TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices

View at publisher
Authors: Wataru Kawabe, Hiroto Fukuda, Akihisa Shitara, Yuri Nakao, Yusuke Sugano
Cited by: 1
References: 41

Abstract

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 suggest that TofuML has the potential to enhance user engagement compared to 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.

Fields of Study & Subjects

Data Visualization and Analytics Human Motion and Animation Machine Learning and Data Classification

Publication details

Journal / source
International Journal of Human-Computer Interaction
Publisher
Informa UK Limited
Pages
1–27
Publication date
16 February 2026
Language
EN