AI 中文总结
该研究提出将大型语言模型应用于硬件调试的Chat-Debugging方法，通过人机交互提升电气类学生的调试信心与技能，填补了物理硬件调试辅助工具的研究空白。
AI 中文摘要
这篇处于研究进展中的论文探讨了Chat-Debugging，这是大型语言模型作为硬件调试任务助手以提升学生调试技能的新应用场景。硬件调试是一项耗时且易让人产生压力的技能，易引发挫败感等负面情绪。过往研究多聚焦于简化和自动化以数字电路为主的软件类电路调试，而Chat-Debugging可辅助处理包含模拟、数字或混合信号的物理硬件调试。研究从LLM聊天日志与对一名四年级电气工程本科生的访谈中收集定性数据，采用持续比较分析法提取主要主题。Chat-Debugging包含准确的硬件信息，能妥善处理电路的自然语言描述，提升调试信心。成功的Chat-Debugging会话包括探究LLM提出的多个潜在根本原因、消除根本原因的耐心与决心，以及学生主导调试过程并果断纠正LLM误解的行为。这种人机交互可提升电气与计算机工程专业学生调试时的信心，还能改善其调试技能。
英文摘要
This work-in-progress research paper explores Chat-Debugging, a novel use case for large language models as an assistant for hardware debugging tasks to improve students' debugging skills. Hardware debugging can be a time-consuming and stressful skill to develop, leading to frustration and other negative emotions. While past work has explored streamlining and automating software-based circuit debugging where digital circuits are dominant, Chat-Debugging aids in physical hardware debugging where circuits may be analog, digital, or mixed-signal. Qualitative data were collected from LLM chat logs and interviews with a fourth-year electrical engineering undergraduate student. Major themes were extracted using a constant comparative analysis. Chat-Debugging incorporates accurate hardware information, properly handles natural language descriptions of circuits, and improves debugging confidence. A successful Chat-Debugging session includes investigating multiple potential root causes proposed by the LLM, the patience and determination to eliminate root causes, and a student who leads the debugging process by assertively correcting the LLM's misunderstandings. This human-computer interaction can improve electrical and computer engineering students' confidence during debugging and improve their debugging skills.
CommentsThis is the accepted version of a paper accepted for presentation at the 2026 IEEE Frontiers in Education Conference (FIE). The final version will be available via IEEE Xplore at: https://ieeexplore.ieee.org/Xplore/home.jsp
