James Hutson – författare

Designed to cater to the needs of both novice and seasoned writing instructors, this book provides a range of practical and adaptable strategies for integrating generative artificial intelligence (AI) into English writing curricula.

Generative AI in the English Composition Classroom proposes strategic methodologies to ensure that AI is utilized as a facilitator of learning and creativity, rather than as a shortcut to academic success. With a particular emphasis on sophisticated large language models such as Claude, ChatGPT, and Gemini, this book critically addresses potential challenges, including concerns related to academic integrity. It includes case studies and practical strategies to exemplify how AI can enhance the writing process while emphasizing the continuing importance of a solid foundation in writing structure, processes, and rhetorical strategies. These case studies and strategies are designed for immediate application, offering educators and students practical tools to effectively navigate AI-augmented writing environments. Finally, the book looks to the future, discussing the evolving skillsets required in the workforce and how educators can equip students for a future in which AI is an integral component.

A forward-thinking and invaluable guide, this book will be of interest to educators involved in teaching English Composition and writing.

Designed to cater to the needs of both novice and seasoned writing instructors, this book provides a range of practical and adaptable strategies for integrating generative artificial intelligence (AI) into English writing curricula.

Generative AI in the English Composition Classroom proposes strategic methodologies to ensure that AI is utilized as a facilitator of learning and creativity, rather than as a shortcut to academic success. With a particular emphasis on sophisticated large language models such as Claude, ChatGPT, and Gemini, this book critically addresses potential challenges, including concerns related to academic integrity. It includes case studies and practical strategies to exemplify how AI can enhance the writing process while emphasizing the continuing importance of a solid foundation in writing structure, processes, and rhetorical strategies. These case studies and strategies are designed for immediate application, offering educators and students practical tools to effectively navigate AI-augmented writing environments. Finally, the book looks to the future, discussing the evolving skillsets required in the workforce and how educators can equip students for a future in which AI is an integral component.

A forward-thinking and invaluable guide, this book will be of interest to educators involved in teaching English Composition and writing.

This book delineates a comprehensive framework designed to ultimately assist organizations as they navigate the critical juncture—often termed the inflection point—in adopting generative Artificial Intelligence (AI). Addressing the exigent shift in organizational strategy mandated by Industry 4.0, and urging a transition from mere digital transformation to what is being progressively understood as "generative transformation,” it fills a conspicuous lacuna in both academic and practical discourses by presenting a timely synthesis of research, empirical studies, and case analyses. The authors utilize an interdisciplinary methodology, bridging the epistemological divide between the technological intricacies of generative AI and its effective implementation within institutional frameworks. Reorienting the focus of organizational leaders from a simplistic replacement paradigm to one of technological-human augmentation, it works toward a prescriptive blueprint for enabling organizations to adopt generative AI without compromising their most valuable asset: human intellectual and emotional capital. Fostering interdisciplinary dialog among academics, industry professionals, and policymakers, it fills a critical gap in current discourses and serves as a catalyst for future research and collaboration.

This book delineates a comprehensive framework designed to ultimately assist organizations as they navigate the critical juncture—often termed the inflection point—in adopting generative Artificial Intelligence (AI). Addressing the exigent shift in organizational strategy mandated by Industry 4.0, and urging a transition from mere digital transformation to what is being progressively understood as "generative transformation,” it fills a conspicuous lacuna in both academic and practical discourses by presenting a timely synthesis of research, empirical studies, and case analyses. The authors utilize an interdisciplinary methodology, bridging the epistemological divide between the technological intricacies of generative AI and its effective implementation within institutional frameworks. Reorienting the focus of organizational leaders from a simplistic replacement paradigm to one of technological-human augmentation, it works toward a prescriptive blueprint for enabling organizations to adopt generative AI without compromising their most valuable asset: human intellectual and emotional capital. Fostering interdisciplinary dialog among academics, industry professionals, and policymakers, it fills a critical gap in current discourses and serves as a catalyst for future research and collaboration.

AI-powered coding tools are revolutionizing software development, transforming programming from a specialized skill into an accessible educational practice across disciplines. This book investigates how tools such as Cursor AI, GitHub Copilot, and Replit''s Ghostwriter are dismantling traditional barriers to entry for learners—particularly those from non-STEM backgrounds—by enabling natural language code generation, intelligent debugging, and interactive, project-based learning. Bridging the gap between theoretical instruction and practical application, the book serves as both a guide and a critical framework for integrating generative AI into curricula. It highlights how these tools expand the boundaries of programming education by supporting interdisciplinary applications, from literary analysis to creative writing, thereby making coding relevant and actionable for students in the humanities and beyond. The book equips educators with the tools and strategies necessary to incorporate AI-assisted programming into diverse academic contexts by offering lesson plans and adaptable project models. This resource is essential for instructors seeking to demystify coding, promote inclusivity in technical learning, and reimagine the role of software literacy in the twenty-first-century classroom.

AI-powered coding tools are revolutionizing software development, transforming programming from a specialized skill into an accessible educational practice across disciplines. This book investigates how tools such as Cursor AI, GitHub Copilot, and Replit''s Ghostwriter are dismantling traditional barriers to entry for learners—particularly those from non-STEM backgrounds—by enabling natural language code generation, intelligent debugging, and interactive, project-based learning. Bridging the gap between theoretical instruction and practical application, the book serves as both a guide and a critical framework for integrating generative AI into curricula. It highlights how these tools expand the boundaries of programming education by supporting interdisciplinary applications, from literary analysis to creative writing, thereby making coding relevant and actionable for students in the humanities and beyond. The book equips educators with the tools and strategies necessary to incorporate AI-assisted programming into diverse academic contexts by offering lesson plans and adaptable project models. This resource is essential for instructors seeking to demystify coding, promote inclusivity in technical learning, and reimagine the role of software literacy in the twenty-first-century classroom.

This research monograph explores the complex resistance to integrating Artificial Intelligence (AI) within higher education institutions. Despite the significant potential of AI to enhance education, faculty adoption remains inconsistent and is often met with skepticism.

This book investigates key factors contributing to this resistance, such as leadership deficits, funding barriers, cultural inertia, and faculty attitudes toward technological change. Drawing on qualitative and quantitative empirical data, case studies from U.S. and international institutions, and theoretical analysis, the book uncovers underlying concerns about job security and professional identity.

It points to actionable strategies for overcoming these barriers, and will be relevant for scholars, researchers, advanced students and educators grappling with issues navigating technological integration in academia, and with interests in the sociology of education, educational technology, and higher education administration.

This research monograph explores the complex resistance to integrating Artificial Intelligence (AI) within higher education institutions. Despite the significant potential of AI to enhance education, faculty adoption remains inconsistent and is often met with skepticism.

This book investigates key factors contributing to this resistance, such as leadership deficits, funding barriers, cultural inertia, and faculty attitudes toward technological change. Drawing on qualitative and quantitative empirical data, case studies from U.S. and international institutions, and theoretical analysis, the book uncovers underlying concerns about job security and professional identity.

It points to actionable strategies for overcoming these barriers, and will be relevant for scholars, researchers, advanced students and educators grappling with issues navigating technological integration in academia, and with interests in the sociology of education, educational technology, and higher education administration.