Reading Habits of the Students with Bengali Medium Background at the English Medium Private Universities in Bangladesh
Bibliographic record
Abstract
This paper investigates into the reading habits of the English medium private university students with Bengali medium background. It analyses the realities in the context, which are both nurturing the old and shaping new reading habits of the students. The data gathered by means of interview schedule have been analyzed both quantitatively and qualitatively. The data shows that our students’ reading habits - avoiding text books, memorizing readymade things for exam purposes, very little reading in not only English but Bengali as well - do not change remarkably during their tertiary level of study at the private universities. Rather they are further solidified and nurtured by the teachers’ supply of lecture notes, an acute lack of motivation for reading the study materials in English, and the negative backwash of the exam system. These causes of the undesirable reading habits can be removed only if all the teachers dealing with the students come forward and work together with the English teachers for a long period of time to achieve the aims.
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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 | 0.000 |
| 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".