Students’ Views on the Use of Critical Thinking-Based Pedagogical Approach for Vocabulary Instruction
Bibliographic record
Abstract
This research aimed to explore students’ views towards the use of a critical thinking pedagogical model for vocabulary instruction. From this end, a questionnaire was utilized to collect both quantitative and qualitative data to investigate the students’ opinions about such an educational experience. Data analysis revealed that the meaningful and purposeful critical thinking vocabulary tasks triggered learners’ motivation while engaging their higher cognitive abilities in solving the tasks and enabling them to reflect on their topics based on their personal and life experiences. This challenging process led learners to have more opportunities for practicing ‘elaborative rehearsal’, and as a result, to process the targeted vocabulary deeper. This created a stronger association with the taught vocabulary, which ultimately enabled them to be encoded in the learners’ long-term memory. Based on these findings, the authors recommend that teachers, teacher educators, and curriculum designers should draw upon the findings of these studies and consider the advisability of embedding critical thinking-based teaching methods across all strata of the EFL teaching system: policy documents, curricula, teacher training courses and the language classrooms.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".