New Publication: The AITEE Framework for Socratic Tutoring

I am excited to announce that our latest research paper, “Recognition, Retrieval, and Response: The AITEE Framework for Socratic Tutoring in Electrical Engineering”, has been published in IEEE Access.

This paper introduces AITEE, a novel agentic tutoring framework designed to tackle the unique challenges of intelligent tutoring in symbolic and structural domains like electrical engineering.

We address three fundamental problems:

1. Robust Perception: High-fidelity recognition of hand-drawn circuits using a novel line-loss metric.
2. Structure-Aware Retrieval: Instead of standard text retrieval, we use Graph Neural Networks (Multi-Representation Indexing) to retrieve content based on topological structure.
3. Pedagogically Sound Dialogue: Delegating arithmetic to SPICE simulators to prevent LLM calculation hallucinations while maintaining Socratic instruction.

Our experiments show that structure-aware indexing enables even medium-sized models to reach 85% accuracy in methodology application for complex circuit topologies!

You can read the full open-access paper here or find more details in the Publications section.