编程教育中人工智能助教的理想特征
Desirable Characteristics for AI Teaching Assistants in Programming Education
AI总结：
本研究通过部署LLM驱动的数字助教并收集813名学生的反馈，识别出编程教育中AI助教应具备即时支持、平等访问及保留学习自主性的关键特征。
摘要：
在编程课程中，向大量学生提供及时且个性化的反馈是一个长期存在的挑战。依赖人类助教（TA）的做法已被广泛研究，并揭示出若干潜在缺陷。这些缺陷包括：当需要支持时，缺乏自信的学生无法获得平等的帮助机会；以及助教直接提供解决方案，而未帮助学生培养自身的问题解决能力。随着功能强大的大语言模型（LLM）的出现，为编程情境配置的数字助教已成为一种有吸引力且可扩展的方式，能够提供即时、平等、全天候的支持。尽管数字助教能为编程任务提供多种帮助，从高层次的解题建议到直接生成解决方案，但此类工具的有效性取决于其促进有意义学习体验的能力。如果学生认为数字助教中实施的护栏过于约束，或其他期望未得到满足，他们可能会以不利于学习的方式寻求帮助。因此，识别学生认为使数字助教有价值的特征至关重要。我们在一个入门编程课程中部署了一个基于LLM的数字助手，并收集了813名学生对他们认为最重要的工具特征的反馈。我们的结果强调，学生重视此类工具因其能提供即时、引人入胜的支持，尤其是在评估截止日期等高峰时段。他们还强烈偏好能够使其在学习过程中保持自主性的功能，例如提供引导他们逐步解决问题而非直接展示解决方案的支架式帮助。
英文摘要：
Providing timely and personalized feedback to large numbers of students is a long-standing challenge in programming courses. Relying on human teaching assistants (TAs) has been extensively studied, revealing a number of potential shortcomings. These include inequitable access for students with low confidence when needing support, as well as situations where TAs provide direct solutions without helping students to develop their own problem-solving skills. With the advent of powerful large language models (LLMs), digital teaching assistants configured for programming contexts have emerged as an appealing and scalable way to provide instant, equitable, round-the-clock support. Although digital TAs can provide a variety of help for programming tasks, from high-level problem solving advice to direct solution generation, the effectiveness of such tools depends on their ability to promote meaningful learning experiences. If students find the guardrails implemented in digital TAs too constraining, or if other expectations are not met, they may seek assistance in ways that do not help them learn. Thus, it is essential to identify the features that students believe make digital teaching assistants valuable. We deployed an LLM-powered digital assistant in an introductory programming course and collected student feedback ($n=813$) on the characteristics of the tool they perceived to be most important. Our results highlight that students value such tools for their ability to provide instant, engaging support, particularly during peak times such as before assessment deadlines. They also expressed a strong preference for features that enable them to retain autonomy in their learning journey, such as scaffolding that helps to guide them through problem-solving steps rather than simply being shown direct solutions.
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。
