The Use of Experimental Statistical Analysis to Enhance Understanding of Variable Relationships in Science Learning

Abstract

This study investigates the use of experimental statistical analysis as an instructional approach to enhance students’ understanding of variable relationships in science learning. Many students tend to memorize experimental results without comprehending the underlying relationships between variables, resulting in limited analytical reasoning and superficial understanding. To address this issue, the present study explores how integrating basic statistical tools-such as mean, correlation, and regression-into experimental activities can strengthen conceptual comprehension, analytical reasoning, and scientific literacy. Grounded in constructivist and inquiry-based learning frameworks, the research emphasizes active engagement, where students participate in data collection, analysis, and interpretation to draw evidence-based conclusions. The study employed a quasi-experimental design involving science students divided into experimental and control groups. Both groups conducted similar laboratory experiments, but only the experimental group received explicit instruction in statistical analysis. Data were collected through pre-tests and post-tests to measure changes in students’ understanding of variable relationships. The results indicated a 25% improvement in the experimental group’s comprehension and reasoning ability compared to the control group. Students who applied statistical analysis demonstrated greater proficiency in interpreting data, identifying causal patterns, and connecting theoretical knowledge to experimental findings. In contrast, students taught through traditional narrative-based instruction showed minimal gains and relied heavily on memorization. The findings highlight the effectiveness of integrating statistical reasoning in promoting critical thinking, problem-solving, and scientific reasoning skills.