首页|New Machine Learning Study Findings Recently Were Reported by Researchers at Clemson University (Shifting Roles and Slow Research: Children's Roles In Participatory Co-design of Critical Machine Learning Activities and Technologies)
New Machine Learning Study Findings Recently Were Reported by Researchers at Clemson University (Shifting Roles and Slow Research: Children's Roles In Participatory Co-design of Critical Machine Learning Activities and Technologies)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Clemson, South Carolina, by NewsRx correspondents, research stated, “Including children’s voices in the design of learning activities and technologies has increasingly become a subject of conversation among researchers and learning designers. Research suggests children have lived experiences that position them as useful contributors in co-designing curricula activities or technologies they will use.” Funders for this research include National Science Foundation10.13039/501100008982, National Sci- ence Foundation (NSF), Office of the Associate Dean for Research in the College of Education at Clemson University. Our news editors obtained a quote from the research from Clemson University, “However, one significant challenge in participatory co-design is engaging children in the co-design of curricula when they have not yet learned the disciplinary content within the curricula. We present our two-year participatory design-based research study in which we co-designed a Critical Machine Learning educational programme with different groups of children at two after-school centres over two consecutive years. In this paper, we characterize the roles children embodied in two cycles of participatory co-design and how the program’s activities impacted these roles. Findings in this study suggest that in two participatory design-based research cycles, children embodied different roles of tester, informant, or designer of both AI learning activities and AI technologies.” According to the news editors, the research concluded: “Based on this design-based research study, we propose that a ‘slow research’ approach that emphasises trust-building and a deep understanding of children’s perspectives can be instrumental in achieving meaningful co-design outcomes.” This research has been peer-reviewed.
ClemsonSouth CarolinaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningTechnologyClemson University
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Taylor & Francis
