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Record W2776248795 · doi:10.5539/ies.v11n1p165

The Effectiveness of Neurological Impress Method on Reading Fluency of Students with Learning Disabilities in Amman, Jordan

2017· article· en· W2776248795 on OpenAlexvenueno aff
Ayed H. Ziadat, Mohammad Soud A. AL-Awan

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsnot available
Fundersnot available
KeywordsFluencyPsychologyReading (process)Learning disabilityMathematics educationTest (biology)Reading comprehensionDevelopmental psychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the effectiveness of Neurological Impress Method (NIM) on reading fluency of students with learning disabilities in Amman, Jordan. A sample of forty students (boys and girls) between the ages 10-12 years old with learning disabilities were selected from the Fourth Amman Educational Directorate in the Hashemite Kingdom of Jordan.Students focused groups in this research were separated into two different groups including the satisfactory controlled group. The participants were taught for one complete semester. Two hypotheses were formulated to guide this research.Statistical analysis to the gathered data revealed that the focused group of students who were trained according to the scheduled strategy to improve students reading ability or became more fluent in reading.Full analyses were applied using the T-test on all available data, indicating that students who were trained according to the scheduled strategy.The study found out that the strategy reduced the reading fluency deficiency in teens with different levels of learning disabilities. Consequently, it was recommended that the strategy can be used to improve reading fluency of students with learning disabilities.

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)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.069
GPT teacher head0.440
Teacher spread0.372 · 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.

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

Citations6
Published2017
Admission routes1
Has abstractyes

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