English in Uzbekistan: language ideologies and teaching practices
Bibliographic record
Abstract
Abstract This study examines the evolving role of English in Uzbekistan’s educational institutions within the context of recent educational reforms initiated by President Mirziyoyev to modernize the education system and create a “competitive state” where multilingualism, including English proficiency, is prioritized. The research explores the instrumental functions of English in the aftermath of these reforms and employs theories of language ideologies (LI) to analyze Uzbek EFL teachers’ perceptions of English. Additionally, it investigates how these ideologies influence teaching methodologies and classroom practices. To address the research questions, the study draws on multiple primary data sources, including interviews and observational notes. The findings highlight that the presidential reforms, alongside initiatives by the US Embassy and the British Council, are key drivers promoting the spread of English within Uzbekistan’s educational landscape. Data analysis reveals that these reforms have significantly influenced and reshaped EFL teachers’ language ideologies. Teachers reported adopting pedagogical methods and strategies aimed at preparing students to thrive in a globalized world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".