and institutional contexts combine conceptual analysis, case comparison, technical architectures, and practical institutional recommendations. A central concern is how universities can use intelligent systems to improve efficiency, trust, access, and responsiveness while preserving professional judgment, transparency, privacy, and human responsibility. The volume treats faculty development and inclusion as essential parts of technological transformation rather than secondary implementation issues. Intended for researchers, university leaders, faculty developers, quality assurance professionals, policymakers, IT teams, and graduate students, it argues that decision intelligence becomes educationally valuable only when automation is governed ethically, interpreted critically, and aligned with institutional learning.

This volume examines the transformation of higher education through smart university models, digital learning, artificial intelligence, and administrative innovation. Twelve chapters connect global collaboration, adaptive learning in sports education, responsible AI feedback, decentralized and hybrid pedagogy, institutional digital transformation, faculty role change, student online experiences, academic quality, teaching capital, and AI-driven university administration. The contributors combine conceptual reviews, empirical cases, governance analysis, and practice-oriented frameworks from diverse geographic and institutional contexts. Rather than treating smartness as a collection of technologies, the volume asks how universities can integrate data, automation, learning platforms, and intelligent systems while protecting equity, trust, privacy, and professional judgment. It highlights student experience and faculty capability as critical tests of whether digital transformation creates genuine educational value. Intended for researchers, university leaders, faculty, quality assurance professionals, policymakers, administrators, IT teams, and graduate students, the volume argues that smart universities must be designed as humane, accountable, and continuously learning institutions.