An Evaluation of Data-Driven Programming Hints in a Classroom Setting

课堂环境下数据驱动编程提示的评估

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Abstract

Data-driven programming hints are a scalable way to support students when they are stuck by automatically offering suggestions and identifying errors. However, few classroom studies have investigated data-driven hints’ impact on students’ performance and learning. In this work, we ran a controlled experiment with 241 students in an authentic classroom setting, comparing students who learned with and without hints. We found no evidence that hints improved student performance or learning overall, and we discuss possible reasons why.

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