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Main Authors: Sydora, Viacheslav, Er, Guner Dilsad, Muehlebach, Michael
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.19376
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author Sydora, Viacheslav
Er, Guner Dilsad
Muehlebach, Michael
author_facet Sydora, Viacheslav
Er, Guner Dilsad
Muehlebach, Michael
contents This paper presents the web-based platform Machine Learning with Bricks and an accompanying two-day course designed to teach machine learning concepts to students aged 12 to 17 through programming-free robotics activities. Machine Learning with Bricks is an open source platform and combines interactive visualizations with LEGO robotics to teach three core algorithms: KNN, linear regression, and Q-learning. Students learn by collecting data, training models, and interacting with robots via a web-based interface. Pre- and post-surveys with 14 students indicate statistically significant improvements in self-reported understanding of machine learning algorithms, changes in AI-related terminology toward more technical language, high platform usability, and increased motivation for continued learning. This work suggests that tangible, visualization-based approaches can make machine learning concepts accessible and engaging for young learners while maintaining technical depth. The platform is freely available at https://learning-and-dynamics.github.io/ml-with-bricks/, with video tutorials guiding students through the experiments at https://youtube.com/playlist?list=PLx1grFu4zAcwfKKJZ1Ux4LwRqaePCOA2J.
format Preprint
id arxiv_https___arxiv_org_abs_2601_19376
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Teaching Machine Learning Fundamentals with LEGO Robotics
Sydora, Viacheslav
Er, Guner Dilsad
Muehlebach, Michael
Robotics
Artificial Intelligence
Computers and Society
Human-Computer Interaction
Machine Learning
This paper presents the web-based platform Machine Learning with Bricks and an accompanying two-day course designed to teach machine learning concepts to students aged 12 to 17 through programming-free robotics activities. Machine Learning with Bricks is an open source platform and combines interactive visualizations with LEGO robotics to teach three core algorithms: KNN, linear regression, and Q-learning. Students learn by collecting data, training models, and interacting with robots via a web-based interface. Pre- and post-surveys with 14 students indicate statistically significant improvements in self-reported understanding of machine learning algorithms, changes in AI-related terminology toward more technical language, high platform usability, and increased motivation for continued learning. This work suggests that tangible, visualization-based approaches can make machine learning concepts accessible and engaging for young learners while maintaining technical depth. The platform is freely available at https://learning-and-dynamics.github.io/ml-with-bricks/, with video tutorials guiding students through the experiments at https://youtube.com/playlist?list=PLx1grFu4zAcwfKKJZ1Ux4LwRqaePCOA2J.
title Teaching Machine Learning Fundamentals with LEGO Robotics
topic Robotics
Artificial Intelligence
Computers and Society
Human-Computer Interaction
Machine Learning
url https://arxiv.org/abs/2601.19376