Relationship between Academic Optimism and Classroom Management Styles of Teachers—Case Study: Elementary School Teachers in Isfahan
Bibliographic record
Abstract
The purpose of this study was to investigate the relationship between classroom management styles of the teachers and their academic optimism. In this study, three types of classroom management styles (interventionist style, interactionist style, and non-interventionist style) have been considered. Research community is all public primary school teachers in the Isfahan province in academic year 2014-2015. The sample size was calculated using the formula of Cochran 384. It is a multi-stage cluster sampling method. Classroom management style has been calculated using standard questionnaires of classroom management style of Wolfgang and Glickman (1986). The academic optimism variable was evaluated using academic optimism questionnaire of A. Hoy, Tarter, and W. Hoy (2006) in a sample of 384 teachers. The results showed that there is a significant relation between classroom management style of the teachers and their academic optimism and the correlation coefficient equal to 39% was obtained and the correlation coefficient of 47% was obtained between the academic optimism and non-interventionist classroom management, and the correlation coefficient of 43% was obtained between the academic optimism and interactionist classroom management, and the correlation coefficient of 24% was obtained between the academic optimism and interventionist classroom management that is significant.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".