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Record W2741858294 · doi:10.5539/ies.v10n8p145

Emotional Intelligence Levels of Students with Sensory Impairment

2017· article· en· W2741858294 on OpenAlexvenueno aff
Suhair M. Al-Tal, Fuad Eid Al-Jawaldeh, Heyam Al-Taj, Lina Maharmeh

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyEmpathyVisual impairmentEmotional intelligenceScale (ratio)Developmental psychologyValidityReliability (semiconductor)PsychometricsSocial psychology

Abstract

fetched live from OpenAlex

This study aimed at revealing the emotional intelligence levels of students with sensory disability in Amman in Jordan. The participants of the study were 200 students; 140 hearing impaired students and 60 visual impaired students enrolled in the special education schools and centers for the academic year 2016-2017. The study adopted the descriptive Approach. To achieve the goals of the study, the researchers prepared an emotional intelligence scale consisted of 30 items distributed into four fields: emotional knowledge, emotion regulation, empathy, and social efficiency. The scale’s reliability and validity were verified. Results showed that the total degree of the emotional intelligence of the students with hearing impairment was low and it was moderate for the students with visual impairment. Additionally, results revealed statistical significant differences between the students with hearing impairment and students with visual impairment in all the fields in favor of the students with visual impairment.The study confirmed the necessity to encourage people with sensory disabilities to take part in well-prepared activities and programs that allow them to express their emotions freely as drawing, acting, music and others to develop their emotional intelligence.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.427
GPT teacher head0.646
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

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