Correlation between Students’ Self-Efficacy and Teachers’ Educational Leadership Style in Iranian Midwifery Students
Bibliographic record
Abstract
BACKGROUND: Self-efficacy is believe in and feeling of ability to complete work. One of these factors is educational teachers ' role. This study aimed to determine relationship between teachers' leadership style and students' self-efficacy in midwifery students. METHOD: This Study is a cross sectional correlation study. Sampling was conducted in midwifery students in Bachelor Science degree in 2013. Data collection tools were multi leadership questionnaire and self-efficacy clinical performance. After explaining the goals of study, 97 students completed the questionnaire. Scoring the questionnaire was based on a Liker's scale (0-5).Data were analyzed by SPSS 16. Correlation coefficient test was adopted to investigate the relationship and p value was considered 0.05. RESULT: Mean of self-efficacy scores were 116.12 (24.66.). In 53.3% of the cases, self-efficacy was good, in 42.2% moderate and in 4.3%, it was bad. The majority of the students (88.9%) reported that their teachers had an idealized style in leadership. About 94.6% of the students with good self- efficacy believed that their teachers' leadership style was transformational style. There was a significant correlation between self- efficacy and leadership style (p<0.05). CONCLUSIONS: Results showed that transformational style is appropriate for midwifery teachers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".