MétaCan
Menu
Back to cohort
Record W2743445667 · doi:10.5539/elt.v10n9p49

Effect of Inclusion Versus Segregation on Reading Comprehension of EFL Learners with Dyslexia: Case of Lebanon

2017· article· en· W2743445667 on OpenAlexvenueno aff
Ghada Awada, Mar Gutiérrez‐Colón

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsReading comprehensionPsychologyAutomatic summarizationMnemonicInclusion (mineral)Reading (process)Mathematics educationNarrativeTest (biology)DyslexiaComprehensionLinguisticsCognitive psychologyComputer scienceSocial psychologyNatural language processing

Abstract

fetched live from OpenAlex

This study reports the relative effectiveness of the inclusion theory when the combined strategy instruction on improving the reading comprehension of narrative and expository texts for students with dyslexia is implemented. A total sample of 298 students of English as a foreign language from both public and private schools participated in the study which employed a pre-test- post-test control group design to investigate the efficacy of combined strategy instruction consisting of Graphic organizers, Visual displays, Mnemonic illustrations, Computer exercises, Prediction, Inference, Text structure awareness, Main idea identification, Summarization, and Questioning. The study concluded that combined strategy instruction in the field of the inclusion theory is more effective than regular instruction in improving reading comprehension when using narrative texts, but there’s no difference, when using expository texts. There was no significant difference neither by gender nor by school types in all the grade levels under study.

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 score0.700
Threshold uncertainty score0.520

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 integrity0.0000.000
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 head0.013
GPT teacher head0.335
Teacher spread0.322 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicReading and Literacy DevelopmentFrench-language works237,207