Hi, I’m Michael Henry. During my REU program, my project focused on using a video game, Super Mario, to measure motor learning performance. The main objective was to develop and modify a Python game project to dynamically adjust the challenge level for users, based on their skill level. By increasing the number of sprites (enemies) as the user progresses through levels, I aimed to make the game more challenging, which would help establish an optimal challenge point for motor learning. The user’s performance was measured by how quickly they completed each level, with the completion time tracked within the game's code. Preliminary results showed how changes in difficulty affected the time taken to complete levels, providing insight into the user’s challenge level.