What’s the problem that the University of Florida is trying to solve?
Doubling the rate of math learning presents significant challenges, such as students’ disengagement and lack of motivation. Many students struggle with grasping mathematical concepts because they can’t relate to the topics and have limited options to tailor their learning experience. These issues disproportionately affect low-income students. Although advancements in AI offer exciting possibilities for the future of education, current applications of AI in education often place students in a passive role, in which they are only receivers of the technology’s decision-making.
What does ALTER-Math do?
ALTER-Math will adopt the learning-by-teaching (LT) framework, which reshapes students’ roles from passive learners into proactive teachers and develops and applies effective and scalable AI-augmented teachable agents using large language models. ALTER-Math will be embedded in Math Nation for algebra learning and influence millions of K-4 students.
What is the wow factor?
While we focus on training LLMs to be better teachers, they are already exceptional students. The learning-by-teaching process perfectly echoes reinforcement learning from human feedback to teach LLMs.
How does it work?
Our solution includes AI scaffolding, such as a teachable agent engineered with personalities to provide a personalized and adaptive learning experience for students working in Math Nation; a mentor agent that empowers students’ teaching with strategic feedback and choices to help them generalize their learning; and an automatic evaluation system to investigate students’ teaching quality and strategies for further reflection and improvement.