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This study investigates how students use AI-generated code and whether different assistant modes affect direct copy-paste behavior, editing behavior, and code understanding.
Some sessions included assistant outputs designed to encourage careful review or reconstruction before execution. The purpose is not to trick or grade participants, but to study whether controlled friction at the point of code transfer changes how learners engage with AI-generated code.
The broader research goal is to inform the design of AI coding assistants that support learning, comprehension, and responsible reuse of generated code.
You may close this window. If you have questions about the study or wish to withdraw your data, please contact the research team.