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Record W2285166838 · doi:10.5539/ells.v6n1p1

Why Do Saudi EFL Readers Exhibit Poor Reading Abilities?

2016· article· en· W2285166838 on OpenAlexvenueno aff
Abdulaziz Al-Qahtani

Bibliographic record

VenueEnglish Language and Literature Studies · 2016
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)VocabularyPsychologyReading comprehensionMathematics educationContext (archaeology)PerceptionPedagogyMedical educationMedicineLinguistics

Abstract

fetched live from OpenAlex

<p>The aim of the current study was to investigate the reasons behind Saudi learners’ poor reading skills. To this end, the objectives were to identify the reading habits of Saudi English as a Foreign Language (EFL) middle school learners, to understand the extent to which Saudi EFL middle school learners use reading comprehension skills and to explore the perceptions of learners, teachers and supervisors regarding Saudi EFL learners’ reading abilities. The study sample consisted of 90 Saudi EFL middle school students, eight EFL teachers and six supervisors. The students were surveyed and interviewed about their reading habits and use of reading skills, while the teachers and supervisors were interviewed to explore their perceptions about reading instruction in the Saudi context. The results revealed that most Saudi EFL students lack the necessary reading habits in L1 and L2. In addition, they rarely make use of important reading skills when they read English texts. This study identified “lack of exposure to target language”, “poor teaching skills and teacher training programs”, “little attention to comprehension and more attention to reading aloud”, “students’ lack of motivation”, “little emphasis on reading skills in textbooks”, “unfamiliar and unsuitable reading topics”, “lack of reading skills training for students”, “students’ limited vocabulary” and “lack of parental involvement” as the most important factors behind Saudi students’ poor reading abilities. The study concluded with important recommendations and suggestions for future research.</p>

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)0.001
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 score0.449
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.012
GPT teacher head0.290
Teacher spread0.278 · 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

Citations58
Published2016
Admission routes1
Has abstractyes

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