An Investigation of the Psychometric Properties of Emotional Intelligence Scale Using Item Response Theory
Bibliographic record
Abstract
Students’ emotional intelligence represents an important variable that is connected to students’ academic achievementand life success. One main challenge when measuring students’ emotional intelligence is to have a valid and reliablemeasure that captures this emotional construct. The current study aims to investigate the psychometric properties of theArabic version of Alsmadoni emotional intelligence scale (AEIS-25) using item response theory (IRT) models. Thestudy was applied among 3030 students in grades 7-10 in Oman.Data model fit was examined through evaluating IRT assumptions (i.e. unidimensional assumption and localindependence assumption) and goodness of fit (i.e. items fit and persons fit). It was found that item parameters wereacceptable and satisfactory, which indicates the appropriateness of AEIS to examine emotional intelligence amongadolescents. Findings from exploratory factor analysis for 2924 students and for the remaining 24 items indicated thepresence of a 2-factor model since the third factor was loaded by only one item. AEIS was considered as a reliable andpotentially valid measure of trait emotional intelligence.
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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 | 0.016 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".