Navigating Generative AI in Education: A Narrative Review of Teaching Practices and Ethical Challenges
George Ayobami Thomas
*
College of Engineering, Iowa State University, Ames, Iowa, USA.
Stephen Abu
Educational Leadership, Policy and Technology Studies, University of Alabama, Tuscaloosa, USA.
Ademola Busayo Ajayi
Research, Evaluation, Measurement, and Statistics, School of Educational Foundations, Leadership and Aviation, Oklahoma State University, USA.
Philip Andoh Frempong
College of Social and Behavioral Sciences, University of Arizona, Tucson, Arizona, USA.
Doreen Mensah
Department of Computing and Information Technology, College of Southern Nevada, Las Vegas, Nevada, USA.
John Oluwafemi Badmus
Department of Foreign Languages, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria.
Abara Happiness Etim
Government & Development Studies, Ahmadu Bello University, Zaria, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Generative Artificial Intelligence (GenAI) is rapidly reshaping higher education, prompting a fundamental reconsideration of how learning is designed, assessed, and ethically governed. This narrative review synthesizes studies published from 2022 to 2025 to examine how teaching practices and institutional policies are adapting to the widespread availability of GenAI tools. The analysis reveals a shift toward higher-order learning objectives, AI literacy, collaborative human–AI knowledge creation, and process-oriented assessment designed to maintain transparency and integrity. However, significant challenges persist, including ambiguity around authorship, inequities driven by differential access and algorithmic bias, and unresolved concerns regarding data privacy and ownership. By integrating pedagogical and ethical perspectives, this review advances current understanding by showing that responsible GenAI adoption requires coordinated transformation across curriculum design, assessment innovation, faculty development, and governance. The study concludes that human-centered, equity-focused policy frameworks are essential to ensure GenAI enhances educational quality while safeguarding academic values and social responsibility.
Keywords: Generative artificial intelligence, AI literacy, pedagogical, ethical perspectives