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Record W2907486783 · doi:10.5539/ijel.v9n1p178

Iraqi EFL Students’ Difficulties in Writing Composition: An Experimental Study (University of Baghdad)

2018· article· en· W2907486783 on OpenAlexvenueno aff
Sura Muttlak Nasser

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsComposition (language)PsychologyTest (biology)Mathematics educationAcademic writingAcademic yearMedical educationPedagogyMedicineArtLiterature

Abstract

fetched live from OpenAlex

Iraqi EFL students face difficulties in writing composition, especially academic writing, which affects negatively their exam results. This study has been conducted in the Department of English at College of Education for Women, University of Baghdad, in order to identify first year EFL students’ incompetence in writing. This may enhance their achievement by some weekly writing activities. It deals with Iraqi EFL students’ difficulties in writing paragraphs such as descriptive, process, opinion, and factual paragraphs. The study aims to identify these difficulties and to suggest suitable solutions for them. The researcher perceives that it is necessary to enhance students’ skills in writing because it is an important tool in their education progress. The study proved that the distinction is considerable. However, the researcher had a group sitting for pre and post- test to assess the output of the means of students’ results.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.032
GPT teacher head0.371
Teacher spread0.339 · 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 designNon-randomized trial
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

Citations42
Published2018
Admission routes1
Has abstractyes

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