MANIPULATIVE MODEL UTILIZATION: UPSHOT IN THE PERFORMANCE OF SOLVING NORMAL DISTRIBUTION PROBLEMS

This study examined the use of physical and pictorial manipulatives in improving college students’ performance in solving normal distribution problems at Jose Rizal Memorial State University, Dipolog Campus. A quasi-experimental pretest–posttest design involving non-equivalent groups was employed using intact classes. The control group received traditional instruction, while the experimental group received instruction integrating physical and pictorial manipulatives. A researcher-made 50-item test, with a reported Kuder–Richardson Formula 20 coefficient of .89, measured achievement before and after four instructional sessions. A researcher-made test assessed students’ performance in selected areas of normal distribution before and after the intervention. Data were summarized using means and standard deviations and analyzed using z-tests and t-tests to examine differences within and between groups. Results revealed no statistically significant difference between the groups’ pretest performance, indicating comparable initial performance. Both groups demonstrated statistically significant improvements from pretest to posttest. Although the experimental group obtained a higher posttest mean and a larger descriptive gain, the overall difference in posttest performance between the groups was not statistically significant. These findings suggest that physical and pictorial manipulatives may support students’ learning of normal distribution concepts, but their superiority over traditional instruction was not established. Teachers may consider incorporating these resources based on instructional objectives and learners’ needs and may develop and implement an extension program for students. Further research should examine learning retention and the conditions under which manipulatives contribute to improved performance.