Revisiting Creative Teaching Approach in Saudi EFL Classes: Theoretical and Pedagogical Perspective
Bibliographic record
Abstract
The present study aims to address the aspects of similarities and differences between the traditional and the creative teaching approaches in the Saudi EFL context by providing a comparative critical review of literature about the current teaching approaches. The study adopts a comparative critical approach that employs critical comparison to assess, critique, and synthesize the literature on a research topic in a way that enables new theoretical frameworks and perspectives to emerge. It also critically compares the previous studies dealing with creativity in teaching English as a Foreign Language with those dealing with traditional teaching approaches to explore the impediments of the application of the creative teaching approach to teaching English in a Saudi environment. The study has found that the previous studies on creativity and teaching English as a foreign language are in short of a clear understanding of how creativity can be used as an effective teaching approach and they also lack empirical evidence. In addition, there seems to be a conflation of creativity and the traditional teaching approach in the sense that although several studies claimed that they provided a creative teaching approach, their results and findings contradicted their objectives and hypotheses. In most cases, their methods were tailored to offer an impractical and illusory teaching approach, which has nothing to do with creativity. The proposed teaching approaches are incoherent and inhomogeneous which never suits either of them. Therefore empirical studies on creativity and its impact on EFL learners' minds in Saudi Arabia should be initiated.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".