R Programming for Senior High School Quantitative Research: Its Influence on Students’ Data Analysis Performance and Anxiety

This paper discusses the influence and effectiveness of R programming on senior high school students’ data analysis performance and statistical anxiety. The data analysis using R was performed in RStudio – an integrated development environment for R. A pretest-posttest quasi-experimental control group design was employed in this study. During the intervention phase, the teacher employed R programming as the proposed strategy for the experimental group, where students performed data visualization, descriptive analysis, hypothesis testing, modelling, and data interpretation, as opposed to the conventional teaching method used in the control group. A delayed posttest was then administered to compare the data analysis performance and statistical anxiety of the control group and experimental group. One-way analysis of covariance (ANCOVA) revealed that there is a significant improvement in data analysis performance and a significant reduction in statistical anxiety among students in the experimental group as compared to students in the control group. The implications of this study will be useful for research educators, as R programming may be used to promote senior high school students’ data analysis performance in quantitative research.

Keywords: : data analysis performance, statistical anxiety, R programming

To cite: Gernel S. Lumacad, “R Programming for Senior High School Quantitative Research: Its Influence on Students’ Data Analysis Performance and Anxiety.” American Journal of Educational Research, vol. 13, no. 9 (2025): 471-424. doi: 10.12691/education-13-9-1.