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Record W2140999911 · doi:10.5539/ijps.v5n2p92

The Effects of Multisensory Method and Cognitive Skills Training on Perceptual Performance and Reading Ability among Dyslexic Students in Tehran-Iran

2013· article· en· W2140999911 on OpenAlexvenueno aff
Seyedmorteza Nourbakhsh, Mariani Mansor, Maznah Baba, Zainal Madon

Bibliographic record

VenueInternational Journal of Psychological Studies · 2013
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyReading (process)CognitionDyslexiaTest (biology)Developmental psychologyIntervention (counseling)Perception

Abstract

fetched live from OpenAlex

The purpose of this research is to examine the effects of cognitive (cognitive skills training) and developmentalintervention (sensory-perceptual skills training) on performance and reading ability of dyslexic students. In thestudy 60 dyslexic students participated and they were divided into three experimental groups including 20students as the first experimental group (E1), 20 students as the second experimental group (E2), and 20 studentsas the control group (C). The effectiveness of the 16-session intervention for both E1 and E2 groups wasmeasured by Reading and Dyslexic test (RTD) as screening test at the beginning and followed by the BenderVisual Motor Gestalt Test (BVMGT) and Rey-Osterrieth Complex Figure test (ROCF). The results wereanalyzed by using analysis of variance (ANOVA) to compare mean scores among the three dyslexic groups afterintervention. Findings suggest that developmental intervention significantly improves RDT, BVMGT andmemory scale of ROCF performance of dyslexic students. However, cognitive intervention does not appear tosignificantly increase performance of the students compared to the control group.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
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 head0.071
GPT teacher head0.433
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 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

Citations11
Published2013
Admission routes1
Has abstractyes

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