Artificial Intelligence in Teaching and Learning

Abstract

Artificial intelligence is increasingly reshaping how teaching and learning are designed, delivered, and experienced across educational institutions worldwide. This paper examines the role of artificial intelligence in teaching and learning, tracing its evolution from early intelligent tutoring systems to contemporary generative and large language model based tools such as ChatGPT. Drawing on published research from higher education and educational psychology, the paper synthesizes evidence on the pedagogical benefits of adaptive tutoring, automated feedback, and personalized learning pathways, while also examining the growing body of literature on the risks and limitations of these technologies, including concerns about academic integrity, over-reliance, and the weak connection between many artificial intelligence applications and established pedagogical theory. The paper further considers how artificial intelligence is being applied across different phases of the teaching and learning process, from content delivery and assessment to administrative support for educators. While the evidence reviewed here indicates that artificial intelligence based tools can produce measurable learning gains under appropriate conditions, the paper concludes that realizing these benefits depends heavily on thoughtful pedagogical integration, teacher preparedness, and continued attention to the ethical and equity implications of these rapidly evolving technologies.