Chat Debugging: An Exploratory Study of Human-AI Collaboration to Debug Analog Circuits

• URL: http://arxiv.org/abs/2608.02955v1
• Date: Mon, 03 Aug 2026 23:40:40 GMT
• Title: Chat Debugging: An Exploratory Study of Human-AI Collaboration to Debug Analog Circuits
• Abstract summary: This study describes undergraduates' conversations with public-domain large language models (LLMs)<n>Through thematic analysis of students' voluntarily shared chat logs, we discovered multimodal usage patterns by students and considerable domain knowledge.<n>We also identified major gaps in LLM technologies and students' skills during human-AI collaborative debug.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This research paper describes an exploratory study on the effectiveness of Chat Debugging: troubleshooting malfunctioning analog circuits on breadboards and printed circuit boards (PCB) by undergraduates through conversations with public-domain large language models (LLMs). Through thematic analysis of students' voluntarily shared chat logs when debugging pre-determined buggy circuits under exam and time pressure, we discovered multimodal usage patterns by students and considerable domain knowledge and sensible debugging suggestions offered by off-the-shelf LLMs. Meanwhile, we also identified major gaps in LLM technologies and students' skills during human-AI collaborative debugging, such as LLMs' limitations in 2D/3D image-based reasoning, unjustified tone of confidence, and students' deficits in fundamental concepts and critical thinking.

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