مقاله درمورد 129، Formal، Personal، autonomy

ong the independent (i.e. predictor) variables of the study are not above .7, which demonstrates that the multicollinearity assumption is met.
Tables 4.46 to 4.48 also show that only the correlation coefficient between General autonomy and Expert teaching style is close to .3, and the rest of the predictor variables have an insignificant correlation with all autonomy scores. It is therefore, predicted that in the final results of regression, these insignificantly correlated predictor variables are not going to have significant contribution in terms of predicting autonomy. Nevertheless, the regression analysis was continued to observe which of these predictor variables would indeed have any prediction power in terms of different autonomy scores.

Table 4.46
General Autonomy Correlations

General autonomy
Expert
Formal authority
Personal model
Facilitator
Delegator
NLP
Pearson Correlation
General autonomy
1.000
.308
.156
.191
.292
.178
.088

Expert
.308
1.000
.716
.807
.718
.604
.281

Formal authority
.156
.716
1.000
.821
.689
.722
.392

Personal model
.191
.807
.821
1.000
.773
.667
.480

Facilitator
.292
.718
.689
.773
1.000
.769
.454

Delegator
.178
.604
.722
.667
.769
1.000
.452

NLP
.088
.281
.392
.480
.454
.452
1.000
Sig. (1-tailed)
General autonomy
.
.000
.038
.015
.000
.022
.160

Expert
.000
.
.000
.000
.000
.000
.001

Formal authority
.038
.000
.
.000
.000
.000
.000

Personal model
.015
.000
.000
.
.000
.000
.000

Facilitator
.000
.000
.000
.000
.
.000
.000

Delegator
.022
.000
.000
.000
.000
.
.000

NLP
.160
.001
.000
.000
.000
.000
.
N
General autonomy
129
129
129
129
129
129
129

Expert
129
129
129
129
129
129
129

Formal authority
129
129
129
129
129
129
129

Personal model
129
129
129
129
129
129
129

Facilitator
129
129
129
129
129
129
129

Delegator
129
129
129
129
129
129
129

NLP
129
129
129
129
129
129
129

Table 4.47
Curriculum Autonomy Correlations

Curriculum autonomy
Expert
Formal authority
Personal model
Facilitator
Delegator
NLP
Pearson Correlation
Curriculum autonomy
1.000
-.257
-.266
-.259
-.142
-.004
-.018

Expert
-.257
1.000
.716
.807
.718
.604
.287

Formal authority
-.266
.716
1.000
.821
.689
.722
.416

Personal model
-.259
.807
.821
1.000
.773
.667
.511

Facilitator
-.142
.718
.689
.773
1.000
.769
.464

Delegator
-.004
.604
.722
.667
.769
1.000
.439

NLP
-.018
.287
.416
.511
.464
.439
1.000
Sig. (1-tailed)
Curriculum autonomy
.
.002
.001
.002
.054
.480
.419

Expert
.002
.
.000
.000
.000
.000
.000

Formal authority
.001
.000
.
.000
.000
.000
.000

Personal model
.002
.000
.000
.
.000
.000
.000

Facilitator
.054
.000
.000
.000
.
.000
.000

Delegator
.480
.000
.000
.000
.000
.
.000

NLP
.419
.000
.000
.000
.000
.000
.
N
Curriculum autonomy
129
129
129
129
129
129
129

Expert
129
129
129
129
129
129
129

Formal authority
129
129
129
129
129
129
129

Personal model
129
129
129
129
129
129
129

Facilitator
129
129
129
129
129
129
129

Delegator
129
129
129
129
129
129
129

NLP
129
129
129
129
129
129
129

Table 4.48
Total Autonomy Correlations

Total
Autonomy
Expert
Formal authority
Personal model
Facilitator
Delegator
NLP
Pearson Correlation
Total
Autonomy
1.000
.191
.005
.051
.249
.207
.086

Expert
.191
1.000
.716
.807
.718
.604
.287

Formal authority
.005
.716
1.000
.821
.689
.722
.416

Personal model
.051
.807
.821
1.000
.773
.667
.511

Facilitator
.249
.718
.689
.773
1.000
.769
.464

Delegator
.207
.604
.722
.667
.769
1.000
.439

NLP
.086
.287
.416
.511
.464
.439
1.000
Sig. (1-tailed)
Autonomy
.
.015
.476
.281
.002
.009
.165

Expert
.015
.
.000
.000
.000
.000
.000

Formal authority
.476
.000
.
.000
.000
.000
.000

Personal model
.281
.000
.000
.
.000
.000
.000

Facilitator
.002
.000
.000
.000
.
.000
.000

Delegator
.009
.000
.000
.000
.000
.
.000

NLP
.165
.000
.000
.000
.000
.000
.
N
Autonomy
129
129
129
129
129
129
129

Expert
129
129
129
129
129
129
129

Formal authority
129
129
129
129
129
129
129

Personal model
129
129
129
129
129
129
129

Facilitator
129
129
129
129
129
129
129

Delegator
129
129
129
129
129
129
129

NLP
129
129
129
129
129
129
129

4.2.4.2. Assumption of Normality

Another assumption of multiple regression is the normality of the regression standardized residuals, which was checked via checking the Normal Probability Plot of the regression standardized residuals (Figures 4.4, 4.5 & 4.6). As shown in the figures, it can be said that the points have lain in an almost straight diagonal line from bottom left to top right without many deviations; therefore, it is assumed the assumption of normality of the regression standardized residuals is met for all the data.

