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Record W4200220747 · doi:10.5539/elt.v15n1p79

The Effect of Using KWL (Know-Want-Learned) Strategy on Reading Comprehension Of 5th Grade EFL Students in Kuwait

2021· article· en· W4200220747 on OpenAlexvenueno aff
Amel AlAdwani, Anam AlFadley, Maha AlGasab, Ahmad F. Alnwaiem

Bibliographic record

VenueEnglish Language Teaching · 2021
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsnot available
Fundersnot available
KeywordsReading comprehensionMetacognitionPsychologyMathematics educationReading (process)CurriculumLanguage proficiencyComprehensionCognitionEnglish as a foreign languagePedagogyLinguistics

Abstract

fetched live from OpenAlex

Metacognitive reading strategies play an essential role in improving reading comprehension. This study explores the effects of English metacognitive reading strategies and reading comprehension in Kuwaiti primary school students as foreign language learners; this experimental study tries to find a relationship between students' metacognitive strategies, metacognitive strategies, and students' reading performance. Participants were fifth grade EFL students in Kuwait primary education government public schools. The students' reading comprehension was evaluated. Comprehension tracking strategies were measured using Metacognitive strategies (K-W-L Plus). While the experimental groups (B) received instructions according to (K-W-L Plus) techniques, the control (A) group was trained with the traditional teaching approach based on the Kuwait national curriculum school textbooks. A questionnaire investigating the use of English and perceived English proficiency was also conducted. The results revealed that Perceived proficiency in English was not determined by the early or late pre-school age of second language acquisition. Also, bilingual students with perceived proficiency in English had better meta-cognitive reading skills than low perceived proficiency in English. Comprehension monitoring and (K-W-L) strategy was adequate and the most important predictor of reading comprehension among all students in the research sample.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.398
Teacher spread0.361 · 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 designQualitative
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

Citations11
Published2021
Admission routes1
Has abstractyes

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