Study the Impact of Employing Action Research on Middle School Teachers' Performance
Bibliographic record
Abstract
This research aims to study the impact of employing action research on middle school teachers' performance in district 3 education of Tehran in 2015 educational year. With regard to its aim, this study can be considered as an applied research and regarding the data collection method, it is a descriptive(ex post facto) research. The population of this study includes middle school teachers working in district 3 education of Tehran in 1394 educational year. A study sample of 100 individuals was selected through random stratified sampling method and divided into two groups of 50 teachers. Research tool was the organizational performance questionnaire by Hersey and Goldsmith (2003). This questionnaire was set up as a 5-point scale questionnaire and includes seven sub-scales(ability, clarity, assistance, encouragement, evaluation, validity and environment). Validity of instrument was determined by Goldsmith through content method and in this research content validity was used as well. In addition, reliability factor of the questionnaire is 87% which is calculated by Cronbach’s alpha. Data collected from questionaries was analyzed using independent T-tests and Manova in two different levels of descriptive and Inferential statistics. The results of the current research indicate that in general deploying action research affects performance of middle school teachers in district 3 education of Tehran. In secondary hypotheses using action research is effective considering ability, clarity, assistance, encouragement, evaluation, validity and environment while it has no effect on examining teachers’ performance. Besides, analyzing lateral findings of multivariate analysis of variance claims that in sample group's view, there is no significant difference between teacher’s performance divided by years of experience or levels of education.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".