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Record W4321433955 · doi:10.5539/ijel.v13n2p58

English Language Learning and Prospect of Secondary Schools in Bangladesh

2023· article· en· W4321433955 on OpenAlexvenueno aff
Abdul Awal

Bibliographic record

VenueInternational Journal of English Linguistics · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationEnglish languageClass (philosophy)Foundation (evidence)PsychologyPedagogyPolitical scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

In Bangladesh, English as an international language is taught in primary and secondary schools to build a strong foundation for English learning for children from childhood. The necessity to determine the current situation of English-language learning among secondary school students in Bangladesh and the future of this phase is the sole purpose of this study. For this study, data were collected from ten different secondary schools in Bangladesh where the Class 8—English for Today book was used to teach English. Concisely, the objectives of the study are to gather information and discuss learning the vibrant international languages of the present and future. In this research, data collected from 200 students from ten secondary high schools in ten upazilas [sub-districts] is used to analyze prospective English language learning. The results of the analysis revealed that the textbook is not effective for English learning and has not met people’s expectations. Measures must be taken to overcome the problem.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.020
GPT teacher head0.358
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

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