The factors associated with teachers’ job satisfaction and their impacts on students’ achievement: a review (2010–2021)
Bibliographic record
Abstract
Abstract The success of any educational organization depends heavily on the effectiveness of its teachers, who are tasked with transferring knowledge, supervising students, and enhancing the standard of instruction. Teachers’ job satisfaction has a significant impact on the lessons they teach since they are directly involved in transferring knowledge to students. In order to determine the effect of teachers’ job satisfaction (TJS) on students’ accomplishments, the researchers sought to analyze the empirical studies conducted over the previous 12 years (SA). To determine the characteristics that link to instructors’ job satisfaction and their effect on students’ achievement, thirty-two empirical studies were examined. The analysis of world-wide empirical research findings shows four types of results: (i) In some countries, teachers’ job satisfaction is low, but students’ achievement is high (Shanghai, China, South Korea, Japan, Singapore) (ii) In some countries, teacher job satisfaction is high, but student achievement is low (Mexico, Malaysia, Chile, Italy). (iii) In some countries, teachers’ job satisfaction is high, and so is student achievement (Finland, Alberta, Canada, Australia). (iv) In some countries, teacher job satisfaction is low, which has a negative impact on student achievement (Bulgaria, Brazil, Russia). In sum, irrespective of countries, highly satisfied teachers give their best to their students’ success, not only by imparting knowledge but also by giving extra attention to ensure the better achievement of each student. The review of this study makes it even more worthwhile to reflect on the need to avoid stereotypical considerations and assessments of any objective presentation of the phenomenon and to reflect more deeply on the need to assess the validity of the relationship study.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".