The Contribution of Emotional Intelligence and Achievement Motivation on Psychological Well-Being
Bibliographic record
Abstract
The purpose of this study was contribution of Emotional intelligence and achievement motivation on psychological well-being of students in the Shahr-e-Qods University. The statistical population of this study included all the students of University from 2015 to 2016. A sample of 200 students has been selected through cluster sampling. These students responded to a set of questionnaires included emotional intelligence (EI), achievement motivation, and psychological well-being. Hierarchical regression analyses conducted for each dependent variable showed that emotional intelligence and achievement motivation could be considered as important indicators of psychological well-being (p<0.01).The results indicated that achievement motivation can predict psychological well-being, and among emotional intelligence components, self-control and self-awareness can predict psychological well-being. As the results indicated, growth and promotion of the emotional intelligence can be considered as methods for improving students' psychological well-being. This can be promoted and revolted through a rich Educational Environment, so it is recommended to teach emotional intelligence skills to students with low psychological well-being through training workshops.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".