Analyzing key features affecting user retention in game-based learning

In this study, we investigate crucial factors affecting engagement in game-based learning environment. As a measure, we used different classification algorithms including stacking model to classify user retention as early as possible in the game and analyzed important features selected by the classifiers. Having prior experience in digital games, plays significant role when classifying user retention in early stages. Additionally, we suggest balancing learning time and game time for effective design to further endorse continued learning.