Figure 4.4. The Normal Probability Plot of the Regression Standardized Residuals Dependent Variable: General Autonomy

Figure 4.5. The Normal Probability Plot of the Regression Standardized Residuals – Dependent Variable: Curriculum Autonomy

Figure 4.6. The Normal Probability Plot of the Regression Standardized Residuals Dependent Variable: Total Autonomy

4.2.4.3. Assumption of Homoscedasticity

Figure
s 4.7 to 4.9 also present scatter plots of the standardized residuals which indicate that there are only a few negligible outliers which have lain outside the rectangular cluster of the data in the center with regard to the large sample size in this study. Moreover, since there is a clear or systematic pattern to the residuals (e.g. curvilinear or higher on one side than the other) with very few deviations from a centralized rectangle, it is assumed that there is no violation of homoscedasticity in all the data for all the autonomy scores and the independent variables.

Figure 4.7. Scatterplot of the Standardized Residuals – Dependent Variable: General Autonomy

Figure 4.8. Scatterplot of the Standardized Residuals – Dependent Variable: Total Autonomy

Figure 4.9. Scatter Plot of the Standardized Residuals-Dependent Variable: Curriculum Autonomy

Tables 4.49 to 4.51 present the descriptive statistics for all the variables, and Tables 4.52 to 4.54 demonstrate what variables are going to be entered into the regression analysis. Since the literature suggested no order for entering the variables in the regression model and there was almost no logic for this issue, the method of regression was chosen to be simultaneous multiple regression analysis for all autonomy scores.
Table 4.49
Descriptive Statistics of General Autonomy, Styles and NLP

Mean
Std. Deviation
N
General autonomy
39.2248
5.24142
129
Expert
3.8117
.53063
129
Formal authority
3.6609
.57158
129
Personal model
3.8556
.64337
129
Facilitator
3.9002
.58887
129
Delegator
3.5530
.53970
129
NLP
143.5504
11.64847
129

Table 4.50
Descriptive Statistics of Curriculum Autonomy, Styles and NLP

Mean
Std. Deviation
N
Curriculum autonomy
16.8915
2.98758
129
Expert
3.8117
.53063
129
Formal authority
3.6609
.57158
129
Personal model
3.8556
.64337
129
Facilitator
3.9002
.58887
129
Delegator
3.5530
.53970
129
NLP
143.5504
11.64847
129
Table 4.51
Descriptive Statistics of Total Autonomy, Styles and NLP

Mean
Std. Deviation
N
Autonomy
56.1163
4.43112
129
Expert
3.8117
.53063
129
Formal authority
3.6609
.57158
129
Personal model
3.8556
.64337
129
Facilitator
3.9002
.58887
129
Delegator
3.5530
.53970
129
NLP
143.5504
11.64847
129

Table 4.52
Variables Entered/Removeda
Model
Variables Entered
Variables Removed
Method
1
NLP, Expert, Delegator, Formal authority, Facilitator, Personal modelb
.
Enter
a. Dependent Variable: General autonomy
b. All requested variables entered.
Table 4.53
Variables Entered/Removeda
Model
Variables Entered
Variables Removed
Method
1
NLP, Expert, Delegator, Formal authority, Facilitator, Personal modelb
.
Enter
a. Dependent Variable: Autonomy
b. All requested variables entered.

Table 4.54
Variables Entered/Removeda
Model
Variables Entered
Variables Removed
Method
1
NLP, Expert, Delegator, Formal authority, Facilitator, Personal modelb
.
Enter
a. Dependent Variable: Curriculum autonomy
b. All requested variables entered.

In Tables 4.55 to 4.57, the value given under the heading R Square indicates how much of the variance in the dependent variable (i.e. General, Curriculum and Total autonomy) is explained by the model (which includes the entered variables). In the case of General autonomy, the value is .139 which, expressed as a percentage, explains 13 percent of the variance in General autonomy. In the case of Total autonomy, the value is .184 which, expressed as a percentage, explains 18 percent of the variance in Total autonomy. Finally, In the case of Curriculum autonomy, the value is .175 which, expressed as a percentage, explains 17 percent of the variance in Curriculum autonomy.

Table 4.55
Model Summaryb (General Autonomy)
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.373a
.139
.097
4.98209
a. Predictors: (Constant), NLP, Expert, Delegator, Formal authority, Facilitator, Personal model
b. Dependent Variable: General autonomy

Table 4.56
Model Summaryb (Total Autonomy)
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.429a
.184
.144
4.10078
a. Predictors: (Constant), NLP, Expert, Delegator, Formal authority, Facilitator, Personal model
b. Dependent Variable: Autonomy

Table 4.57
Model Summaryb (Curriculum Autonomy)
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.418a
.175
.134
2.78016
a. Predictors: (Constant), NLP, Expert, Delegator, Formal authority, Facilitator, Personal model
b. Dependent Variable: Curriculum autonomy

To assess the statistical significance of the above results, it is necessary to look in Tables 4.58 to 4.60. The ANOVA tests the null hypothesis that multiple R in the population equals 0. As the results indicate, the model reaches statistical significance in all autonomy scores; therefore, all the predictor variables together make significant predictive contribution to the models.

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