Reviewing Emotional Intelligence Levels and Time Management Skills among Students of School of Physical Education and Sports
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aimed at exploring emotional intelligence levels and time management skills of students of school of physical education and sports (SPES) and assessing their emotional intelligence levels and time management skills in terms of some variables. 309 students who studied at SPES of Erciyes University during the 2017-2018 academic year participated in the study that was designed in screening model. In order to determine participant students’ emotional intelligence levels and time management skills; “Schutte Emotional Intelligence Scale”—Turkish adaptation of which was performed by Tatar, Tok, & Saltukoglu (2011) and Time Management Inventory—Turkish adaptation of which was performed by Alay & Kocak (2002) were used as data collection tools. In the study; Mann-Whitney U Test and Independent-Samples T Test were employed for paired comparisons while One Way Anova and Kruskal Wallis Test were used for multiple comparisons. For measurement of correlations, Pearson Correlation Analysis technique was used. According to study results, emotional intelligence levels and time management skills of students of school of physical education and sports were at “moderate level”. Students’ emotional intelligence levels differed significantly in terms of sex, academic grades and academic departments but not in terms of type of high school, sportive branch and age. Students’ time management skills did not change considerably in terms of age, sex, sportive branch, type of high school, academic grades and academic departments. Moreover, a positive and significant correlation existed between students’ emotional intelligence levels and time management skills.
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.
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 | 0.001 | 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 it