  This study explores the integration of generative artificial intelligence
(AI), specifically large language models, with multi-modal analogical reasoning
as an innovative approach to enhance science, technology, engineering, and
mathematics (STEM) education. We have developed a novel system that utilizes
the capacities of generative AI to transform intricate principles in
mathematics, physics, and programming into comprehensible metaphors. To further
augment the educational experience, these metaphors are subsequently converted
into visual form. Our study aims to enhance the learners' understanding of STEM
concepts and their learning engagement by using the visual metaphors. We
examine the efficacy of our system via a randomized A/B/C test, assessing
learning gains and motivation shifts among the learners. Our study demonstrates
the potential of applying large language models to educational practice on STEM
subjects. The results will shed light on the design of educational system in
terms of harnessing AI's potential to empower educational stakeholders.
