Design AI-assisted accessibility tools for personalization, practitioner review, and cultural and contextual specificity¶

Strategy · All strategies
Evidence · 1 claim (1 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The article distills its findings into design implications for AI-assisted accessibility tools in special education: personalization, practitioner review, and contextual specificity. It notes that "personalization must also have a cultural dimension as social narratives developed in Western contexts may miss locally meaningful cues and expectations." Concrete realizations include grade-based comprehension categories instead of subjective labels, sentence-length controls, child-like narration voices, tablet-friendly use, and support for varied learner needs across the autism spectrum.

Design Implications¶

Context¶

Requirements¶

• Practitioner input during design to align tools with real-world workflows and constraints

Constraints¶

• Views on system-wide analytics were mixed among practitioners; some preferred student-level information only

Target Learners¶

• Autistic children with varied cognitive abilities, attention spans, and communication profiles

Target Learning Goals¶

• Engagement and comprehension of social narratives tailored to the learner's context

Claims¶

• Practitioners perceived the profile-driven workflow as reducing Social Story preparation burden [+W]

Related Strategies¶

• Preparing preservice teachers to implement AI-powered personalized learning in special education through professional development in technical and pedagogical expertise

Examples¶

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Key Sources¶

• Buyankhishig Enkhjargal, Himanshi Lalwani, Hanan Salam. (2026). AI-Assisted Social Story Intervention for Special Education: The Design of AdaptED Stories. arXiv preprint. https://arxiv.org/abs/2609.24245