An Investigation Regarding the Preservice Teachers’ Emotional Literacy Levels and Self-Efficacy Beliefs
Bibliographic record
Abstract
Self-efficacy beliefs and emotional literacy skills are considered as one of the most fundamental characteristics of teachers to create positive effects on students. The aim of this study is to investigate the relationship between preservice teachers’ self-efficacy beliefs and their emotional literacy levels. This study is designed as a relational survey model research. Study group consisted of 318 volunteer preservice teachers who are fourth graders at education faculty in a state university in the West of Turkey, in 2015-2016 academic year. Teacher Efficacy Scale, Emotional Literacy Scale and Personal Information Form were used to collect data. The results of this study are that according to the gender, there is a significant difference in favor of female preservice teachers in social competence subscale and total score of emotional literacy scale; according to the departments preservice teachers are educated, there is a significant difference in emotional awareness and emotional self-efficacy subscales of emotional literacy scale; on the basis of the gender, preservice teachers’ self-efficacy levels differ significantly in favor of female preservice teachers in teaching competency/external factors subscale and total score of the scale; according to the departments preservice teachers are educated, there is a significant difference in preservice teachers’ self-efficacy levels in teaching competency/external factors subscale; and finally there is a positive relationship between preservice teachers’ emotional literacy levels and their self-efficacy belief levels.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".