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"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmers

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arxiv 2304.02491 v1 pith:GVTKXOC7 submitted 2023-04-05 cs.HC cs.AI

classification cs.HCcs.AI
keywords codecopilotlearningprogrammingtoolsintroductorynovicenovices
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. To Google or To ChatGPT? A Comparison of CS2 Students' Information Gathering Approaches and Outcomes

    cs.HC 2025-01 conditional novelty 6.0 of 10

    In a 32-participant within-subjects study, CS2 students scored significantly better on a conceptual quiz for currying when learning via web search than via ChatGPT, while query behavior differed markedly between the t...

  2. The New Calculator? Practices, Norms, and Implications of Generative AI in Higher Education

    cs.HC 2025-01 conditional novelty 6.0 of 10

    Interviews show university students self-govern their GenAI use under unclear guidelines, developing unspoken rules and reliance strategies amid plagiarism-focused institutional messaging.

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