Investigating the Policy-Reality (Mis)Match in IELTS and TOEFL from the Perspectives of Global Englishes
Bibliographic record
Abstract
Abstract Introduction: In recent years, the number of test-takers of international tests of English has grown at an exponential rate. Those whose first language is not English, i.e. non-native English speakers (NNES), constitute the predominant majority of these test-takers, largely based in non-Anglophone contexts. Thus, the state of whether the international tests of English are fit for purpose and reflect the current realities of language users, especially in higher education institutions, has become a matter of serious concern recently. Hence, we aim to analyze the websites and language documents of two major international tests of English boards (i.e. IELTS and TOEFL) in relation to the kind of Englishes against which they judge their test-takers’ English proficiency - either by implication or by explicit expression. Methods: To analyse the websites and language policy documents of the major international tests of English boards, we adopted a qualitative research design in which our prime purpose was to collect a blend of textual, visual and audio materials from their websites as well as publicly available documents, such as skill-band-descriptors, sample test materials, and handbooks for test takers. The analysis of the data was multimodal, utilizing a mixture of qualitative frameworks to analyze the websites and documents. Results: The findings reveal that IELTS and TOEFL promote themselves as welcoming international test takers, while in practice, most of the contents in their examinations still draw on NES norms based on what is considered standardized English. Visual portrayals on their websites indicate that these tests are aware of English diversity and aim to embrace multicultural clients. However, no remedial measures seem to have been taken in practice as can be understood from their test and measurement criteria as regards writing and speaking. Discussion: Drawing on the results, it may be argued that the visual portrayals are merely the tools to attract NNES test takers and the covert message is that those who are NNESs should take these proficiency examinations. Moreover, many listening exams employ NESs to produce the voices or simulate the conversations. Although the tests claim that the voices are from diverse accents, including Australia, Canada, New Zealand, the UK, and the USA; they fail to recognize that many more English varieties exist within the Outer and Expanding Circle countries. Limitations: This research has only dealt with two major international tests of English, namely IELTS and TOEFL. There are other major tests of English available in the market. Therefore, sufficient caution should be exercised while generalizing the results to other tests as there may have been some rethinking and awareness in other tests with respect to their future test-takers’ profile and linguistic diversity. Conclusion: The findings illustrate a degree of recognition of Global Englishes (WE and ELF) at a “theoretical level” in the international tests of English, but at the “practical level”, many crucial principles are absent as the tests, judging international test takers, remain confined within the native-norm territory. In short, the phenomenon demonstrates a theoretical level of awareness, but such awareness is not further applied at the practical level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".