The Effectiveness of the Simulation-Based Learning Method in Improving Statistical Inferential Testing Abilities Using SPSS for English Students

Ahmad Zuhri Rosyidi; Mul Muliadi; Hazairin Alfian; Rizki Alawiya; Lalu Hasan Ashari

doi:10.61924/jasmin.v4i3.173

Authors

Ahmad Zuhri Rosyidi English Education Program of Institut Pendidikan Nusantara Global, Indonesia
Mul Muliadi English Education Program of Institut Pendidikan Nusantara Global, Indonesia
Hazairin Alfian Nasional University of Malaysia, Malaysia
Rizki Alawiya IAI Al-Manan NU Lombok Timur, Indonesia
Lalu Hasan Ashari Physical Education of Institut Pendidikan Nusantara Global, Indonesia

DOI:

https://doi.org/10.61924/jasmin.v4i3.173

Keywords:

Simulation-Based Learning (SBL), Inferential Statistic, SPSS

Abstract

This study investigates the effectiveness of Simulation-Based Learning (SBL) in improving students’ ability to conduct inferential statistical analysis using SPSS. The research employed a quantitative approach with a sample of 31 students, utilizing observation and testing as data collection methods. Statistical analysis was conducted through normality tests, homogeneity tests, and hypothesis testing. The results of the Kolmogorov-Smirnov and Shapiro-Wilk tests indicated that both pre-test and post-test data were not normally distributed (p < 0.05). Furthermore, Levene’s test revealed that the data did not meet the assumption of homogeneity of variances. Consequently, non-parametric analysis was applied using the Wilcoxon Signed Rank Test. The Wilcoxon test results showed a Z value of -4.794 with a significance level of 0.000 (p < 0.05), confirming a significant difference between pre-test and post-test scores. These findings demonstrate that SBL is effective in enhancing students’ statistical analysis skills, particularly in applying inferential tests through SPSS. Overall, this research provides empirical evidence that SBL is a powerful pedagogical approach for bridging theoretical knowledge and practical application in statistical learning, thereby equipping students with essential competencies for academic and professional contexts.

References

Cant, R. P., & Cooper, S. J. (2010). Simulation-based learning in nurse education: Systematic review. Journal of Advanced Nursing, 66(1), 3–15.

Cook, D. A., et al. (2011). Comparative effectiveness of instructional design features in simulation-based education. Medical Teacher, 33(11), 873–883.

Dasari, D., Hendriyanto, A., sahara, S., Ariawan, I. P. W., Muhaimin, L. H., & Pahmi, S. (2025). Crafting epistemic knowledge in statistics education via didactical engineering integrating the theory of didactical situations and the SECI model. Discover Sustainability, 6(1), 928.

Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE

Gravetter, F. J., & Wallnau, L. B. (2021). Statistics for the behavioral sciences (11th ed.). Cengage Learning.Publications.

Ghosh, S., & Mitra, J. (2020). Importance of normality testing, parametric and non-parametric approach, association, correlation and linear regression (multiple & multivariate) of data in food & bio-process engineering. In Mathematical and Statistical Applications in Food Engineering (pp. 112-126). CRC Press.

Hogg, R. V., Tanis, E. A., & Zimmerman, D. L. (2019). Probability and statistical inference (10th ed.). Pearson.

Howell, D. C. (2012). Statistical methods for psychology (8th ed.). Wadsworth, Cengage Learning.

Issenberg, S. B., et al. (2005). Features and uses of high-fidelity medical simulations that lead to effective learning: A BEME systematic review. Medical Teacher, 27(1), 10–28

Lateef, F. (2010). Simulation-based learning: Just like the real thing. Journal of Emergencies, Trauma, and Shock, 3(4), 348–352.

Mertler, C. A., Vannatta, R. A., & LaVenia, K. N. (2025). Advanced and multivariate statistical methods: Practical application and interpretation. Routledge.

Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). McGraw-Hill Education

Pudjiastuti, S. R. (2022). The role of statistics in research to improve critical thinking skills. JHSS (Journal of Humanities and Social Studies), 6(3), 417-422.

Rahma, Y. (2024). ANALISIS LEARNING OBSTACLE MATERI STATISTIKA PADA MATA KULIAH PEMBELAJARAN MATEMATIKA SMA/MA (Doctoral dissertation, UIN RADEN INTAN LAMPUNG).

Sa’idah, N., Jailani, Sudiyatno, & Retnawati, H. (2026). Innovative teaching models and critical thinking in mathematics and statistics education: A meta-analytical review. International Journal of Research in Education and Science (IJRES), 12(1), 140–157. https://doi.org/10.46328/ijres.5054

Siregar, A. A., Pasaribu, L. H., & Hasibuan, L. R. (2026). Pengaruh Problem-Based Learning terhadap peningkatan kemampuan berpikir kritis siswa pada materi statistika. Jurnal Nasional Pendidikan Matematika, 10(1), 45–56.

Stevens, J. P. (2013). Intermediate statistics: A modern approach. Routledge