The Relationship between Critical Thinking and EFL Learners’ Speaking Ability
Bibliographic record
Abstract
<p>The current study sought to investigate the relationship between critical thinking and speaking ability among EFL students at Payame Noor University (PNU) of Rasht. This research concerned determining the fact that whether language students who are as critical thinker, perform better in their speaking ability or not. In order to answer the research question and test the hypothesis, 100 PNU English students were selected by applying IELTS speaking test as the samples of this study. Then in order to figure out critical and uncritical learners, Lauren Starkey Critical Thinking Test including 30-multiple choice item was administered to the participants. After that, based on the obtained data and due to lack of normal distribution, Spearman non-parametric correlation was employed. The findings of the current study revealed a significant correlation coefficient among these two major variables. In fact, those English learners who were recognized as critical thinkers performed better in their speaking.</p>
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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 | 0.000 | 0.006 |
| 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) | 0.004 | 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".