Impact of Demographic Variables in the Development of Teachers’ Self-Efficacy Beliefs in the Context of Saudi Arabia
Bibliographic record
Abstract
Teacher self-efficacy is one of the important variables to bring change in students’ learning. The current study aimed to assess teachers’ self-efficacy beliefs on four sub-scales; namely, classroom management, persistent behaviour, classroom anxiety and professional mastery, in the context of Saudi Arabia. The key objective of the study was to determine teachers’ self-efficacy beliefs on these sub-scales in relation to gender, age, professional qualification, level of teaching, and job experience. A random sample of 168 male and 106 female teachers was selected from two public and two private schools in Jeddah. A Teachers’ Self- Efficacy Beliefs scale developed by Shaukat (2011) was administered to collect data from teachers; the results for this study reported .89 overall reliability of the scale, .72 for classroom management, .73 for persistent behaviour, .66 for classroom anxiety and .76 for professional mastery. Data were analysed using the t-test and ANOVA to determine the impact of demographic variables on the four sub-scales of self-efficacy beliefs. Results showed significant differences between the self-efficacy beliefs of male and female teachers; BA, MA and PhD qualified teachers; primary and elementary and secondary school teachers; and public and private teachers with regard to classroom management, persistent behaviour, classroom anxiety and professional mastery. This study has possible implications for policy makers and teacher educators.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".