"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmers
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Abstract (arXiv)
Recent developments in deep learning have resulted in code-generation models that produce source code from natural language and code-based prompts with high accuracy. This is likely to have profound effects in the classroom, where novices learning to code can now use free tools to automatically suggest solutions to programming exercises and assignments. However, little is currently known about how novices interact with these tools in practice. We present the first study that observes students at the introductory level using one such code auto-generating tool, Github Copilot, on a typical introductory programming (CS1) assignment. Through observations and interviews we explore student perceptions of the benefits and pitfalls of this technology for learning, present new observed interaction patterns, and discuss cognitive and metacognitive difficulties faced by students. We consider design implications of these findings, specifically in terms of how tools like Copilot can better support and scaffold the novice programming experience.
Key facts. Cited by 64 papers in the map (data through 14 Oct 2026). Builds on 26 of its 122 references that are in the map. First posted on arXiv 5 Apr 2023.
Builds on
26 of 122 references.
References · 26
- 2020Language Models are Few-Shot Learnerscited by 32,419
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- 2020CodeBERT: A Pre-Trained Model for Programming and Natural Languagescited by 1,310
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- 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 274
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- 2021A Neural Network Solves, Explains, and Generates University Math Problems by Program Synthesis and Few-Shot Learning at Human Levelcited by 96
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- 2022AI-driven Development Is Here: Should You Worry?cited by 15
- 2022Pop Quiz! Can a Large Language Model Help With Reverse Engineering?cited by 14
- 2019A Survey of Automated Programming Hint Generation -- The HINTS Frameworkcited by 12
- 2022Fooling MOSS Detection with Pretrained Language Modelscited by 12
- 2021The Role of Working Memory in Program Tracingcited by 2
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Citing papers per year: 2023: 12; 2024: 23; 2025: 18; 2026: 11.
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