CodeToon: Story Ideation, Auto Comic Generation, and Structure Mapping for Code-Driven Storytelling

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Abstract

Recent work demonstrated how we can design and use coding strips, a form of comic strips with corresponding code, to enhance teaching and learning in programming. However, creating coding strips is a creative, time-consuming process. Creators have to generate stories from code (codeĝ†▪story) and design comics from stories (storyĝ†▪comic). We contribute CodeToon, a comic authoring tool that facilitates this code-driven storytelling process with two mechanisms: (1) story ideation from code using metaphor and (2) automatic comic generation from the story. We conducted a two-part user study that evaluates the tool and the comics generated by participants to test whether CodeToon facilitates the authoring process and helps generate quality comics. Our results show that CodeToon helps users create accurate, informative, and useful coding strips in a significantly shorter time. Overall, this work contributes methods and design guidelines for code-driven storytelling and opens up opportunities for using art to support computer science education.

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APA

Suh, S., Zhao, J., & Law, E. (2022). CodeToon: Story Ideation, Auto Comic Generation, and Structure Mapping for Code-Driven Storytelling. In UIST 2022 - Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, Inc. https://doi.org/10.1145/3526113.3545617

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