Analisis Perbedaan Skor Pre-Test dan Post-Test pada Pembelajaran Bahasa Inggris Berbasis IoT dengan Uji Wilcoxon - Simamora, Tabita Paulina; Sianturi, Tiurmaida (Madani: Jurnal Ilmiah Multidisiplin, 2025)
The utilization of Internet of Things (IoT) technologies in the world of education opens up new opportunities in creating more adaptive, interactive, and data-driven learning. This study aims to analyze the differences in students pre-test and post-test scores after following English Language learning using IoT-based platforms. The data used was secondary data from the Kaggle platform, which loaded students learning outcome information, including pre-test scores, post-test scores, engagement levels, and device types used. The sample size in this study was 30 students. The approach used was a quantitative approach with One Group Pretest-Posttest Design. The normality test against the difference in scores was performed using the ShapiroWilk test and showed that the data were not normally distributed (0.0053). Therefore, the analysis proceeded with the Wilcoxon Signed-Rank test as a nonparametric test for two paired data. The test results showed there was a significant difference between the pre-test and post-test scores , with the median of the post-test score being higher (77) compared to the pre-test (67). Data visualizations in the form of histograms, QQ plots, boxplots, and scatters of individual plots were used to support the analysis results and interpretation. The results of this study show that IoT-based learning contributes to the improvement of students learning outcomes in English Language, so it is recommended as an alternative to technology-based learning strategies.