Assessing the effectiveness of the contextual teaching and learning model on students’ mathematical understanding ability: a meta-analysis study

Abstract

Abstract To date, in the literature, hundreds of studies have been found on mathematics learning that is supported by the Contextual Teaching and Learning (CTL) Model. Several studies with conflicting results are found in the literature. This meta-analysis study was carried out to combine and interpret the findings of this study. Related databases are sought for studies that qualify for examining the effects of CTL compared to conventional learning on students’ mathematical understanding abilities. Random-effect models with 95% confidence intervals (CIs) were estimated. 21 effect sizes were analyzed from 21 primary studies that met the inclusion criteria and were published in ERIC documents, journal articles, proceedings, and repository documents from 2010 to 2020, and with a total of 1349 students involved. The Comprehensive Meta-Analysis (CMA) program is used to assist analysis. Based on the results of the analysis found the overall effect size (ES) is 0.868 with a standard error of 0.155 based on a random-effects model. The size of the effect represents that the average student exposed to CTL exceeds the ability of mathematical understanding by 76% of students in conventional classes who are initially equivalent. This result can also be interpreted that, students shift from the 50th percentile to the 79th percentile in mathematical understanding abilities when CTL is applied. The results of the analysis of the mediator variables were found that all variables except the year of study and education level were related to ES. The strongest relationship was found for sample size variables and publication sources. The analysis shows that CTL is more effective if it is applied in the condition of a sample size of 1-30 students. It was found that there were sources of publications which tended to publish only significant studies, although they did not indicate publication bias. These facts are considered by mathematics education practitioners for CTL implementation in the future.