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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CITATION STYLE
Price, T. W., Marwan, S., Winters, M., & Williams, J. J. (2020). An Evaluation of Data-Driven Programming Hints in a Classroom Setting. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12164 LNAI, pp. 246–251). Springer. https://doi.org/10.1007/978-3-030-52240-7_45
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