Exploring Saudi University English Teachers' Perceptions of Global Englishes
Bibliographic record
Abstract
This paper aims to explore the paradigm of Global Englishes through the perceptions held towards it by university English teachers in Saudi Arabia. Due to reasons, such as globalization and colonization, the presence of English can be found in all countries throughout the world. Some countries, such as Saudi Arabia have not yet fully institutionalized the language which places them in the expanding circle, where English is currently seen and pedagogically taught as a foreign language. There are currently more non-native speakers of English than native English speakers worldwide, presenting a wide array of English varieties, influenced by native languages and local dialects. International teachers and students of English have presented a common theme and that is their desire to speak English with native like proficiency. Thus, in turn, the current method through which English language teaching takes place is typically a standard nativism approach using American or British English as a benchmark. The concern is that the standard nativism model may not accurately reflect the variety of English that is practiced and used specifically in Saudi Arabia in the case of this study, nor within the world as countless people use English as their second or even third language. Global Englishes offers a diversified and inclusive way of accepting varieties of English and it offers a framework for English to be taught within. The current study sought to explore the perceptions held by Saudi university teachers towards Global Englishes. The study made use of focus group interview discussions with university English teachers in Saudi Arabia from which three dominant themes emerged through thematic analysis. Firstly, it was clear that the teachers were not fully aware of the notion of Global Englishes before the study, and therefore did not realize that alternative methods of English language teaching were being developed to include and accept different varieties of English. In addition, the teachers did not view Global Englishes as a legitimate framework for teaching English, for reasons such as it navigates from the “pure” form of standard English. In conclusion, the teachers seemed to be some-what apprehensive about incorporating Global Englishes into their teaching curriculum. Similar results have been found in other studies of a comparable nature.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".