A Digital Model-Based Serious Game for PID-Controller Education: One-Axis Drone Model, Analytics, and Student Study

This paper presents a serious game designed to support the teaching of PID controllers. The game couples a visually clear Unity scene with a physics-accurate digital model of a drone with a single degree of freedom (called a one-axis drone) and helps prepare students to meet the demands of Industry 4.0 and 5.0. An analytics back-end logs system error at 10 Hz and interaction metrics, enabling instructors to diagnose common tuning issues from a plot and to provide actionable hints to students. The design process that led to choosing the one-axis drone and turbulence application via “turbulence balls” is explained, after which the implementation is described. The proposed solution is evaluated in a within-subjects study performed with 21 students from mixed technical backgrounds across two short, unsupervised tinkering sessions of up to 10 min framed by four quizzes of both general and theoretical content. Three questions shaped the analysis: (i) whether error traces can be visualized by instructors to generate actionable hints for students; (ii) whether brief, unsupervised play sessions yield measurable gains in knowledge or stability; and (iii) whether efficiency of tuning improves without measurable changes in tune performance. Results show that analysis of plotted error values exposes recognizable issues with PID tunes that map to concrete hints provided by the instructor. When it comes to unsupervised play sessions, no systematic pre/post improvement in quiz scores or normalized area under absolute error was observed. However, it required significantly less effort from students in the second session to reach the same tune performance, indicating improved tuning efficiency. Overall, the proposed serious game with the digital twin-inspired one-axis drone and custom analytics back-end has emerged as a practical, safe, and low-cost auxiliary tool for teaching PID controllers, helping bridge the gap between theory and practice.