2026 ASEE Annual Conference & Exposition

High school computer science students often struggle to connect abstract probability concepts with real-world events and then to translate them into working code using random number generators. A combination of physical and digital instructional approaches helps students to develop a comprehensive understanding. However, existing approaches often incorporate only one method. This paper describes an integrated three-pronged approach to bridge the gap between theoretical probability and practical programming skills. A combination of physical simulations and online tools is used to connect theory directly to coding practice. Finally, gamification is used for assessment. Gamification provides an engaging way for students to demonstrate their understanding and receive immediate feedback, while leveraging the motivational benefits of game-based learning. Instructional effectiveness was evaluated using a multi-stage pretest and posttest and opinion survey. The pretest assessed students' initial understanding. Post-tests were given after the lecture and after the hands-on activities to measure learning gains. The opinion survey collected student feedback on the lesson's clarity, usefulness, and enjoyability. Results showed a 12% improvement in post-test scores, indicating a positive impact on learning. Furthermore, approximately 74% of students agreed or strongly agreed that the lesson improved their understanding of probability. The multi-stage assessment approach allows learning gains to be tracked at different stages of the learning process. The positive student feedback and improvement in test scores suggest that this integrated approach can be a valuable model for other educators seeking to enhance student understanding of probability and simulation in computer science.