The Use of AI in Teaching and Learning

This chapter explores the transformative potential of artificial intelligence (AI) in delivering timely, personalized, and scalable feedback across educational contexts. Grounded in foundational learning theories—including behaviorism, constructivism, and cognitive load theory—it examines how AI-powered tools enhance self-regulated learning, motivation, and equity. Technologies such as natural language processing, intelligent tutoring systems, and affective computing are analyzed for their role in fostering responsive and dialogic feedback. The chapter also critically addresses ethical concerns, including bias, data privacy, and automation bias. Through practical examples and design principles, it advocates for human-centered AI feedback systems that align with pedagogical goals, empower educators, and promote learner agency. Ultimately, it argues that feedback must remain relational and ethically grounded to truly enrich teaching and learning in the digital age.