Teachers' Perspectives on Teacher Self-Efficacy and Principal Leadership Characteristics
Bibliographic record
Abstract
The purpose of this study was to investigate how elementary teachers rate their level of self-efficacy and to examine the characteristics of school leaders influencing teacher self-efficacy, including when teachers worked from home during the COVID-19 school shutdown. On the Teachers’ Sense of Efficacy Scale (TSES), all 287 participating teachers rated their self-efficacy in the high or moderate range. On the Principal Rating and Ranking Scale (PRRS), teachers reported that Communication, Inspiring Group Purpose, Consideration, and Empowering Staff were the most important characteristics of leaders related to teacher self-efficacy. The teachers interviewed reported that Communication and Flexibility were their principals’ most supportive leadership characteristics during the COVID-19 school shutdown, and that areas for improvement were more Communication, Situational Awareness, and Modelling Instructional Expectations. This work gives district leaders a clearer understanding of practices, strategies, and behaviours they can implement to improve teacher self-efficacy, teacher practice, and student achievement.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".