No abstract

No abstract

The current study examined gender differences in divergent thinking (DT) using meta-analyses of mean difference and variation. The main objective of the meta-analysis of mean difference was to resolve contradictory findings in the creativity literature regarding the prevalence of creativity among males or females in creative potential. The meta-analysis of variation aimed to test the greater male variability hypothesis (GMVH) in DT. To test gender differences in means (i.e., Hedges' g), results from 213 studies (k = 1,251; N = 115,289) were analyzed using a three-level approach. Females slightly outperformed males in DT, g = À.065, 95% CI [À.095, À.034], p = # .001. Three-level multiple regression analyses showed that the mean effect size significantly varied by (a) country, (b) DT subscale, (c) type of task, and (d) ability (gifted vs. nongifted). In the second meta-analysis, the GMVH in creative potential was tested by synthesizing the results of 1,152 effect sizes from 187 studies (k = 1,152; N = 101,328). The results confirmed the existence of greater male variability (GMV) in DT, (InVR) = 1.216, 95% CI [1.14, 1.29], p # .001, indicating 21.6% GMV in DT. Multiple regression analyses explained 29.82% of variability in the mean effect (InVR) at Level-2 (within-studies variance), and 5% of the variability in the mean effect at Level-3 (between-studies variance). The mean difference findings support the gender similarity hypothesis, while variation results tend to support the gender differences hypothesis. Limitations and recommendations for future studies are discussed.

No abstract

Problem finding (PF) and divergent thinking (DT) are considered to be indicators of creative potential. Previous studies, with different goals, suggest a positive correlation between PF and DT. However, none of these works have explicitly examined which index of DT is more associated with PF. The current investigation examined the association between PF and three main indexes of DT: fluency, flexibility, and originality. It also tested whether such a relation differs based on task nature (verbal vs. figural). The sample consisted of 90 sixth graders who completed three tests: (a) a verbal DT test, (b) a figural DT test, and (c) a PF test. Correlational analysis showed that flexibility was highly correlated with PF in the verbal DT test, whereas originality was significantly correlated with PF in the figural test. Results of the path analysis confirmed the results from correlational analyses and showed that verbal flexibility strongly predicted PF fluency, flexibility, and originality more than any other variable. Likelihood ratio test showed that using 1 or 3% cutoff for scoring originality did not significantly altered the results in both figural and verbal DT (vs. PF), while the likelihood ratio test showed significant differences between the figural and verbal DT. Finally, predictor variables in the verbal DT accounted for 40–58% of the variance in PF skills, whereas predictor variables in the figural DT accounted for 28–37% of the variance in PF skills. As suggested by experts in the field of PF, the role of flexibility in PF is a fertile area to be considered in future studies.