Application of Variance Analysis to Measure the Impact of STEM Methodology Components in an Educational Intervention

Authors

DOI:

https://doi.org/10.19153/cleiej.29.1.5

Keywords:

Data Science, STEM Education, Educational Data Analysis, Learning Impact Assessment

Abstract

This study presents the application of variance analysis (ANOVA) to evaluate the effectiveness of the STEM (Science, Technology, Engineering, and Mathematics) methodology in an educational intervention. The primary objective was to measure the learning impact per session and assess the influence of three key components: preparation time, teacher performance, and social interaction. The analysis revealed no statistically significant differences in the average learning rate per session, suggesting a consistent learning outcome above 75% throughout the intervention. However, notable differences emerged when examining the influence of specific components. Regarding preparation time, courses with extensive preparation achieved an average learning rate of 94.5%, in contrast to only 13.64% for sessions with immediate preparation. In terms of teacher performance, instructors who exceeded teaching expectations reached an average learning rate of 92.74%, while those demonstrating deficiencies resulted in only 11.25%. Finally, classrooms characterized by dynamic social interaction reported a 95.14% learning rate, compared to just 10.19% under minimal interaction conditions. These findings emphasize that the effectiveness of STEM methodology is significantly enhanced when supported by thorough preparation, high teaching quality, and active classroom engagement. The study highlights the value of pedagogical planning and collaborative learning environments in optimizing STEM-based education.

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Published

2026-03-13