A Prompt-Engineering Approach to Develop Scalable, Flexible, and Real-Time Hybrid Micro-Level Personalization in a General Purpose AI Teaching Assistant

Explain Like I'm Normal

Researchers have developed a framework to personalize AI teaching assistants using six learner dimensions, ranging from abstraction preference to cognitive complexity. By mapping student queries to Bloom's Taxonomy and specific learner profiles, the system provides real-time, micro-level tutoring adjustments. This moves beyond generic RAG responses toward a more nuanced, human-like pedagogical interface.