AI-Driven Assessment Tools for Special Needs Students

Abstract

AI-driven assessment tools have revolutionized the evaluation process for special needs students by providing personalized, adaptive, and objective measurements of their learning progress. By leveraging machine learning algorithms, natural language processing, and data analytics, these tools offer real-time feedback, tailored interventions, and insights into student performance. This paper explores the role of AI-driven assessment tools in special education, focusing on their applications, benefits, and challenges. Using a mixed-methods approach, the study evaluates the effectiveness of these tools in assessing diverse learning needs and identifies strategies for ethical and equitable implementation. The findings highlight AI’s potential to transform special education assessment, fostering inclusivity and improving educational outcomes.