mlsanityData to 14 Oct 2026

AI-Tutoring in Software Engineering Education

arXiv 2404.02548 ↗First posted 3 Apr 2024cs.SE cs.AIcited by 11

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Abstract (arXiv)

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.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 5 of its 47 references that are in the map. First posted on arXiv 3 Apr 2024.

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5 of 47 references.

References · 5

  1. 2023Jailbreaking ChatGPT via Prompt Engineering: An Empirical Studycited by 498
  2. 2023An Analysis of the Automatic Bug Fixing Performance of ChatGPTcited by 110
  3. 2023Is ChatGPT the Ultimate Programming Assistant -- How far is it?cited by 76
  4. 2023Learning gain differences between ChatGPT and human tutor generated algebra hintscited by 43
  5. 2023ChatGPT and Software Testing Education: Promises & Perilscited by 42

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 2; 2026: 5.

11 papers.