Effectiveness of frequent testing over achievement: A meta analysis study

In current study, through a meta-analysis of 78 studies, it is aimed to determine the overall effect size for testing at different frequency levels and to find out other study characteristics, related to the effectiveness of frequent testing. 78 studies met the inclusion criteria out of 118 experimental and quasi-experimental studies in the potential study pool and 37 of them were journal articles, 21 doctoral dissertations, 14 master theses, and the rest were ERIC documents and conference papers. The newest study in the pool dated back to the year 2003. After the coding process, Hedges’ d effect size was calculated. The results were analyzed by SPSS and Meta Win. 233 effect sizes were calculated from 78 studies. Studies with similar exam frequency were categorized into three categories: low, medium, and high according to the frequency of the tests used in the study. According to the results, the cumulative mean effect size for 78 studies was .46. The results also indicated that there were not statistically significant differences between the mean effect sizes of the studies examine students at high, medium and low frequency levels. Overall, the findings indicated that frequent testing increases academic achievement. Also, the effectiveness of a set of categorical variables possibly related to the overall effect size for academic achievement is sought through Q statistic.In current study, through a meta-analysis of 78 studies, it is aimed to determine the overall effect size for testing at different frequency levels and to find out other study characteristics, related to the effectiveness of frequent testing. 78 studies met the inclusion criteria out of 118 experimental and quasi-experimental studies in the potential study pool and 37 of them were journal articles, 21 doctoral dissertations, 14 master theses, and the rest were ERIC documents and conference papers. The newest study in the pool dated back to the year 2003. After the coding process, Hedges' d effect size was calculated. The results were analyzed by SPSS and Meta Win. 233 effect sizes were calculated from 78 studies. Studies with similar exam frequency were categorized into three categories: low, medium, and high according to the frequency of the tests used in the study. According to the results, the cumulative mean effect size for 78 studies was .46. The results also indicated that there were not statistically significant differences between the mean effect sizes of the studies examine students at high, medium and low frequency levels. Overall, the findings indicated that frequent testing increases academic achievement. Also, the effectiveness of a set of categorical variables possibly related to the overall effect size for academic achievement is sought through Q statistic