Ethical and Social Impact of AI Driven Analysis for Students with Learning Disabilities Processes

Abstract

A multitude of intricate factors interact to determine kids' academic achievement. The varied demands of pupils are frequently not adequately met by traditional educational methods, which produces less than ideal learning results. The goal of this essay is to provide a thorough understanding of how learning difficulties and study techniques affect academic success. The idea behind integrating artificial intelligence (AI) capabilities is to provide recommendations for an enhanced educational approach through a decision support system (DSS). We used an artificial neural network (ANN) to detect patterns of correlation between study tactics, learning disorders, and academic achievement in order to discover features with stronger explanatory power based on empirical data. A fuzzy artificial intelligence (AI) system was developed to provide suggestions for successful educational interventions based on the contemplated attributes. The results highlight how important study techniques are for reducing the detrimental effects of learning difficulties on academic achievement. With the use of the suggested AI tools framework, teachers will be able to customize their lesson plans to each student's specific cognitive profile. More inclusivity in the classroom and better academic results can result from tailored interventions based on recognized trends. The data-driven techniques that have been offered can be implemented by educators and policymakers to improve teaching approaches and better meet the requirements of children with learning difficulties. This method encourages a more fair and inclusive educational environment, which helps all students succeed academically.