Emotional Self-Efficacy among A Sample of Faculty Members and Its Relation to Gender (Male/Female), Experience, Qualification, and Specialization
Bibliographic record
Abstract
The present study aimed to identify the level of emotional self-efficacy among a sample of faculty members who speak Arabic at the Abu Dhabi University. The study sample consisted of 99 faculty members Ph.D. and master’s holders from scientific, social and education and management and humanities disciplines in University branches: Abu Dhabi and AlAin. The Arabian version of the emotional self-efficacy scale standardized on the Emirati environment was applied which consists of 27 items distributed on four aspects: using and managing your own emotions, identifying and understanding your own emotions, dealing with emotions in others and perceiving emotions through facial expressions and body language.To detect the level of emotional self-efficacy the researcher calculated the arithmetic means, and deviations from the faculty member’s performance on the four scale aspects and the scale as a whole, the results showed a high level of emotional self-efficacy with faculty members who speak Arabic at the Abu Dhabi University. The study also found that there were no statistically significant differences at the level (0.05) or less between faculty members due to the variables gender (male/female), qualification, specialization, and years of experience. The researcher recommended the importance of academic community awareness of emotional self-efficacy and further studies on the subject of emotional self-efficacy in the light of other variables such as self-regulation and self-awareness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".