mlsanityData to 14 Oct 2026

GPTutor: a ChatGPT-powered programming tool for code explanation

arXiv 2305.01863 ↗First posted 3 May 2023cs.HC cs.AI cs.CLcited by 23

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Abstract (arXiv)

Learning new programming skills requires tailored guidance. With the emergence of advanced Natural Language Generation models like the ChatGPT API, there is now a possibility of creating a convenient and personalized tutoring system with AI for computer science education. This paper presents GPTutor, a ChatGPT-powered programming tool, which is a Visual Studio Code extension using the ChatGPT API to provide programming code explanations. By integrating Visual Studio Code API, GPTutor can comprehensively analyze the provided code by referencing the relevant source codes. As a result, GPTutor can use designed prompts to explain the selected code with a pop-up message. GPTutor is now published at the Visual Studio Code Extension Marketplace, and its source code is openly accessible on GitHub. Preliminary evaluation indicates that GPTutor delivers the most concise and accurate explanations compared to vanilla ChatGPT and GitHub Copilot. Moreover, the feedback from students and teachers indicated that GPTutor is user-friendly and can explain given codes satisfactorily. Finally, we discuss possible future research directions for GPTutor. This includes enhancing its performance and personalization via further prompt programming, as well as evaluating the effectiveness of GPTutor with real users.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). Builds on 3 of its 10 references that are in the map. First posted on arXiv 3 May 2023.

Builds on

3 of 10 references.

References · 3

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2019The Curious Case of Neural Text Degenerationcited by 2,916
  3. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 606

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 6; 2025: 8; 2026: 5.

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  1. 2024Exploring How Multiple Levels of GPT-Generated Programming Hints Support or Disappoint Novicescited by 10
  2. 2025The StudyChat Dataset: Analyzing Student Dialogues With ChatGPT in an Artificial Intelligence Coursecited by 9
  3. 2023Learning from Teaching Assistants to Program with Subgoals: Exploring the Potential for AI Teaching Assistantscited by 7
  4. 2023Exploring the Limits of ChatGPT in Software Security Applicationscited by 6
  5. 2024Enhancing Programming Education with ChatGPT: A Case Study on Student Perceptions and Interactions in a Python Coursecited by 6
  6. 2023Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competitioncited by 5
  7. 2023Authoring Worked Examples for Java Programming with Human-AI Collaborationcited by 2
  8. 2024Understanding Help-Seeking Behavior of Students Using LLMs vs. Web Search for Writing SQL Queriescited by 2
  9. 2024From Critique to Clarity: A Pathway to Faithful and Personalized Code Explanations with Large Language Modelscited by 2
  10. 2025VTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedbackcited by 2
  11. 2025Enhancing COBOL Code Explanations: A Multi-Agents Approach Using Large Language Modelscited by 2
  12. 2025A Meta-Analysis of LLM Effects on Students across Qualification, Socialisation, and Subjectificationcited by 2
11 more
  1. 2024Human-AI Co-Creation of Worked Examples for Programming Classescited by 1
  2. 2024Easy Come, Easy Go? Examining the Perceptions and Learning Effects of LLM-based Chatbot in the Context of Search-as-Learningcited by 1
  3. 2025Semantic Captioning: Benchmark Dataset and Graph-Aware Few-Shot In-Context Learning for SQL2Textcited by 1
  4. 2025JELAI: Integrating AI and Learning Analytics in Jupyter Notebookscited by 1
  5. 2025Design of AI-Powered Tool for Self-Regulation Support in Programming Educationcited by 0
  6. 2025Cognitive-Level Adaptive Generation via Capability-Aware Retrieval and Style Adaptationcited by 0
  7. 2026Chat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learningcited by 0
  8. 2026ALGOGEN: Tool-Generated Verifiable Traces for Reliable Algorithm Visualizationcited by 0
  9. 2026Patterns of Learner-AI Interaction and Academic Performance in an Object-Oriented Programming Coursecited by 0
  10. 2026A Retrieval-Augmented Automated Stakeholder for Requirements Elicitation Education: A Comparative Studycited by 0
  11. 2026Understanding Generative AI Use in Programming MOOCs: The Role of Course Context and Learner Characteristicscited by 0