Full Description
This book provides a theoretical framework to allow educators, researchers, and policymakers to better understand computer‑generated writing and the policy and pedagogical implications of generative AI.
Generative AI, such as ChatGPT and Gemini, has substantially disrupted educational spaces, forcing educators, policymakers, and other stakeholders to reconsider writing and how it should be used in education. Responding to this disruption, this book provides technically sound guidance on how various stakeholders should engage with generative AI. After providing a foundational and technical discussion of the technology, this book directly addresses the educational context. Informed by theories of learning and knowledge transfer and utilizing rhetorical theories of writing, this book assesses the impact of AI on student learning, student performance, and academic honesty and integrity. In doing so, the book outlines how generative AI can be both a help and a hindrance for students, enabling readers to craft informed and meaningful policies and successfully integrate AI in the composition classroom.
This book will be of interest to scholars in the fields of Rhetoric and Composition, Technical Writing, Communication Studies, Linguistics, and TESOL, as well as to Education and Machine Learning policymakers, program directors, and researchers.
Contents
Introduction. Acknowledgments 1. How I Learned to Stop Worrying and Love AI 2. A Background in Computing 3. Computers and Language 4. Writing Theory for Generative AI 5. Risks and Opportunities in Pedagogy and Research. Conclusion. References. Index
