“A Compliment is all I need” – Teachers Telling Principals How to Promote Their Staff's Self-Efficacy
Bibliographic record
Abstract
The purpose of the present study is to compare the perceptions of teachers representing opposite ends of the self-efficacy spectrum regarding the effects of the principal’s behavior on their professional self-efficacy. In the first quantitative stage, a statistical procedure was conducted to identify the two groups of teachers: a group of 16 teachers with a high self-efficacy and a group of 14 teachers with a low self-efficacy. In the second and main stage, the qualitative stage, the teachers were asked about their professional successes and failures, using in-depth, open-ended interviews. Data were analyzed using grounded theory. Five categories of management style were found pertinent to both groups: modes of communication, feedback from the principal, social atmosphere, strength of the principal, and shared values. Differences found between the two participant groups regarding each management style category are discussed. Findings also indicate that the human aspect of teacher-principal relations is the decisive factor determining those teachers’ sense of professional self-efficacy. L’objectif de la présente étude est de comparer des perceptions d’enseignants quant à l’effet du comportement du directeur d’école sur leur auto-efficacité professionnelle. Les perceptions recueillies représentent les extrémités opposées du spectre. Pendant la première étape quantitative, on a identifié les deux groupes d’enseignants par une procédure statistique : un groupe de 16 enseignants jouissant d’une grande auto-efficacité et un groupe de 14 enseignants avec un faible degré d’auto-efficacité. Pendant l’étape principale, la deuxième et qualitative cette fois, nous avons interrogé les enseignants sur leurs réussites et leurs échecs professionnels par le biais d’entrevues approfondies à questions ouvertes. Les données ont été analysées conformément à la théorie reposant sur les faits. Les résultats ont révélé cinq catégories de style de gestion, applicables aux deux groupes : modes de communication, rétroaction du directeur, ambiance sociale, autorité du directeur et valeurs partagées. Nous discutons des écarts entre les deux groupes par rapport aux styles de gestion. Les conclusions ont également indiqué que l’aspect humain du rapport enseignant-directeur est le facteur déterminant dans le sentiment d’auto-efficacité professionnelle chez les enseignants.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 0.001 |
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".