Measuring student motivation: how the formulation of a question affects a response
Analysis of the immediate impact of the applied methods on the work results. Survey, question formulation and wording. Motivation-measuring scales. The main results of the analysis that were carried out in order to test the main hypothesis of the study.
| Рубрика | Социология и обществознание |
| Вид | дипломная работа |
| Язык | английский |
| Дата добавления | 16.08.2020 |
| Размер файла | 2,0 M |
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Estimate Std.Err z-value P(>|z|)
.MTA2_rev 0.031 0.077 0.404 0.686
.MTA3_rev 0.640 0.077 8.291 0.000
.MTA4_rev 0.463 0.062 7.453 0.000
.MTA1_rev 0.559 0.063 8.859 0.000
.MTA5_rev 0.800 0.095 8.426 0.000
avoid 1.148 0.153 7.481 0.000
Model “Confidence” and “Support” combined - Positive questions
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lavaan (0.5-23.1097) converged normally after 35 iterations |
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Number of observations 148 |
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Estimator ML |
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Minimum Function Test Statistic 635.817 |
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Degrees of freedom 35 |
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P-value (Chi-square) 0.000 |
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Model test baseline model: |
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|
Minimum Function Test Statistic 2016.161 |
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Degrees of freedom 45 |
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|
P-value 0.000 |
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|
User model versus baseline model: |
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|
Comparative Fit Index (CFI) 0.695 |
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|
Tucker-Lewis Index (TLI) 0.608 |
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|
Loglikelihood and Information Criteria: |
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|
Loglikelihood user model (H0) -1267.033 |
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|
Loglikelihood unrestricted model (H1) -949.124 |
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Number of free parameters 20 |
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|
Akaike (AIC) 2574.066 |
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Bayesian (BIC) 2634.010 |
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Sample-size adjusted Bayesian (BIC) 2570.717 |
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|
Root Mean Square Error of Approximation: |
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RMSEA 0.341 |
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90 Percent Confidence Interval 0.318 0.364 |
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P-value RMSEA <= 0.05 0.000 |
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Standardized Root Mean Square Residual: |
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SRMR 0.080 |
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Parameter Estimates: |
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Information Expected |
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|
Standard Errors Standard |
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Latent Variables: |
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Estimate Std.Err z-value P(>|z|) |
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teacher =~ |
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|
TS-1 1.000 |
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TS-2 0.882 0.077 11.494 0.000 |
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TS-3 0.997 0.084 11.831 0.000 |
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TS-4 1.059 0.089 11.939 0.000 |
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TS-5 0.913 0.100 9.129 0.000 |
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|
CIT-1 1.025 0.105 9.738 0.000 |
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CIT-2 0.950 0.085 11.127 0.000 |
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CIT-3 0.934 0.084 11.117 0.000 |
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CIT-4 1.068 0.094 11.398 0.000 |
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CIT-5 0.845 0.089 9.533 0.000 |
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Variances: |
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|
Estimate Std.Err z-value P(>|z|) |
|||||
|
.TS-1 0.493 0.060 8.228 0.000 |
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|
.TS-2 0.126 0.017 7.457 0.000 |
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.TS-3 0.124 0.017 7.113 0.000 |
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|
.TS-4 0.127 0.018 6.964 0.000 |
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|
.TS-5 0.457 0.055 8.266 0.000 |
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|
.CIT-1 0.443 0.054 8.164 0.000 |
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|
.CIT-2 0.186 0.024 7.704 0.000 |
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|
.CIT-3 0.181 0.023 7.710 0.000 |
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|
.CIT-4 0.198 0.026 7.531 0.000 |
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.CIT-5 0.330 0.040 8.202 0.000 |
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|
teacher 0.608 0.116 5.254 0.000 |
Model “Performance” - Positive questions
|
lavaan (0.5-23.1097) converged normally after 26 iterations |
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|
Number of observations 148 |
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|
Estimator ML |
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|
Minimum Function Test Statistic 38.670 |
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|
Degrees of freedom 5 |
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|
P-value (Chi-square) 0.000 |
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|
Model test baseline model: |
|||||
|
Minimum Function Test Statistic 1004.871 |
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|
Degrees of freedom 10 |
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|
P-value 0.000 |
|||||
|
User model versus baseline model: |
|||||
|
Comparative Fit Index (CFI) 0.966 |
|||||
|
Tucker-Lewis Index (TLI) 0.932 |
|||||
|
Loglikelihood and Information Criteria: |
|||||
|
Loglikelihood user model (H0) -921.722 |
