Activation Light Pattern: A Theoretical Approach to Teaching ReLU Activation through Gamification

<p><span lang="EN-US">Artificial Intelligence (AI) is becoming<span> </span>more and more applicable to education, yet the issue of how to introduce the complexity<span> </span>of<span> </span>machine<span> </span>learning<span> </span>to<span> </span>kids<span> </span>still exists. In this research, an interactive learning method with an application of game-based design, ”Activation Light Pattern,” for introducing activation functions to kids as part of neural networks’ Rectified Linear Unit (ReLU) is presented. The game is comprised of a sequence of neurons that are depicted as light bulbs and are activated based on a set threshold level so that children can anticipate patterns of activation and be given feedback. The application of the visual and interactive aspects is intended to<span> </span>maximize<span> </span>interest<span> </span>and<span> </span>understanding<span> </span>of AI concepts. The research assesses the methodology through experimental testing,<span> </span>quantifying<span> </span>learning<span> </span>retention and cognitive effect against con- ventional methods of teaching. Evidence indicates that<span> </span>gamified<span> </span>learning<span> </span>of<span> </span>AI<span> </span><span>enhances </span></span><span lang="EN-US">understanding and engagement with machine learning principles among children in a substantial way.</span></p>