Effects of Principals’ Support on Teachers’ Self -Efficacy in Integrating e-learning in the Jordanian Discovery Schools
Bibliographic record
Abstract
This study examines the effect of perceptions of principals’ support of teachers in Jordan Discovery schools on the integration of e-learning into their teaching. 350 teachers were randomly stratified from a total of 2,389 teachers from all the secondary Discovery schools in the four districts (strata) of the capital, Amman. The dependent variable was the integration of e-learning. The independent variable was the perception on the Principals’ support needed for the integration of e-Learning and the moderating variable was the gender and teaching experiences. The responses from the survey were analyzed with descriptive statistics and two-way ANOVA. The findings of this study exhibit moderate levels of self-efficacy. From the perspective of self-efficacy, there were significant differences among the means for main effect for both teachers’ teaching experience and gender on the integration of e-learning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".