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

Artificial Intelligence (AI) is becoming more and more applicable to education, yet the issue of how to introduce the complexity of machine learning to kids 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 maximize interest and understanding of AI concepts. The research assesses the methodology through experimental testing, quantifying learning retention and cognitive effect against con- ventional methods of teaching. Evidence indicates that gamified learning of AI enhances understanding and engagement with machine learning principles among children in a substantial way.