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2015 | OriginalPaper | Chapter

Creating Data-Driven Feedback for Novices in Goal-Driven Programming Projects

Authors : Thomas W. Price, Tiffany Barnes

Published in: Artificial Intelligence in Education

Publisher: Springer International Publishing

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Programming environments that afford the creation of media-rich, goal-driven projects, such as games, stories and simulations, are effective at engaging novice users. However, the open-ended nature of these projects makes it difficult to generate ITS-style guidance for students in need of help. In domains where students produce similar, overlapping solutions, data-driven techniques can leverage the work of previous students to provide feedback. However, our data suggest that solutions to these projects have insufficient overlap to apply current data-driven methods. We propose a novel subtree-based state matching technique that will find partially overlapping solutions to generate feedback across diverse student programs. We will build a system to generate this feedback, test the technique on historical data, and evaluate the generated feedback in a study of goal-driven programming projects. If successful, this approach will provide insight into how to leverage structural similarities across complex, creative problem solutions to provide data-driven feedback for intelligent tutoring.

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Metadata
Title
Creating Data-Driven Feedback for Novices in Goal-Driven Programming Projects
Authors
Thomas W. Price
Tiffany Barnes
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-19773-9_132

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