Scaling Up Mastery Learning with Generative AI: Exploring How Generative AI Can Assist in the Generation and Evaluation of Mastery Quiz Questions
Stephen J. Hutt, Grayson Hieb · 2024
Generative AI has the potential to scale a number of educational practices, previously limited by resources. One such instructional approach is mastery learning, a pedagogy emphasizing proficiency before progression that is highly resource (teacher time, materials) intensive. The rise of computer-based instruction offered partial solutions, tailoring student progression and automating some facets of the mastery learning process. This work in progress considers the application of large language models for content generation tailored to mastery learning. We present a paired framework for analyzing and evaluating the generated content relative to rubrics designed by the teacher. Recognizing the potential of large language models, we critically assess the potential of improving mastery-based instruction. We close our discussion by considering the applications and limitations of this approach.