Research Summary: AI literacy development among special education graduate students: a mixed-methods exploration

A mixed-methods study exploring AI literacy among master's-level special education graduate students revealed a significant conceptual shift. Initially perceiving generative AI as an administrative efficiency tool, participants increasingly recognized its potential as an adaptive instructional scaffold for students with high-incidence disabilities. This evolving understanding was coupled with heightened awareness of critical implementation considerations, including human oversight, data privacy, and individualized student alignment.

Why it matters

The evolving perception of generative AI among future educators highlights its potential to transform instructional methodologies, particularly for diverse learning populations. Understanding these shifts and associated concerns is crucial for developing robust frameworks that ensure ethical, effective, and equitable integration of AI technologies across educational settings. This has broad implications for future workforce readiness and service delivery models.

Key insights

• Special education graduate students demonstrated an evolution in their understanding of generative AI, moving from viewing it as an administrative tool to an adaptive instructional scaffold.
• Participants identified the potential of generative AI to support students with high-incidence disabilities.
• Key considerations for responsible AI implementation included critical human oversight, adherence to data privacy regulations (e.g., FERPA), and ensuring individualized alignment with student needs.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1967082