Teaching Machine Learning Fundamentals with LEGO Robotics

TL;DR

This paper introduces an open-source, web-based platform using LEGO robotics to teach core machine learning algorithms to students aged 12-17 through engaging, visualization-based activities, demonstrating significant learning gains.

Contribution

It presents a novel, accessible approach combining robotics and visualizations to teach machine learning fundamentals to young learners, with evidence of improved understanding and motivation.

Findings

Significant improvement in students' understanding of ML algorithms.

High usability and engagement reported by students.

Platform effectively increases motivation for learning AI.

Abstract

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.