CYAIHCMay 27, 2025

AITEE -- Agentic Tutor for Electrical Engineering

arXiv:2505.21582v13 citationsh-index: 1Has Code
Originality Incremental advance
AI Analysis

This addresses the need for scalable, personalized, and effective learning environments for electrical engineering students, though it is incremental as it builds on existing intelligent tutoring systems and retrieval augmented generation methods.

The paper tackled the problem of insufficient capability of large language models in addressing specific electrical circuit questions by presenting AITEE, an agent-based tutoring system that significantly outperforms baseline approaches in domain-specific knowledge application, with medium-sized LLM models showing acceptable performance.

Intelligent tutoring systems combined with large language models offer a promising approach to address students' diverse needs and promote self-efficacious learning. While large language models possess good foundational knowledge of electrical engineering basics, they remain insufficiently capable of addressing specific questions about electrical circuits. In this paper, we present AITEE, an agent-based tutoring system for electrical engineering designed to accompany students throughout their learning process, offer individualized support, and promote self-directed learning. AITEE supports both hand-drawn and digital circuits through an adapted circuit reconstruction process, enabling natural interaction with students. Our novel graph-based similarity measure identifies relevant context from lecture materials through a retrieval augmented generation approach, while parallel Spice simulation further enhances accuracy in applying solution methodologies. The system implements a Socratic dialogue to foster learner autonomy through guided questioning. Experimental evaluations demonstrate that AITEE significantly outperforms baseline approaches in domain-specific knowledge application, with even medium-sized LLM models showing acceptable performance. Our results highlight the potential of agentic tutors to deliver scalable, personalized, and effective learning environments for electrical engineering education.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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