基于SRL视角的编程教育中AI辅助求助轨迹研究
AI-Assisted Help-Seeking Trajectories in Programming Education from an SRL-Informed Perspective
AI总结：
本研究从自我调节学习（SRL）视角出发，分析大学生编程中AI辅助求助轨迹，发现多数学生将AI用于被动调试而非主动规划，轨迹模式虽不影响成绩但显著影响代码提交次数。
摘要：
生成式AI工具为新手程序员提供即时、个性化的支持，但也引发了关于AI使用是支持还是绕过了学生问题解决调节的担忧。现有工作主要关注正确性、可用性或总体使用频率，较少关注学生与AI的求助过程。本研究通过分析大学编程中的AI辅助求助轨迹来填补这一空白。使用基于SRL的分析框架，将提示级别的求助代码与概念、实现、调试和反思形式的支持联系起来，我们分析了71名学生在Python入门课程中与任务相关的1,290条学生提示，这些提示关联到17,190次代码提交。具体来说，我们考察了求助交互在轮次和尝试中的结构，以及轨迹模式与任务分数和代码提交次数的关系。结果表明，许多学生主要将AI用于被动调试，而非有计划的自我调节问题解决。尽管轨迹模式与任务分数无显著差异，但在所需代码提交次数上差异显著。这些发现表明，AI支持的教育意义不仅在于学生是否使用AI，还在于他们在编程问题解决中求助轨迹的发展方式。
英文摘要：
Generative AI tools provide novice programmers with instant, personalized support, but also raise concerns about whether AI use supports or bypasses students' regulation of problem-solving. Existing work has largely focused on correctness, usability, or overall usage frequency, with less attention to how student--AI help-seeking unfolds. This study addresses this gap by analyzing AI-assisted help-seeking trajectories in university-level programming. Using an SRL-informed analytical framework that links prompt-level help-seeking codes to conceptual, implementation, debugging, and reflective forms of support, we analyzed 1,290 task-specific student prompts linked to 17,190 code submissions from 71 students in introductory Python programming courses. Specifically, we examined how help-seeking interactions were structured across turns and attempts, and how trajectory patterns related to task scores and the number of code submissions. Results indicate that many students primarily used AI for reactive troubleshooting rather than for planned, self-regulated problem-solving. Although trajectory patterns were not associated with significant differences in task scores, they differed substantially in the number of code submissions required. These findings suggest that the educational significance of AI support lies not only in whether students use AI, but in how their help-seeking trajectories develop during programming problem-solving.
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