Exploring Machine Teaching with Children
Exploring Machine Teaching with Children
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DOI：
10.1109/vl/hcc51201.2021.9576171
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发表时间：
2021-09
期刊：
影响因子：
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通讯作者：
Utkarsh Dwivedi;Jaina Gandhi;R. Parikh;Merijke Coenraad;Elizabeth M. Bonsignore;Hernisa Kacorri
中科院分区：
文献类型：
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作者：
Utkarsh Dwivedi;Jaina Gandhi;R. Parikh;Merijke Coenraad;Elizabeth M. Bonsignore;Hernisa Kacorri
迭代地构建和测试机器学习模型可以帮助孩子们在机器学习和人工智能方面培养创造力、灵活性和舒适性。我们与14名儿童（7-13岁）和成人共同设计师一起探索儿童如何使用机器教学界面。孩子们训练图像分类器并测试彼此的模型的鲁棒性。我们的研究阐明了儿童如何对机器学习概念进行推理，为儿童设计机器教学体验提供了这些见解：(i)机器学习指标（例如置信度分数）应该在实验中可见；（ii）机器学习活动应使儿童能够交换模式，以促进思考和模式识别；（iii）界面应该允许快速数据检查（例如图像与手势）。
Iteratively building and testing machine learning models can help children develop creativity, flexibility, and comfort with machine learning and artificial intelligence. We explore how children use machine teaching interfaces with a team of 14 children (aged 7–13 years) and adult co-designers. Children trained image classifiers and tested each other's models for robustness. Our study illuminates how children reason about ML concepts, offering these insights for designing machine teaching experiences for children: (i) ML metrics (e.g. confidence scores) should be visible for experimentation; (ii) ML activities should enable children to exchange models for promoting reflection and pattern recognition; and (iii) the interface should allow quick data inspection (e.g. images vs. gestures).