Lect\=uraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching

Lect\=uraAgents is a newly proposed multi-agent framework designed for adaptive personalized AI-assisted learning, featuring a hierarchical architecture that mimics a professor-student dynamic. Key innovations include an adaptive embodied teaching mechanism, where a ProfessorAgent performs pedagogically motivated actions, and the Teaching Action-Speech Alignment (TASA) algorithm, which generates coherent teaching sequences based on learner profiles. The framework has shown significant improvements in lecture content quality and personalization across various educational levels, making it a valuable tool for practitioners focused on enhancing learning experiences through AI.