Analysis and Early Diagnosing Tool for Learning Disability using Machine Learning Models

Abstract

The learning deficit is one particular type of neurological disorder that can affect a kid's mental abilities, word identification, ability to write and read, as well as their capacity for problem-solving. These disabilities are known as Particular Learning Disabilities because they primarily influence individuals' academic performance, particularly reading (dyslexia), writing (dysgraphia), and trouble with mathematical (dyscalculia) (SLD). These pupils must be discovered at an early stage so that, with the right assistance, they can gain sufficient experience with a particular task and hone their disability-related skills. The testing scale tool has been suggested for use in diagnosing and identifying SLD. The suggested tool enables the student who may have SLD to participate in the quiz. Depending on the type of test, some individual questions are repeated. The machine learning algorithms CNN and Random Forest receives the test results as input after the test is over. The algorithms predict children with learning impairments based on student grades and the amount of time spent by the kids. The suggested tool is used to create a user-friendly, integrated system for diagnosing reading, writing, and math impairments. It also suggests to parents and instructors the best methods and instructional activities.