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Asia-Pacific Forum
on Science Learning and Teaching. Volume 10, Issue 2, Article 13 (Dec., 2009) |
In this study, the Teacher Disposition Index (TDI) questionnaire was distributed to primary school in-service teachers, as a descriptive study. After contacting teachers through face-to-face interaction, mail and email, 161 male and 251 female (total 412) teachers from 72 primary schools participated in the data collection process.
The TDI categorized in Student-Centered Subscale (S) of 25 questions and Professionalism, Curriculum-Centered Subscale (P) of 20 questions, was adapted from Schulte et al. (2002). During the adaptation process, guidelines for cross-cultural adaptation were used. Back-translation with bilingual test of the original English instrument, content and construct validity and inter-item correlation were done independently by three experts (Chapman & Carter, 1979). After this process, three experts decided on the Turkish version and then the pilot study and the questionnaire were applied. A five-point Lickert scale, ranging from 1, for strongly disagrees, to 5, for strongly agrees, was used. The TDI took approximately 15 minutes to complete.
There were found a significant correlation at 0.05 levels (2 tailed). The Kaiser-Meyer-Olkin (KMO) measures the sampling adequacy which should be greater than 0.5 for a satisfactory factor analysis to proceed. The KMO measure was 0.97 and the Bartlett's test of sphericity is significant (table 1).
Table 1: Conformation factor analysis:
Model
c2
df
c2 / df
Goodness of Fit Index (GFI)
Comparative Fit Index (CFI)
RMSEA
0.81
0.98
0.069
Normal value: P-Value for Test of Close Fit (RMSEA < 0.05) = 0.00
Its associated probability is less than 0.05. This means that the correlation matrix is not an identity matrix. Moreover, according to measuring the Cronbach alpha the reliability for the 20-questions regarding the professionalism/curriculum-centered scale was 0.94, and for the 25-item of student-centered questions was 0.95. These results gave us permission to continue with factor analyzing. While exploratory factor analysis is useful in revealing the empirical structure of TDI items, the confirmatory factor analysis (CFA) is a statistical technique that provides a means of assessing how well a proposed theoretical model fits a set of data by examining patterns of covariance in the data. The CFA specifies what TDI items load onto underlying factors (INTASC’s ten principles), and the relationship between these factors. CFA has GFI (goodness of fit) and CFI (comparative fit index) indicating how much better the INTASC’s ten principles (see appendix A) fits the data. Their values can range between 0 and 1 with higher values indicating a better fit. A value above .9 represents a reasonable fit. The RMSEA (root mean square error of approximation) is better conceived of as an index of inappropriateness of fit. If the RMSEA value is below .1 is good, it indicates a reasonable error of approximation (Browne and Cudeck 1993).
In this study, after factor analyzing, the TDI items were categorized into seven INTASC’s principles, which are 1, 2, 3, 5, 6, 7, and 9.
Copyright (C) 2009 HKIEd APFSLT. Volume 10, Issue 2, Article 13 (Dec., 2009). All Rights Reserved.
