Artificial intelligence and related technological advancements have been a matter of discussion in recent times. There has been regular growth in AI-based methods that have proven useful for various industry verticals. Education is one such critical field where AI can play a monumental role in improving quality and helping individuals strive for better education. Meeting the educational requirements of all children, adolescents, and adults has received more attention in recent years. Recent advancements in technology, such as data analysis and ML, can potentially revolutionize how we approach special education. By using these technologies to personalize learning experiences, track progress, and provide individualized support, educators can improve outcomes for students with special needs. With the right approach, data analysis and ML can be powerful tools for improving special education and supporting students with special needs. The main idea of the study is to outline in detail the various applications of AI-assisted special education and discover the depths of the methods.
Top1.0 Introduction
Over the past ten years, technological advancement has fundamentally changed the world and increased computer power in all facets of daily life. Understanding human intelligence in all of its manifestations is one of computing science's most important goals. Over the past 50 years, this quest has inspired numerous researchers to create the science of AI. AI is typically defined as the study and development of intelligent agents that have the ability to perceive their environment and perform actions that maximize their plausibility for success.
The convergence of AI and education is a topic of research in the science of AI. The majority of scientists and academics appear to agree that instruments using AI may successfully support the educational process. The education of all children and meeting the educational requirements of all children, adolescents, and adults have received more attention in recent years. This fact has strengthened the argument for using technology to remove obstacles to learning. The advantages of AI in teaching have long been praised, and the field of special education has long employed AI techniques.
Special education is one of the highly specialized fields within education. that focuses on providing support and assistance to students with special needs. This includes individuals with physical, cognitive, or behavioral disabilities, as well as those with exceptional talents and gifts. While traditional approaches to education have been successful in supporting many students with special needs, there are still many challenges to overcome. One of the most significant challenges is the need to provide individualized support to each student, considering their unique strengths, weaknesses, and learning styles.
Recent advancements in technology, such as data analysis and ML, can potentially revolutionize how we approach special education. By using these technologies to analyze student data, identify patterns, and develop personalized learning plans, educators can provide more effective support for their students. This paper will explore the potential benefits of data analysis and ML in AI-assisted special education.
Special education is a highly complex field that requires a deep understanding of both education and disability. According to the National Center for Education Statistics (2022) under the Individuals with Disabilities Education Act (IDEA), in 2020–21, 7.2 million kids between the ages of 3 and 21 received services with respect to special education. According to the United Nations, Department of Economic and Social Affairs Disability (2015), there are an estimated 1 billion people with disabilities worldwide, or approximately 15% of the populace as a whole, making them the world's biggest minority. Figure 1 from the U.S Department of Education (2021) shows the percentage distribution of IDEA-eligible students aged 3–21 by selected impairment type for the academic year 2020–21. Even with the substantial resources invested in special education, many students with disabilities struggle in conventional classroom environments.
Figure 1. Percentage wise distribution of students having ages between three (3) and twenty one (21) who receive IDEA services according to a particular impairment type: The academic year 2020–21
One of the biggest challenges in special education is the need for individualized support. Each student with special needs has unique strengths, weaknesses, and learning styles, thereby making the creation of a universal educational strategy challenging. Hence, this further complicates the fact that many students with special needs may also have co-occurring conditions, such as ADHD or anxiety, that require additional support.
Data analysis and ML are two technologies that have the potential to address the individual needs of students in special education. Data analysis involves using mathematical and statistical techniques to analyze large datasets and identify patterns and insights. A branch of AI known as machine learning (ML) employs statistical modeling and algorithms to learn, comprehend, and perform predictions or decision-making.