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Artificial Intelligence in Science and Mathematics Assessment for Students with Disabilities: Opportunities and Challenges

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Publicat a:Education Sciences vol. 15, no. 2 (2025), p. 233
Autor principal: Clark, Amy K
Altres autors: Hirt, Ashley, Whitcomb, David, Thompson, W Jake, Wine, Marjorie, Karvonen, Meagan
Publicat:
MDPI AG
Matèries:
National Research Council American Educational Research Association
United States > US
Problem solving
Teaching
Standards
Handicapped accessibility
Students with disabilities
STEM education
Educational technology
Mathematics
Cognition & reasoning
Accountability
Data integrity
Artificial intelligence
Science education
Knowledge
Personalized learning
Decision making
Multiple choice
Educational research
Large language models
School districts
Computer Simulation
Data Use
Educational Practices
Educational Finance
Intelligent Tutoring Systems
Influence of Technology
Academic Achievement
Individualized Programs
Individualized Instruction
Individual Testing
Mathematics Education
Individualized Education Programs
Educational Assessment
Educational Testing
Elementary Secondary Education
Opportunities
Learner Engagement
Educational Facilities Improvement
Educational Equity (Finance)
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Resum:Emerging developments in artificial intelligence present significant opportunities to enhance equity and access to science and mathematics assessment content for students with disabilities. Artificial intelligence (AI) technologies may have the potential to support test developers in creating more inclusive assessments that better measure what students know and can do. But they must also consider the potential accessibility challenges or introduction of construct-irrelevant variance posed by these technologies. The purpose of this article is to provide a conceptual overview of the issues to be considered when creating and implementing large-scale science and mathematics assessments for students with disabilities. We discuss how AI has been utilized in large-scale assessments to date and describe the opportunities and potential pitfalls in the stages of the process: assessment design, development, administration, scoring, reporting, and data use. This article concludes with proposed priorities for research that will advance the responsible practice of AI in large-scale assessment that is inclusive, fair, and valid for students with disabilities. This article contributes to the growing body of information on AI applications for assessment by identifying the roles that AI can play in science and mathematics assessment practices and demonstrating how AI can inform approaches to equitable science, technology, engineering, and mathematics (STEM) learning.
ISSN:2227-7102
2076-3344
DOI:10.3390/educsci15020233
Font:Education Database