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Record W2973835321 · doi:10.5539/jel.v8n5p232

Examination of the Relationship Between Teacher Candidates’ Emotional Intelligence and Communication Skills

2019· article· en· W2973835321 on OpenAlexvenueno aff
Tuğba Cevriye Özkaral, Hasan Ustu

Bibliographic record

VenueJournal of Education and Learning · 2019
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsEmotional intelligencePsychologyTest (biology)Scale (ratio)Communication skillsSample (material)Mathematics educationSocial psychologyMedical education

Abstract

fetched live from OpenAlex

In this study, the relationship between teacher candidates’ emotional intelligence levels and communication skills was examined. It was examined whether there was a significant difference between teacher candidates’ emotional intelligence and communication skills, depending on gender and the departments they studied at. The research was designed in relational screening model. The universe of the research consists of teacher candidates, who are students at Necmettin Erbakan University Ahmet Keleşoğlu, Faculty of Education. In this universe, 326 teacher candidates were selected as the research sample. “Emotional Intelligence Scale” and “Communication Skills Inventory” were used to collect data. In the analysis of the data, one-way variance analysis and independent samples t-test, one of the parametric tests, were used. It is observed that there are low levels of positive relationship between teacher candidates’ communication skills and their emotional intelligence levels. No significant difference was found between teacher candidates’ emotional intelligence levels and communication skills regarding gender and department variables.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

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

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 head0.051
GPT teacher head0.369
Teacher spread0.319 · 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 teacher head, 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

Citations10
Published2019
Admission routes1
Has abstractyes

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