A regression analysis was also run to explore the predictive power of thinking styles types in achievement motivation (Table 9). The model summary statistics contains the R value of 0.56 for multiple correlation coefficient of achievement motivation and components of thinking style. The square value of 0.31 indicates that the independent variable, thinking style, has the power to predict 31% of variations in achievement motivation.
As shown in Table 10, type II and type III of thinking styles are positive predictors of achievement motivation, while type I thinking styles is a negative predictor of achievement motivation(p>0.05). Based on the table, the Beta value is a measure of how strongly each predicator (independent) variable influences the criterion (dependent) variable. The Beta is measured in units of standard deviations. For example, a Beta value of 0.365 indicates that a change of one standard deviation in type III thinking styles will result in a change of 0.365 standard deviations in the students’ achievement motivation. Thus, the higher the Beta value, the greater the impact of the predictor variable on the criterion variable. In table 10, type III thinking styles as subconstructs of thinking styles have the most impact on the students’ achievement motivation. (P=0.365) Insurance regulation
To investigate possible effect of gender, age, major and their interactions on Iranian EFL learners’ thinking styles and achievement motivation, three way ANOVA with thinking styles and achievement motivation as dependent variables was run. The ANOVA analysis revealed a strong effect of gender and major interaction (F(2143)= 3.06, p <0.05, n2=0.041) on students thinking style (Table 11), as shown in Table
12, male students majoring in translation (M=116 ,SD=6.88) had lower scores in overall thinking styles than females (M=131 ,SD=4.05) while male students majoring in TEFL(M=135,SD=6.83) achieved higher scores in over all thinking styles than the females(M= 123,SD=5.33). Needless to mention, female students majoring in English literature (M=125, SD=4.25) had slightly higher thinking styles than male ones (M=124, SD=6.23). (Table 12)
The ANOVA analysis also showed no strong effect for gender (F(1143)= 0.42, p=0.83>0.05, П2=0.000); age (F(2,143)= 0.112, p=0.89>0.05, n2=0.002); major(F(2,143)= 0.48, p=0.61>0.05, n2= 0.007) ; gender and age interaction (F(2,i43)= 0.068, p=0.93>0.05, n2= 0.001); age and major interaction (F(4,143)=1.46, p=0.21>0.05, n2=0.039); gender, age and major interaction (F(3,143)= 0.33, p=0.80>0.05, n2=0.007); were observed.(Table 11)
Moreover, the ANOVA analysis revealed a strong effect of gender (Fq,143)= 4.32, p=0.03<0.05, n2=0.03) on students overall achievement motivation (Table 13), as male students (M=52 ,SD=1.7) had lower scores in overall achievement motivation than females (M=57 ,SD=1.16) (Table 14)
The ANOVA analysis also showed no strong effect for age (F(2,i43)= 1.31, p=0.27>0.05, n2=0.018); major(F(2,i43)= 0.14, p=0.86>0.05, n2= 0.002) ; gender and age interaction (F(2,143)= 0.42, p=0.65>0.05, n2=0.006); gender and major interaction (F(2,143)= 0.87, p= 0.41>0.05, n2=0 012);age and major interaction (F(4143)=1.67, p=0.16>0.05, n2=0 045); gender, age and major interaction (F(3143)= 2.32, p=0.78>0.05, П2=0.047); were observed. (Table 13)
Table 14. Descriptive Statistics of gender for achievement motivation