Designing a Physical Computing toolkit to utilize miniature computers: A case study of Selective Exposure

© 2017 Copyright is held by the owner/author(s). Amid today's explosion of cheap and abundant tools for Physical Computing, there is a serious neglect of design for learnability. This issue is especially important when Physical Computing is not used mainly to teach engineering skills but to fos...

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Bibliographic Details
Main Authors: Marutpong Chailangka, Arnan Sipitakiat, Paulo Blikstein
Format: Conference Proceeding
Published: 2018
Subjects:
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85026295420&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/57078
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Institution: Chiang Mai University
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Summary:© 2017 Copyright is held by the owner/author(s). Amid today's explosion of cheap and abundant tools for Physical Computing, there is a serious neglect of design for learnability. This issue is especially important when Physical Computing is not used mainly to teach engineering skills but to foster creativity and innovation. This empirical study presents a design case study that took place while we were trying to figure out how to best integrate miniature computers like the Raspberry Pi into our "Programmable Brick" platform, the GoGo Board, with the goal of making new and complex functionalities, such as face detection and social media integration, learnable by beginners. Using the construct of Selective Exposure for our design and research, this paper presents a case study with secondary and high school students with our platform.