The Levels of German Teacher Trainers Working in Turkey Regarding Reigeluth’s Organizational Strategies
Bibliographic record
Abstract
The purpose of this study is to evaluate the views of German teacher trainers working in Turkey about their level regarding Reigeluth’s organizational strategies and to analyze their views in terms of gender, geographic region, seniority, and graduated high school variables. While the population of the study consisted of German teacher trainers working in the seven regions of Turkey in the 2014-2015 academic year, the sample of the study comprised 53 German teacher trainers who were selected voluntarily accepted to participate in the study. Data were collected through “Organizational Strategies of German Teacher Trainers Scale” developed by the researchers. As the Content Validity Index value (0.92) was larger than the Content Validity Criterion value (0.56), the items were expressed to be meaningful. The findings revealed the participants to have a high level of organizational strategies. The results regarding the variables were as follows: a) Gender difference was mostly observed favoring the male teachers, b) geographic region difference frequently appeared favoring the Marmara and Black Sea Regions, c) seniority difference was seen favoring the 16-20 year range, d) graduated high school difference was mostly observed as a statistically insignificant variable. In-service training programs encompassing all the regions of Turkey were suggested to be designed regularly and systematically for professional development of foreign language teachers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".