From Automation to Reflective Pedagogy: Reimagining GenAI in Teaching and Learning

Abstract

This book review of Guidebook: Generative Artificial Intelligence for Teaching and Learning by Jack Tsao and Alice Sook Mun Wong aims to provide a critical and reflective analysis that contributes to ongoing scholarly discussions surrounding the integration of generative artificial intelligence (GenAI) in higher education. By situating the guidebook within broader academic debates on AI literacy, critical pedagogy, academic integrity, and digital transformation, this review seeks to evaluate the book’s intellectual and pedagogical contributions to contemporary teaching and learning practices. The review examines how the authors position GenAI not merely as a technological innovation, but as a catalyst for rethinking assessment, critical thinking, creativity, and student engagement in increasingly AI-mediated educational environments. Furthermore, this review critically explores the guidebook’s treatment of ethical concerns, including misinformation, bias, inequitable access, privacy, and the potential erosion of students’ cognitive and analytical skills. Through an examination of the book’s practical case studies and pedagogical strategies, the review highlights its contribution to emerging conversations on AI-aware curriculum design and reflective educational practice. This critical review may serve as a valuable resource for educators, researchers, policy makers, and teacher educators seeking balanced and pedagogically grounded approaches to GenAI integration in education. Ultimately, Guidebook: Generative Artificial Intelligence for Teaching and Learning encourages educators to reconsider the meaning of meaningful learning, human judgement, and critical inquiry in the rapidly evolving landscape of artificial intelligence in education.