their individual goal setting? The hierarchical multiple regression analysis performed to
address the last research question yielded similar results as the previous research questions. Goal orientation was entered into SPSS initially to remove the variance it explains, which was 0%. The remaining variance explained by growth mindset and grit produced a correlational value of .18 and an R2 value that indicated the predictor variables explained 1.4% of the variance within the reading overall RIT achievement scores. The adjusted R2 was -0.3% demonstrating
essentially no explained variance when the number of predictors and sample size were adjusted. The standard error of the estimate was 8.56. The ANOVA test showed a non-significant finding with F (3, 174) = .81, p = .492. Growth mindset and grit do not explain a significant amount of variance within NWEA reading overall achievement for high ability students while controlling for time spent with students on their individual goal setting.
The final test conducted in SPSS was completed to determine the significant amount of variance that growth mindset and grit have on high ability students’ NWEA math scores while
controlling for time spent with students on their individual goal setting. Once again, goal orientation was entered into SPSS first. A correlational value of .07 was obtained showing a very small relationship between the goal orientation composite score and the high ability students’ NWEA math achievement scores. The R2 indicated that only 0.4% of the variance in the math RIT scores were being explained by the goal orientation composite score. The adjusted
R2 was -0.5%. When removing the goal orientation variable to determine explained variance left
within the model, growth mindset and grit did not produce significant results. The R2 value explained 1.5% of the variance of the criterion variable, which produced a 1.1% change. This is a non-significant correlation with high ability students’ NWEA math achievement scores. The standard error of the estimate for growth mindset and grit was 10.50 over the amount of
explained variance that goal orientation achieved. The ANOVA results confirmed non-
significance with F (3, 107) = .55, p = .652. Growth mindset and grit do not explain a significant amount of variance within math overall achievement for high ability students while controlling for time spent with students on their individual goal setting.
Emerging data and the inferential findings. After looking at the descriptive data found earlier in this chapter, two emerging findings arose in addition to the findings regarding my research questions. It became evident that there was quite a difference between the males and females in their math composite scores. The other noticeable difference was school setting seemed to play a role on growth mindset in which the suburban setting was higher than the rural setting. Because these differences appeared evident, I decided to statistically test those two emerging findings. For the first test regarding gender, an independent samples t-test was
performed. This was done because there were only two levels on the independent variable: male and female. For the test focusing on school setting compared to growth mindset, a one-way
ANOVA was run because there were three levels on the independent variable: rural, suburban, and urban. With three levels on the independent variable, this would result in three different comparisons needed: urban versus suburban, urban versus rural, and suburban versus rural.
As mentioned, an independent samples t-test was conducted to determine whether significant differences exist on math composite scores based on the gender of the participant. The assumption of homogeneity of variance was determined by a Levene’s Test for Equality of Variances and met with p = .77. The assumption of normality was met with non-significant Shapiro Wilks test, p > .05. The dependent variable scores within this question were only in one level of the independent variable. In other words, every math score used was either a male’s score or a female’s score; there was no duplication.
The males’ math composite score (M = 23.80, SD = 10.31) was significantly higher than the females’ math composite score (M = 18.68, SD = 10.06). This is evident with a significant independent samples t-test with t (109) = 2.63, p = .01, two-tailed. High ability male students significantly outperformed the female students who participated in this study.
The other noticeable finding in the descriptive data pertained to school setting and its potential comparison to growth mindset composite scores. To further examine how school
setting possibly compared to growth mindset composite scores, the one-way ANOVA test was
run. I ran this statistical test so it can be determined whether the differences seen in the descriptive data are due to chance or a significant difference does exist.
The assumption of homogeneity of variances was violated with a significant Levene’s Test of Homogeneity of Variances, with F (2, 177) = 3.26, p = .041. The one-way ANOVA is robust to the violation of assumption of homogeneity of variances, but to accommodate for such a violation, the Games-Howell test was utilized to interpret any significant findings. The Games-
Howell post hoc test does not assume equal variances among the dependent variable scores on level of the independent variable.
The one-way ANOVA produced statistically significant data as F (2, 177) = 6.6, p = .002. To determine which groups within the one-way ANOVA were significant, the Games- Howell output was examined due to the violation of assumption of homogeneity of variances. The students in a suburban setting (M = 4.16, SD = .56) scored significantly higher than those students in a rural setting (M = 3.76, SD = .74). The mean difference was significant with p = .001. That is, those students in a suburban setting exhibited significantly higher levels of growth mindset than those students in a rural school setting in this particular study.
Summary
The descriptive statistics presented in this chapter appear to have demonstrated students in grades 4 through 8 have the propensity of a growth mindset as revealed by the growth mindset composite mean scores for each grade level. It appears the growth mindset composite scores decreased as the grade level increased. Unfortunately, when I attempted to run an inferential statistical analysis, I was unable to do so because the samples sizes per grade level were not conducive to such testing. When considering gender, it appears males tended to have higher values on the growth mindset composite scores more than females. These data were found significant through inferential statistical analysis. The students in the suburban school setting displayed the highest growth mindset mean and that mean was also higher than the whole
sample. Significant findings through inferential statistical testing showed students in a suburban school setting displayed higher levels of growth mindset than those students in a rural school setting.
The inferential data directly related to my research questions did not present significant findings. Neither growth mindset nor grit explained a significant amount of variance on high ability students’ academic achievement when controlling for teacher feedback, self-regulation, or goal orientation. However, it should be noted that when controlling for self-regulation, the ANOVA test indicated a significant amount of variance was removed based on self-regulation for NWEA reading achievement scores. This will be discussed more in Chapter Five.
Additionally, Chapter Five will discuss the findings in this chapter and how they relate to the review of literature, practical implications, and recommendations for future research.
CHAPTER FIVE