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    Turtlestitch - Coded Embroidery

     

     

    Turtlestitch is based on a browser-based educational programming language (Snap!) to generate patterns for embroidery machines. It is easy to use, requiring no prior knowledge in programming, yet powerful in creating nowels patterns for embroidery. It is useful for designers to experiment with generative aesthetics and precision embroidery as well as a tool for innovative workshops combining an introduction to programming with a haptic output.

    Turtlestitch uses Snap!s "pen module" which it interprets as a needle and transforms its output into widely-used embroidery file formats.

     

    About Snap!

    Snap! is a visual, drag-and-drop programming language that allows students to create interactive stories, animations, games, and more, while learning about mathematical and computational ideas. Snap! was inspired by Scratch, but also targets both novice and more advanced students by including and expanding Scratch's features.

    Snap! is developed by the University of California, Berkeley with the support from the National Science Foundation, MioSoft, and the CommunicationDesign Group at SAP Labs.
    The design of Snap! is influenced and inspired by Scratch, from the Lifelong Kindergarten group at the MIT Media Lab. For more information see
    http://snap.berkeley.edu and http://scratch.mit.edu

    Snap 4.0 (beta) Copyright (C) 2015 by Jens Mönig and Brian Harvey

     

    Source Code

    Turlestitch is Free Software. Find its source code on GitHub: turtlestitch

    The Cloud platform is also Free Software. It is based on beetleCloud by Bernat Romagosa, and the source is on GitHub: turtleCloud

     

    Credits Turtlestitch

    Project Lead: Andrea Mayr-Stalder
    Lead Developer: Michael Aschauer
     

    Kindly supported by:

    OSEDA

    Vienna University Children’s Office

     

    Previous fundings

    This project has received funding from the European Union’s Horizon2020 research and innovation programme under grant agreement No824630

     

     

     

    OER-Award 2017
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