Meta-Analysis of Findings Related to the Effect of Flipped Learning on Self-Regulation Strategies

This research was conducted to analyze the findings of the studies carried out about the effect of flipped learning on self-regulation strategies and combining their results. This research was conducted through meta-analysis and on 10 pieces of research that were conducted experimentally in the period from 2010 to 2022. To calculate the effect size, Hogg's g, fixed and random effects model, funnel plot diagram, Duval-Tweed correction, fitting test, and I2 and Q tests were used. Data analysis was done using CMA version 3 software. By adding only two studies to the sample, the distribution of meta-analysis studies will be symmetrical and the distortion caused by publication bias will be removed. Based on the results of the I2 and Q tests, the heterogeneity of the studies was confirmed. According to Hoggs’s g index, the effect size and Z calculated for 6 out of 10 studies are significant at the alpha level of 0.05, indicating that the flipped learning approach improves self-regulation skills. Also, the overall effect size is 0.711 in the fixed model and 0.989 in the random model and is significant at the alpha level of 0.05. The combination of the results of the conducted research showed the effect of the flipped learning approach on improving the skill of self-regulation strategies and their application.