With the rapid advancement of artificial intelligence (AI) in various
domains, the education sector is set for transformation. The potential of
AI-driven tools in enhancing the learning experience, especially in
programming, is immense. However, the scientific evaluation of Large Language
Models (LLMs) used in Automated Programming Assessment Systems (APASs) as an
AI-Tutor remains largely unexplored. Therefore, there is a need to understand
how students interact with such AI-Tutors and to analyze their experiences. In
this paper, we conducted an exploratory case study by integrating the
GPT-3.5-Turbo model as an AI-Tutor within the APAS Artemis. Through a
combination of empirical data collection and an exploratory survey, we
identified different user types based on their interaction patterns with the
AI-Tutor. Additionally, the findings highlight advantages, such as timely
feedback and scalability. However, challenges like generic responses and
students' concerns about a learning progress inhibition when using the AI-Tutor
were also evident. This research adds to the discourse on AI's role in
education.

利用 GPT-3.5-Turbo 模型作为 AI 导师的自动化编程评估系统中，利用经验数据和探索性调查发现了不同用户类型以及与 AI 导师的交互模式，总结了实时反馈和可扩展性等优势，但也指出了一些挑战，例如通用回答和学生对使用 AI 导师时学习进展受限的担忧。这项研究为教育中人工智能的作用增加了有益的话题。