<i>ML-Quest</i>: a game for introducing machine learning concepts to K-12 students

Owing to the predominant role of Machine Learning(ML) across domains, it is being introduced at multiple levels education, including K-12. Researchers have leveraged games, augmented reality and other ways make learning ML concepts interesting. However, most existing games teach either focus on use-cases applications instead core or directly introduce terminologies, which might be overwhelming school students. Hence, in this paper, we propose ML-Quest, a game incrementally present conceptual overview three concepts: Supervised Learning, Gradient Descent K-Nearest Neighbor (KNN) Classification. The has been evaluated through controlled experiment, for its usefulness player experience using TAM model, with 41 higher-secondary Results show that students experimental group perform better test than control group, 5% scoring full marks. none could score survey results indicate around 77% participants who played agree strongly ML-Quest made their interactive helpful introducing them concepts.