Abstract
Special education encompasses a unique landscape of challenge in trying to address all diversified needs of students with disability. Traditional teaching methods typically fail to provide individual support needed for effective learning to take place, especially concerning children with learning disabilities and autism spectrum disorder. How AI and data science integration may revolutionize the response of educators to these challenges is yet to be observed. This chapter talks about the use of AI-driven tools and data-informed strategies to improve educators' capabilities in creating personalized learning experiences. The chapter explores how predictive models identify at-r isk students and provide timely interventions and uses of assistive technologies, such as speech-to-text, to increase accessibility. Data science methods, such as clustering and anomaly detection, shed light on performance and behavior and inform instructional decisions to improve program effectiveness.
Original language | English |
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Title of host publication | Driving Quality Education Through AI and Data Science |
Publisher | IGI Global |
Pages | 73-89 |
Number of pages | 17 |
ISBN (Electronic) | 9798369382943 |
ISBN (Print) | 9798369382929 |
DOIs | |
Publication status | Published - Feb 13 2025 |
ASJC Scopus subject areas
- General Computer Science
- General Social Sciences