Page 69 - Volume 4 - Issue 1 - DBU Journal of K-12 Educational Research

Journal of K-12 Educational Research 67 the prediction of the dependent variable. The F -test was used to assess whether the set of independent variables collectively predicts the dependent variable. R -squared, the multiple correlation coefficient of determination was reported and used to determine how much variance in the dependent variable can be accounted for by the set of independent variables. The researcher ran descriptive correlational analysis using the recommended .05 significance level to determine if the significance of the predictor variables contributes to the independent variable for each of the null hypotheses. Findings were organized by research question with separate analyses for each of the six STAAR scores, representing the dependent variable. A non-significant regression was found for third grade math [ F (2, 148) = 1.765, p > .05, R 2 = 0.023 (2.3%), fourth grade math [ F (2, 143) = 0.627, p > .05, R 2 = 0.009 (0.9%), and fifth grade math [ F (2, 143) = 0.671, p > .05, R 2 = 0.009 (0.9%). Table 1 displays the results from the multiple regression analysis and analysis of variance conducted with Grades 3-5 STAAR math. A multiple regression analysis was conducted with third, fourth, and fifth grade STAAR reading scores as the criterion variable and principal overall experience and principal experience in the district as the predictors. A statistically significant regression was found for third grade reading [ F (2, 147) = 3.791, p < .05, R 2 = 0.049 (4.9%). A non-significant regression equation was found for fourth grade reading [ F (2, 143) = 1.831, p > .05, R 2 = 0.025 (2.5%), and fifth grade reading [ F (2, 144) = 0.005, p > .05, R 2 = 0.000. Table 2 displays the results from the multiple regression analysis and analysis of variance conducted with Grades 3-5 STAAR Reading. It was found that neither principal’s experience or principal’s experience in the district predicted math and reading STAAR scores. There was a combined significant impact ( p = 0.025) for third grade STAAR reading scores due to principal experience with the district ( β = 0.100). Discussion & Implications The focus of the current study was to examine the predictive relationship between charter school principal longevity and student achievement. The current study is important because it provides empirical data to an otherwise limited research area. The current study is the first of its kind to examine the impact of charter school principal experience and retention on state assessment results. in the district as the predictors. A statistically significant regression was found for third grade reading [ F (2, 147) = 3.791, p < .05, R 2 = 0.049 (4.9%). A non-significant regression equation was found for fourth grade r ading [ F (2, 143) = 1.831, p > .05, R 2 = 0.025 (2.5%) and fifth g ade reading [ F (2, 144) = 0.005, p > .05, R 2 = 0.000. Table 2 displays the results from the multiple regression analysis and analysis of variance conducted with Grades 3-5 STAAR Reading. Table 2 Model Summary/ANOVA: STAAR Reading R R 2 Adjusted R 2 Std. Error of the Estimate F Sig. Grade 3 .221 0.049 0.036 13.378 3.791 .025 Grade 4 .158 0.025 0.011 14.826 1.831 .164 Grade 5 .008 0.000 -0.014 11.174 0.005 .995 It was found that neither principal’s experience or principal’s experience in the district predicted Table 2. Model Summary/ANOVA: STAAR Reading (0.9%). Table 1 displays the results from the multiple regression analysis and analysis of variance conducted with Grades 3-5 STAAR math. Table 1 Model Summary/ANOVA: STAAR Math R R 2 Adjusted R 2 Std. Error of the Estimate F Sig. Grade 3 .153 0.023 0.01 14.484 1.765 .175 Grade 4 .096 0.009 -0.005 14.198 0.672 .512 Grade 5 .096 0.009 -0.005 9.792 0.671 .513 A multiple regression analysis was conducted with third, fourth, and fifth grade STAAR reading scores as the criterion variable and principal overall experience and principal experience Table 1. Model Summary/ANOVA: STAAR Math