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Leading With Data: AI-Driven Decision Making in Special Education
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Author(s): Ahmed M. Alkaab (United Arab Emirates University, UAE), Mona Humaid Aljanahi (United Arab Emirates University, UAE), latifa Alketbi (United Arab Emirates University, UAE), Mohammed Humaid Aljanahi (United Arab Emirates University, UAE), Khalid Alhammadi (Abu Dhabi Department of Education and Knowledge, UAE)and Hamada Ahmed (Abu Dhabi Department of Education and Knowledge, UAE)
Copyright: 2026
Pages: 22
Source title:
AI in Learning, Educational Leadership, and Special Education: Innovations and Ethical Dilemmas
Source Author(s)/Editor(s): Maria Efstratopoulou (United Arab Emirates University, UAE), Agathi Argyriadi (Frederick University, Cyprus)and Alexandros Argyriadis (Hellenic Mediterranean University, Greece)
DOI: 10.4018/979-8-3373-0573-8.ch013
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Abstract
This chapter explores the potential of artificial intelligence in advancing data-informed decision-making in special education. By systematically collecting and analyzing large sets of student data, AI can identify performance patterns, predict challenges, and suggest tailored interventions—all of which enhance individualized learning outcomes and streamline administrative processes. This chapter highlights successful experiences with AI in school administration to demonstrate its practical impact on special education programs. However, the adoption of AI technologies also introduces critical considerations, including data privacy, stakeholder trust, and the need for professional development. The chapter underscores the importance of strategic implementation and inclusive engagement through a balanced evaluation of both the benefits and complexities of AI-supported decision-making. When thoughtfully applied, AI can promote more responsive and efficient special education services, empowering educators to address the diverse needs of students with greater precision and care.
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