Effectiveness of "R" Simulation in Learning Random Variable Probability Distributions

This study examines the effectiveness of using R software simulation in learning random variable probability distributions. The research employed a quantitative method with two sample classes selected through clustered random sampling. Pretest analysis confirmed that both groups possessed equivalent initial conceptual understanding abilities. Data were analyzed using a t-test with a 5% significance level. The research instruments, including R programming scripts and conceptual understanding questions with their scoring rubrics, were validated as highly reliable by two validators, with average scores of 4.1389 and 4.0278, respectively. The experimental group was taught using R-based simulation, while the control group received conventional instruction. Post-test data analysis using a t-test at the 5% significance level led to the rejection of the null hypothesis. This indicates a statistically significant difference in the average conceptual understanding between the two groups. Based on the post-test means, the class using R simulation demonstrated significantly better conceptual comprehension compared to the conventionally taught class. In conclusion, R simulation proves to be an effective instructional tool that enhances students' conceptual grasp of random variable probability distributions.