The Impact of Self-Directed Learning Readiness on Critical Thinking and Self-Efficacy among the Students of the School of Physical Education and Sports
Bibliographic record
Abstract
The aim of this study was to examine the impact of self-directed learning readiness on critical thinking and general self-efficacy among the students of the School of Physical Education and Sports. In line with this aim, the research sample consisted of 419 students who were randomly selected from the School of Physical Education and Sports in Erciyes University. To collect data, the study used Self-Directed Learning Readiness Scale, Critical Thinking Scale, General Self-Efficacy Scale and 'Personal Information Form' created by the researcher.The data obtained through the Personal Information Form was statistically analyzed using SPSS 20.0 package program. The candidates' personal information and inventory total scores and factor points were presented by calculating frequency (f) and percentage (%) values. Pearson Moment Correlation Coefficient analysis (r) was performed to indicate the relationship between the points obtained from the scales while multiple regression analysis was performed to identify whether the points are predictor of each other. (β)The study found a positive significant relationship between self-directed learning readiness and critical thinking. A positive significant relationship was also found between self-directed learning readiness and general self-efficacy. Finally, there was a positive high relationship between general self-efficacy and critical thinking. The results of the study suggest that self-directed learning readiness affects critical thinking and general self-efficacy characteristics as it influences other aspects related to education. Self-directed learning readiness predicts critical thinking and general self-efficacy by 50.5%. Hence, authentic environments should be created to improve students' self-directed learning readiness when preparing education and training programs especially as a significant aspect of modern education systems in today's world.
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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 | 0.003 |
| 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) | 0.003 | 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".