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MSD Trends in Computer Networks and Information Technology

Research Article       Open Access      Peer-Reviewed

Comparative Analysis of Adaptive Learning and Fast for Word Programs for ASD Students in Learning English, and Mathematics, and Predicting Future Acad

Aisha Ahmed1*, Abdullahi Abdu Ibrahim2

Abstract

This study investigates the efficacy of adaptive learning methods in teaching English and Mathematics to students diagnosed with autism spectrum disorder (ASD), compared to the Fast ForWord program. Utilizing a randomized controlled trial design, students aged 6-7 were assigned to either the adaptive learning group or the Fast ForWord group. Pre- and post-tests in English and Mathematics, along with engagement and behavior checklists, were used to assess outcomes. We employed machine learning techniques, including Support Vector Machine (SVM), K Nearest Neighbor (KNN), Gaussian Process Regressor (GPR), and Logistic Regression (LR), to predict student scores and analyze the effectiveness of these educational interventions. Results indicate that the Gaussian Process Regressor (GPR) is the best for predicting students’ future grades, and adaptive learning methods significantly improved academic performance and engagement compared to the Fast ForWord program, suggesting a need for personalized educational strategies in ASD. These fi ndings have signifi cant implications for educators and policymakers seeking to enhance educational outcomes for students with ASD.

Introduction

Autism Spectrum Disorder (ASD) is a developmental disorder characterized by difficulties with social interaction, communication, and repetitive behaviors [1]. According to the Centers for Disease Control and Prevention (CDC), approximately 1 in 54 children in the United States is diagnosed with ASD [2]. These students often face significant challenges in traditional educational settings, where standard teaching methods may not cater to their unique learning needs. Educational interventions for students with ASD have evolved over the years, with increasing emphasis on personalized and technology-driven approaches. Adaptive learning methods utilize data analytics and machine learning algorithms to tailor educational content to the individual learner, adjusting in real-time to provide a customized learning experience [3]. The Fast ForWord program is a computer-based intervention designed to enhance cognitive skills related to language and reading, leveraging neuroplasticity to improve cognitive function [4].

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