Struggles in English Learning: Perspectives of Bangla Medium Students at the Higher Secondary Level
Bibliographic record
Abstract
This research provides an overview of the heterogeneous challenges confronted by Bangla medium students at the higher secondary level in engulfing English even after long years of exposure to English in formal education. Using a mixed-methods design, data are collected from 146 students and 15 teachers from three colleges in the Rangpur Division of Bangladesh. Structured Likert-scale questionnaires are used to collect quantitative data and semi-structured interviews and open-ended questions to collate qualitative information. The study reveals that common barriers to communication persist across speaking, writing, reading, and listening domains, shaped by factors such as insufficient exposure to English, low confidence, rigid curriculum design and resource constraints. Thematic analysis reveals that the challenges are grounded in socio-cultural and systemic contexts. Yet students also show resilience through peer-to-peer support, multimedia tools and self-generated strategies. The study suggests curriculum changes, communicative instructional methods, and inclusive classroom strategies that promote both greater English language proficiency and active engagement of students, addressing broader issues of educational inequality.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".