Teaching Artificial Intelligence and Machine Learning in Secondary Education: A Robotics-Based Approach

Abstract

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) highlights the need for innovative, engaging educational approaches in secondary education. This study presents the design and classroom implementation of a robotics-based lesson aimed at introducing core AI and ML concepts to ninth-grade students without prior programming experience. The intervention employed two low-cost, 3D-printed robots, each used to illustrate a different aspect of intelligent behavior: (1) rule-based automation, (2) supervised learning using image classification, and (3) reinforcement learning. The lesson was compared with a previous implementation of similar content delivered through software-only activities. Data were collected through classroom observation and student–teacher discussions. The results indicated increased student engagement and enthusiasm in the robotics-based version, as well as improved conceptual understanding. The approach required no specialized hardware or instructor expertise, making it easily adaptable for broader use in school settings.