Collaborative Design: Leveraging GenAI to Create Metacognition-Aligned Mathematics Instruction for Students With Disabilities

Many educators utilize generative artificial intelligence (GenAI) to streamline demanding workloads and accelerate the individualization of instruction for students with disabilities (SWD). However, challenges may arise if such tools perpetuate ineffective instruction for SWDs. To address this issue, CoIEP was developed. CoIEP is a large-language-model-based multi-agent system specially designed to assist educators in developing individualized programming and evidence-based instruction for SWDs. This article describes how CoIEP, combined with an explicit instructional decision-making process, can support special and mathematics education co-teachers in efficiently designing evidence-based instruction for SWDs. To bridge ongoing debates on effective mathematics instruction for SWDs within both special and mathematics education, this collaborative approach intentionally integrates opportunities for SWDs to foster metacognition (i.e., “thinking about thinking”) as a bridge, a shared understanding, between the two communities. This article presents a step-by-step overview outlining how co-teachers can effectively prompt CoIEP to design evidence-based, metacognition-aligned mathematics instruction for SWDs.

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Publication Details

Journal
Journal of Special Education Technology
Published
2026-04-10
DOI
https://doi.org/10.1177/01626434261435266
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Collaborative Design: Leveraging GenAI to Create Metacognition-Aligned Mathematics Instruction for Students With Disabilities

Tiffany Hunt, Candace Joswick, Ling Zhang, Miriam Sanders et al.
Journal of Special Education Technology
Innovative Teaching and Learning Methods
article

Collaborative Design: Leveraging GenAI to Create Metacognition-Aligned Mathematics Instruction for Students With Disabilities

Tiffany Hunt, Candace Joswick, Ling Zhang, Miriam Sanders, Jana L Nelson
article en

Abstract

Many educators utilize generative artificial intelligence (GenAI) to streamline demanding workloads and accelerate the individualization of instruction for students with disabilities (SWD). However, challenges may arise if such tools perpetuate ineffective instruction for SWDs. To address this issue, CoIEP was developed. CoIEP is a large-language-model-based multi-agent system specially designed to assist educators in developing individualized programming and evidence-based instruction for SWDs. This article describes how CoIEP, combined with an explicit instructional decision-making process, can support special and mathematics education co-teachers in efficiently designing evidence-based instruction for SWDs. To bridge ongoing debates on effective mathematics instruction for SWDs within both special and mathematics education, this collaborative approach intentionally integrates opportunities for SWDs to foster metacognition (i.e., “thinking about thinking”) as a bridge, a shared understanding, between the two communities. This article presents a step-by-step overview outlining how co-teachers can effectively prompt CoIEP to design evidence-based, metacognition-aligned mathematics instruction for SWDs.

Journal of Special Education Technology
University of Wyoming (US), The University of Texas at Arlington (US)
Quality Education
Openalex Percentile: Top 16%
Innovative Teaching and Learning Methods
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