Conceptions of Critical Thinking from University EFL Teachers
Bibliographic record
Abstract
Critical Thinking has become an educational and social ideal. English as a Foreign Language (EFL) teaching has not been apart from the discussion on the importance of implementing Critical Thinking into the educational process. However, research on Critical Thinking has broadly been carried out in other fields of knowledge rather than in EFL. Therefore, this study aimed to comprehend the conceptions university English teachers had about Critical Thinking in order to get a wider understanding on the way it has been conceived in EFL in relation to its concept, traits, promotion and assessment. Content Analysis, as a qualitative process of analysis and source of information, interpretations and conclusions, was the method adopted. The software Atlas.ti was the tool implemented to analyze the information. The results revealed that there is some agreement on the conception of Critical Thinking as a set of cognitive skills for problem-solving and reflective learning. Nevertheless, EFL teachers brought about their deficiency in understanding on what Critical Thinking entails. Thus, they emphasized the need of training on topics such as teaching, learning, didactics, methodology, strategies and resources to foster Critical Thinking in EFL. Based on teachers’ participation in this study and the literature consulted, it was concluded that Critical Thinking in EFL is compound of communicative competence, creativity, argumentation, problem-solving, decision-making, autonomous learning, metacognition and emotions.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".