AI Summary & Key Takeaways
AI InsightIt aims both to present an overall correlation effect size and to identify potential moderators for variation across studies.
📌 3 Key Takeaways
Abstract
This meta-analysis examines the correlation between academic self-efficacy and academic procrastination by synthesizing findings from primary studies. It aims both to present an overall correlation effect size and to identify potential moderators for variation across studies. The study is significant as it not only provides a general effect size but also explores moderator variables that may account for differences in outcomes. Journal articles, theses, and conference papers were reviewed through multiple search engines, and studies meeting the inclusion criteria were analyzed. Studies were included if a Pearson correlation coefficient between academic self-efficacy and academic procrastination was reported in an educational context, reported in Turkish or English. Forty-four primary studies reporting Pearson correlation coefficients (r) were included, representing a total sample of N = 18,330 participants. Alongside the overall effect size, analyses of publication bias and heterogeneity were carried out. There was no evidence of publication bias when it was evaluated using a variety of complimentary techniques, such as funnel plot, Begg & Mazumdar’s rank correlation test, Egger’s regression test, and Rosenthal’s fail-safe N method. Using the random effects method, the mean effect size was moderate and negative (r ̅ = −.37, 95% CI: [−.414, −.317]). Heterogeneity tests indicated significant variability across primary studies (I² = 93.03%), suggesting that moderator analyses were warranted. Among potential moderators, publication year, the proportion of female participants, and publication type did not exhibit a moderating effect, while study country and educational level significantly moderated the relationship. These factors demonstrated a moderate effect on the self-efficacy–procrastination link.