Paper Title
EARLY DIAGNOSIS OF SPECIFIC LEARNING DISABILITY USING DECISION TREE ALGORITHM
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Registration ID: IJNRD_217366
Published ID: IJNRD2404110
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Keywords
Specific Learning Disability, Decision Tree Algorithm, Dyslexia, Dysgraphia, Dyscalculia.
Abstract
A child's cognitive capacities, text comprehension, reading and writing skills, and ability to solve problems might be affected by a learning limitation, which is a specific sort of a learning impairment (neurodevelopmental disease). Specific learning disabilities (SLD) is intellectual disabilities which primarily impact a student's academic performance. Specifically, dyslexia, dysgraphia, and dyscalculia are problems with reading, writing, and math. These students should be identified at an early stage so that they can receive the right help and build their disability skills while gaining sufficient expertise with a particular task. The testing scale tool has been developed as a means of diagnosing the SLD. With the use of the suggested instrument, students who may have SLD can take the quiz. Certain test questions are repeated three times depending on the kind of learning disability. The decision tree algorithm gathers their results after the test is over. The decision tree algorithm predicts kids who possess learning impairments on the basis of their score and time. The suggested method is used to create an integrated, easy to use mechanism that can be quite precise in recognizing issues related to reading, writing, and math. It also suggests the best ways to instruct parents and instructors.
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How To Cite (APA)
Ansira Fathima M & Mr.Pramod K (April-2024). EARLY DIAGNOSIS OF SPECIFIC LEARNING DISABILITY USING DECISION TREE ALGORITHM. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), b67-b72. https://ijnrd.org/papers/IJNRD2404110.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : b67-b72
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Paper Reg. ID: IJNRD_217366
Published Paper Id: IJNRD2404110
Research Area: Engineering
Author Type: Indian Author
Country: -, -, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404110.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404110
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