UCLA

The rapid rate of improvement of natural language processing (NLP) systems and large language models (LLMs) begets a wide array of applications in the field of education and classroom instruction. The possibility of individualized practice and immediate student feedback from a low-cost and widely-available service has an enormous capacity to change modes of student instruction. In this review, we discuss the current state of research into the applications of LLMs for science and mathematics classroom education, calling particular attention to concerns surrounding overreliance and equity, as well as suggesting specific directions for future study. We conclude by considering the CourseKata interactive textbook as an illustration of how AI tools may begin to reshape traditional methods of content delivery.