The Critical Multicultural Education Competencies of Preschool Teachers
Bibliographic record
Abstract
<p>The aim of this study is to determine the perceptions of preschool teachers regarding critical multicultural education competencies. The study is based on “Critical Multicultural Education Competency Model”. The sample of this descriptive research consists of 120 teachers employed at 56 kindergartens and 24 independent nursery classes in the 2014-2015 academic year. The research data is obtained using the “Critical Multicultural Education Competency Scale” (CMECS), which was developed by the researcher. The scale development is carried out with 421 teachers employed in various positions and at different branches in the province of Istanbul. The construct validity is examined by applying exploratory factor analysis and it is found that the scale displays a four-factor structure. The scale, which consists of 42 items, is composed of four sub-dimensions, namely awareness, knowledge, skill and attitude, and the scale can be used as a one-dimensional structure as well. The eligibility of the Critical Multicultural Education Competency Scale (CMECS) for this study is analyzed by looking at the reliability with item analysis. An Alpha model is used for the reliability analysis of the items in the scale and of the sub-dimensions of the scale. As a result of the reliability analysis, which is applied to determine the suitability of the CMECS, it is found that the size of the reliability coefficients vary between 0.674 and 0.887. The reliability coefficient for the whole scale is calculated as .811. As a result of the research, it is determined that the preschool teachers find themselves adequate throughout the overall scale but only partially adequate in terms of knowledge and awareness. It is seen that the variables of gender, age, ethnicity and native language cause significant levels of differentiation in the perceptions of the teachers.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".