Novices performed better and reported lower workload with GitHub Copilot than with human partners, but human partners produced more positive emotions and a smaller drop in retest performance after one week.
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Student-AI prompting trajectories in programming assignments range from direct copying to iterative refinement and serve as windows into self-regulation and learning orientation.
A survey of user studies on LLM use in programming that identifies interaction behaviors, mixed benefits and weaknesses, and factors influencing human and task performance.
citing papers explorer
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Fast and Forgettable: A Controlled Study of Novices' Performance, Learning, Workload, and Emotion in AI-Assisted and Human Pair Programming Paradigms
Novices performed better and reported lower workload with GitHub Copilot than with human partners, but human partners produced more positive emotions and a smaller drop in retest performance after one week.
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Tracing Prompt-Level Trajectories to Understand Student Learning with AI in Programming Education
Student-AI prompting trajectories in programming assignments range from direct copying to iterative refinement and serve as windows into self-regulation and learning orientation.
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Understanding the Human-LLM Dynamic: A Literature Survey of LLM Use in Programming Tasks
A survey of user studies on LLM use in programming that identifies interaction behaviors, mixed benefits and weaknesses, and factors influencing human and task performance.