TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866915431593279488 |
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| author | Kawabe, Wataru Fukuda, Hiroto Shitara, Akihisa Nakao, Yuri Sugano, Yusuke |
| author_facet | Kawabe, Wataru Fukuda, Hiroto Shitara, Akihisa Nakao, Yuri Sugano, Yusuke |
| contents | We introduce TofuML, an interactive system designed to make machine learning (ML) concepts more accessible and engaging for non-expert users. Unlike conventional GUI-based systems, TofuML employs a physical and spatial interface consisting of a small device and a paper mat, allowing users to train and evaluate sound classification models through intuitive, toy-like interactions. Through two user studies -- a comparative study against a GUI-based version and a public event deployment -- we investigated how TofuML impacts users' engagement in the ML model creation process, their ability to provide appropriate training data, and their conception of potential applications. Our results indicated that TofuML enhanced user engagement compared to a GUI while lowering barriers for non-experts to engage with ML. Users demonstrated creativity in conceiving diverse ML applications, revealing opportunities to optimize between conceptual understanding and user engagement. These findings contribute to developing interactive ML systems/frameworks designed for a wide range of users. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_00252 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices Kawabe, Wataru Fukuda, Hiroto Shitara, Akihisa Nakao, Yuri Sugano, Yusuke Human-Computer Interaction We introduce TofuML, an interactive system designed to make machine learning (ML) concepts more accessible and engaging for non-expert users. Unlike conventional GUI-based systems, TofuML employs a physical and spatial interface consisting of a small device and a paper mat, allowing users to train and evaluate sound classification models through intuitive, toy-like interactions. Through two user studies -- a comparative study against a GUI-based version and a public event deployment -- we investigated how TofuML impacts users' engagement in the ML model creation process, their ability to provide appropriate training data, and their conception of potential applications. Our results indicated that TofuML enhanced user engagement compared to a GUI while lowering barriers for non-experts to engage with ML. Users demonstrated creativity in conceiving diverse ML applications, revealing opportunities to optimize between conceptual understanding and user engagement. These findings contribute to developing interactive ML systems/frameworks designed for a wide range of users. |
| title | TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2508.00252 |