The Development of Emotional Quotient Evaluation for Thai University Students
Bibliographic record
Abstract
In this study, we designed an evaluation form to assess the emotional quotient of Thai university students. The indicators and components of the evaluation were developed from theories and principles regarding emotional intelligence. After the process of content validity assessment, the evaluation consists of 80 indicators in 5 components of Self-awareness, Self-regulation, Self-Motivation, Recognizing Emotions in Others, and Social Skills. In detail, the evaluation was found to have an index of congruence (IOC) of 0.50-1.00, discrimination of 0.472-0.817, and reliability of 0.991. It was later tested for construct validity with 200 Thai university students selected by stratified sampling method. The method of confirmatory factor analysis was employed. The results of the study indicate the evaluation construct validity as the goodness of fit indices passed the criteria and the evaluation model fits the empirical data. Chi – Square = 87.436, df = 73, Chi-Square /df = 1.197, p-value = 0.119, CFI = 0.997, TLI = 0.995, RMSEA = 0.031, and SRMR = 0.021.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".