AI-Tutoring in Software Engineering Education
arxiv(2024)
摘要
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.
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