An Analysis of Global Englishes Aspects in English Textbooks at the Lower Secondary Level in Thai EFL Context
Bibliographic record
Abstract
The spread of English as a global language has resulted in several changes, which challenge the foundations of how language should be taught and learned. To match today‘s sociolinguistic realities, researchers have called for a paradigm shift from the traditional pedagogy to a new pedagogy that can prepare students to use English in international communication involving different varieties of English and its cultures. The purposes of this study are (1) to investigate the aspects of target interlocutors, and (2) to investigate cultural depictions as reflected in three selected English textbooks, which are currently used in lower secondary level (Grade 7) in Thailand. Three English textbooks are purposively selected as the samples of this study. Data is collected from the communication practice tasks (e.g., conversation dialogues, emails, and letters) and the contents of the reading passages, and articles in the textbooks. The Galloway's and Rose's (2018) GELT framework and Kachru's (1992) Three Circles Model are used to analyse data. The findings reveal that the textbooks mostly represent the target interlocutors from Native English users. With regards to the aspect of cultural depiction, the findings reveal that various cultures from all three circles are represented in these textbooks. The findings suggest that the English textbooks that which are currently used in Thai EFL context are likely to rely on the traditional ELT in the aspect of the target interlocutors. However, the depiction of cultural aspects in the textbooks corresponds more to the GELT concept with regards to the promotion of learners from different cultures across circles.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".