The effect of learning cycle models on students' science achievement: A meta-analysis study

This study aims to investigate how effective the learning cycle models are in science education compared to traditional teaching methods in enhancing students' science achievement. To achieve this goal, findings from relevant primary studies were synthesized using the meta-analysis method, and the overall effect size for the dependent variable, "science achievement," was calculated. In addition, moderator analyses were conducted based on study characteristics to examine whether the overall effect of learning cycle models varied according to these moderators. Within this scope, a comprehensive literature search was carried out in databases including the National Thesis Center, EBSCOhost, Web of Science, Scopus, TR Dizin, and DergiPark, resulting in the identification of many studies conducted in the field of science education. The studies obtained from the literature search were evaluated based on predetermined inclusion criteria. As a result, 123 primary studies were included in the meta-analysis, with 127 reported effect sizes. In the analysis phase, Hedge's g was used as the effect size metric, and the random-effects model was chosen for estimating the overall effect size. The overall effect size was calculated as g = 1,121 (95% CI [0,963, 1,279]; k = 123; p < ,001). This value indicates that the use of learning cycle models has a large effect on students' science achievement. Moderator analyses revealed that the model remains consistently effective across most contexts. However, it was also found that certain factors, such as educational level, subject matter, teacher effect, and researcher effect, should be carefully considered during implementation. In summary, this meta-analysis provides strong evidence that the use of learning cycle models in science teaching is an effective method for enhancing students' achievement and promoting deeper learning compared to traditional instructional methods.