Implications and Identification of Specific Learning Disability Using Weighted Ensemble Learning Model

The proposed WEL-XGB model effectively identifies learning disabilities in children, offering a powerful tool for both diagnosis and instructional support. Its high accuracy rates underscore its potential to revolutionize the assessment and intervention process for dyslexia and dysgraphia, benefiting students, parents and educators alike.

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Publication Details

Journal
Child Care Health and Development
Published
2024-12-23
DOI
https://doi.org/10.1111/cch.70026
Citations
2
Primary Topic
Text Readability and Simplification
Type
article
Field-Weighted Citation Impact
0.69

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article

Implications and Identification of Specific Learning Disability Using Weighted Ensemble Learning Model

Faris Algahtani, Sultan Alzahrani
2 citations
Child Care Health and Development
Text Readability and Simplification
0.69
article

Implications and Identification of Specific Learning Disability Using Weighted Ensemble Learning Model

Faris Algahtani, Sultan Alzahrani
article en
2 citations

Abstract

The proposed WEL-XGB model effectively identifies learning disabilities in children, offering a powerful tool for both diagnosis and instructional support. Its high accuracy rates underscore its potential to revolutionize the assessment and intervention process for dyslexia and dysgraphia, benefiting students, parents and educators alike.

Child Care Health and DevelopmentVol. 51(1)
University of Jeddah (SA)
University of Jeddah
Quality Education
Openalex Percentile: Top 22%
Text Readability and Simplification
0.69
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