Challenges of Pronunciation Practices in the ESL Curriculum within the CLT Framework in Bangladesh: A Systematic Review
Bibliographic record
Abstract
This systematic review explores the challenges of pronunciation in the ESL curriculum within the Communicative Language Teaching (CLT) framework in Bangladesh. Pronunciation, a critical component of language proficiency, often presents significant hurdles for ESL learners. The review highlights key issues such as inadequate teacher training, limited resources, and the influence of native language interference. It also examines the impact of large class sizes and the lack of individualized attention on learners' pronunciation skills. The CLT framework, while promoting communicative competence, sometimes overlooks the explicit teaching of pronunciation, further complicating the acquisition process. This study synthesizes findings from various research articles to provide a comprehensive understanding of these challenges. It underscores the need for targeted professional development for teachers, the integration of technology, and the inclusion of pronunciation-focused activities in the curriculum. By addressing these issues, the ESL curriculum in Bangladesh can better equip learners with the necessary pronunciation skills for effective communication.
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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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".