Integrating AI-driven tools in higher education is an emerging area with
transformative potential. This paper introduces Iris, a chat-based virtual
tutor integrated into the interactive learning platform Artemis that offers
personalized, context-aware assistance in large-scale educational settings.
Iris supports computer science students by guiding them through programming
exercises and is designed to act as a tutor in a didactically meaningful way.
Its calibrated assistance avoids revealing complete solutions, offering subtle
hints or counter-questions to foster independent problem-solving skills. For
each question, it issues multiple prompts in a Chain-of-Thought to
GPT-3.5-Turbo. The prompts include a tutor role description and examples of
meaningful answers through few-shot learning. Iris employs contextual awareness
by accessing the problem statement, student code, and automated feedback to
provide tailored advice.
An empirical evaluation shows that students perceive Iris as effective
because it understands their questions, provides relevant support, and
contributes to the learning process. While students consider Iris a valuable
tool for programming exercises and homework, they also feel confident solving
programming tasks in computer-based exams without Iris. The findings underscore
students' appreciation for Iris' immediate and personalized support, though
students predominantly view it as a complement to, rather than a replacement
for, human tutors. Nevertheless, Iris creates a space for students to ask
questions without being judged by others.

虚拟辅导员 Iris 是一个聊天型的基于人工智能技术的工具，集成到交互式学习平台 Artemis 中，为大规模教育环境中的计算机科学学生提供个性化、上下文感知的辅助。Iris 通过引入多种提示和问题，避免提供完整答案，培养学生独立解决问题的能力。经实证评估发现，学生普遍认为 Iris 有效，因为它能理解问题、提供相关支持并促进学习过程。尽管学生普遍将 Iris 视为编程练习和作业的有价值工具，并且在计算机考试中也对解决编程任务感到自信，但学生们仍然将 Iris 视为人类辅导员的补充，而非替代工具。然而，Iris 为学生提供了一个可以自由提问而不被他人评判的空间。