Self-Efficacy and Its Relationship with Social Skills and the Quality of Decision-Making among the Students of Prince Sattam Bin Abdul-Aziz University
Bibliographic record
Abstract
The present study aimed to reveal the self-efficacy and social skills and their relationship to the quality of decision-making at Prince Sattam bin Abdulaziz University students, and determine the extent of the contribution of self-efficacy and social skills to the quality of decision-making. To achieve this, a questionnaire was built to identify self-efficacy, and a questionnaire of social skills, and a questionnaire of decision- making.The study sample was (560) female students from the College of Education in Prince Sattam bin Abdul Aziz University, the study results indicated that the self-efficacy of the study sample was moderate and that the relationship between self-efficiency and social skills and the quality of decision-making was a positive.The findings revealed that the quality of decision-making interpreted about 81.5% of social skills, and it showed a positive statistically significant effect for the quality of decision-making on social skills, and the quality of decision-making interpreted about 69% of self-efficacy, and results also showed a statistically significant positive impact for the quality of decision-making on self-efficacy.
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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 | 0.003 |
| 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) | 0.002 | 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".