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Record W2030879089 · doi:10.5539/hes.v2n2p100

Reading Habits of the Students with Bengali Medium Background at the English Medium Private Universities in Bangladesh

2012· article· en· W2030879089 on OpenAlexvenueno aff
Khaled Mahmud, Md. Golam Hoshain Mirza

Bibliographic record

VenueHigher Education Studies · 2012
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsBengaliReading (process)MemorizationContext (archaeology)Mathematics educationPsychologySchedulePedagogyMedical educationComputer scienceLinguisticsMedicineHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.349
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2012
Admission routes1
Has abstractyes

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