Abstract
There is a rapidly growing group of people learning to sew online. Without hands-on instruction, these learners are often left to discover the challenges and pitfalls of sewing through trial and error, which can be a frustrating and wasteful process. We present InStitches, a software tool that augments existing sewing patterns with targeted practice tasks to guide users through the skills needed to complete their chosen project. InStitches analyzes the difficulty of sewing instructions relative to a user's reported expertise in order to determine where practice will be helpful and then solves for a new pattern layout that incorporates additional practice steps while optimizing for efficient use of available materials. Our user evaluation indicates that InStitches can successfully identify challenging sewing tasks and augment existing sewing patterns with practice tasks that users find helpful, showing promise as a tool for helping those new to the craft.
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CITATION STYLE
Leake, M., Jin, K., Davis, A., & Mueller, S. (2023). InStitches: Augmenting Sewing Patterns with Personalized Material-Efficient Practice. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3544548.3581499
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