利用编译器集成式对话式人工智能扩展CS1课程支持
Scaling CS1 Support with Compiler-Integrated Conversational AI
AI总结：
本文提出编译器集成的对话式AI工具DCC Sidekick，利用编译器错误上下文生成编程错误解释，并通过大规模CS1课程使用数据验证了其在扩展编程教育支持方面的有效性与可扩展性。
摘要：
本文介绍了DCC Sidekick，这是一个基于网络的对话式AI工具，通过生成教育性的编程错误解释来增强现有的由大语言模型（LLM）驱动的C/C++编译器。该工具将代码显示、编译时和运行时错误消息以及栈帧读取与AI界面无缝结合，利用编译器错误上下文来改进解释质量。我们分析了一门澳大利亚大型CS1课程的使用数据，在该课程中，959名学生在七周内参与了11,222次DCC Sidekick会话，产生了17,982条错误解释。值得注意的是，超过50%的交互发生在工作时间之外，凸显了该工具作为随时可用资源的价值。我们的研究结果表明，AI辅助调试工具被广泛采用，证明了它们在支持大规模CS1课程方面的可扩展性。我们为希望引入AI工具并配备适当教学保障措施的教育工作者提供了实现见解和建议。
英文摘要：
This paper introduces DCC Sidekick, a web-based conversational AI tool that enhances an existing LLM-powered C/C++ compiler by generating educational programming error explanations. The tool seamlessly combines code display, compile- and run-time error messages, and stack frame read-outs alongside an AI interface, leveraging compiler error context for improved explanations. We analyse usage data from a large Australian CS1 course, where 959 students engaged in 11,222 DCC Sidekick sessions, resulting in 17,982 error explanations over seven weeks. Notably, over 50% of interactions occurred outside business hours, underscoring the tool's value as an always-available resource. Our findings reveal strong adoption of AI-assisted debugging tools, demonstrating their scalability in supporting extensive CS1 courses. We provide implementation insights and recommendations for educators seeking to incorporate AI tools with appropriate pedagogical safeguards.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
