Abstract
People have scientifc questions and folk theories; yet most lack the expertise to investigate them. How might people transform their questions into experiments that inform both science and their lives? This paper demonstrates how online volunteers can collaboratively design and run experiments using a novel social computing system. The Galileo system provides procedural support using three techniques: 1) experimental design workfow that provides just-in-time training; 2) review workfow with scafolded questions; and 3) automated routines for data collection. We present two empirical investigations: a study and a feld deployment with online volunteers across 16 and 8 countries respectively. People generated structurally-sound experiments on personally meaningful topics; three communities ran a week-long experiment each. We identify two key challenges for citizen-led experimentation-supporting diferent expertise levels and providing recruitment guidance-and provide specifc suggestions from the social computing literature. Our results highlight the promise and challenges of citizen-led knowledge work like experimentation.
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CITATION STYLE
Pandey, V., Koul, T., & Yang, C. (2021). Galileo: Citizen-led experimentation using a social computing system. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3411764.3445668
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