Educational Game

Educational games are increasingly used to enhance learning, with research focusing on optimizing their design and impact. Current studies employ machine learning models, such as neural networks and ensemble methods, to analyze gameplay data, predict student performance, and personalize learning experiences. Researchers also utilize techniques like Shapley values to interpret game strategies and cluster analysis to understand player behaviors, informing iterative game design improvements. This work contributes to a more data-driven approach to educational game development, leading to more effective and engaging learning tools.