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|
Loglikelihood unrestricted model (H1) -902.388 |
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|
Number of free parameters 10 |
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|
Akaike (AIC) 1863.445 |
|||||
|
Bayesian (BIC) 1893.417 |
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|
Sample-size adjusted Bayesian (BIC) 1861.771 |
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|
Root Mean Square Error of Approximation: |
|||||
|
RMSEA 0.213 |
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|
90 Percent Confidence Interval 0.154 0.278 |
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|
P-value RMSEA <= 0.05 0.000 |
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|
Standardized Root Mean Square Residual: |
|||||
|
SRMR 0.018 |
|||||
|
Parameter Estimates: |
|||||
|
Information Expected |
|||||
|
Standard Errors Standard |
|||||
|
Latent Variables: |
|||||
|
Estimate Std.Err z-value P(>|z|) |
|||||
|
performance =~ |
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|
MTP-1 1.000 |
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MTP-2 1.168 0.071 16.525 0.000 |
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MTP-3 1.061 0.058 18.201 0.000 |
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MTP-4 0.839 0.052 16.102 0.000 |
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|
MTP-5 1.103 0.060 18.412 0.000 |
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|
Variances: |
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|
Estimate Std.Err z-value P(>|z|) |
|||||
|
.MTP-1 0.725 0.091 7.938 0.000 |
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|
.MTP-2 0.516 0.071 7.306 0.000 |
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.MTP-3 0.203 0.035 5.794 0.000 |
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.MTP-4 0.308 0.041 7.488 0.000 |
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|
.MTP-5 0.193 0.035 5.430 0.000 |
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|
performance 2.102 0.320 6.577 0.000 |
Model “Learning” - Positive questions
|
lavaan (0.5-23.1097) converged normally after 24 iterations |
|||||
|
Number of observations 148 |
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|
Estimator ML |
|||||
|
Minimum Function Test Statistic 22.230 |
|||||
|
Degrees of freedom 5 |
|||||
|
P-value (Chi-square) 0.000 |
|||||
|
Model test baseline model: |
|||||
|
Minimum Function Test Statistic 565.810 |
|||||
|
Degrees of freedom 10 |
|||||
|
P-value 0.000 |
|||||
|
User model versus baseline model: |
|||||
|
Comparative Fit Index (CFI) 0.969 |
|||||
|
Tucker-Lewis Index (TLI) 0.938 |
|||||
|
Loglikelihood and Information Criteria: |
|||||
|
Loglikelihood user model (H0) -865.138 |
|||||
|
Loglikelihood unrestricted model (H1) -854.023 |
|||||
|
Number of free parameters 10 |
|||||
|
Akaike (AIC) 1750.276 |
|||||
|
Bayesian (BIC) 1780.248 |
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|
Sample-size adjusted Bayesian (BIC) 1748.602 |
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|
Root Mean Square Error of Approximation: |
|||||
|
RMSEA 0.153 |
|||||
|
90 Percent Confidence Interval 0.092 0.220 |
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|
P-value RMSEA <= 0.05 0.005 |
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|
Standardized Root Mean Square Residual: |
|||||
|
SRMR 0.029 |
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|
Parameter Estimates: |
|||||
|
Information Expected |
|||||
|
Standard Errors Standard |
|||||
|
Latent Variables: |
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|
Estimate Std.Err z-value P(>|z|) |
|||||
|
learn =~ |
|||||
|
MTL-4 1.000 |
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|
MTL-1 0.590 0.050 11.759 0.000 |
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MTL-3 0.705 0.038 18.432 0.000 |
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|
MTL-2 0.389 0.053 7.329 0.000 |
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|
MTL-5 0.789 0.045 17.582 0.000 |
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|
Variances: |
|||||
|
Estimate Std.Err z-value P(>|z|) |
|||||
|
.MTL-4 0.350 0.061 5.776 0.000 |
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|
.MTL-1 0.496 0.062 7.946 0.000 |
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.MTL-3 0.161 0.029 5.555 0.000 |
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|
.MTL-2 0.651 0.078 8.386 0.000 |
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|
.MTL-5 0.254 0.041 6.193 0.000 |
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|
learn 1.800 0.251 7.182 0.000 |
Model “Avoidance” - Positive questions
|
Number of observations 148 |
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|
Estimator ML |
||||
|
Minimum Function Test Statistic 104.527 |
||||
|
Degrees of freedom 5 |
||||
|
P-value (Chi-square) 0.000 |
||||
|
Model test baseline model: |
||||
|
Minimum Function Test Statistic 556.447 |
||||
|
Degrees of freedom 10 |
||||
|
P-value 0.000 |
||||
|
User model versus baseline model: |
||||
|
Comparative Fit Index (CFI) 0.818 |
||||
|
Tucker-Lewis Index (TLI) 0.636 |
||||
|
Loglikelihood and Information Criteria: |
||||
|
Loglikelihood user model (H0) -876.426 |
||||
|
Loglikelihood unrestricted model (H1) -824.163 |
||||
|
Number of free parameters 10 |
||||
|
Akaike (AIC) 1772.852 |
||||
|
Bayesian (BIC) 1802.824 |
||||
|
Sample-size adjusted Bayesian (BIC) 1771.178 |
||||
|
Root Mean Square Error of Approximation: |
||||
|
RMSEA 0.367 |
||||
|
90 Percent Confidence Interval 0.307 0.430 |
||||
|
P-value RMSEA <= 0.05 0.000 |
||||
|
Standardized Root Mean Square Residual: |
||||
|
SRMR 0.143 |
||||
|
Parameter Estimates: |
||||
|
Information Expected |
||||
|
Standard Errors Standard |
||||
|
Latent Variables: |
||||
|
Estimate Std.Err z-value P(>|z|) |
||||
|
learn_avoid =~ |
||||
|
MTA-2 1.000 |
||||
|
MTA-3 1.073 0.075 14.267 0.000 |
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|
MTA-4 1.096 0.056 19.508 0.000 |
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|
MTA-5 -0.460 0.067 -6.849 0.000 |
||||
|
MTA-1 -0.167 0.087 -1.929 0.054 |
||||
|
Variances: |
||||
|
Estimate Std.Err z-value P(>|z|) |
||||
|
.MTA-2 0.294 0.042 7.016 0.000 |
||||
|
.MTA-3 0.481 0.062 7.711 0.000 |
||||
|
.MTA-4 -0.014 0.029 -0.488 0.626 |
||||
|
.MTA-5 0.593 0.069 8.609 0.000 |
||||
|
.MTA-1 1.078 0.125 8.605 0.000 |
||||
|
avoid 0.967 0.145 6.689 0.000 |
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