Prioritize research on GenAI's impact on students with disabilities and design personalized teaching strategies for their needs¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article closes with a forward-looking recommendation for future research: "Future researchers should delve into the impact of GenAI technologies on students with disabilities and design personalized teaching strategies tailored to their needs." This directs the next wave of GenAI-in-education studies toward an under-served population and toward personalization as the design response, extending the meta-analysis's personalized-learning framework to learners whose needs the included studies did not cover.

Design Implications¶

Context¶

Requirements¶

• Future studies must focus on students with disabilities, a population not represented in the current 53-study corpus

Constraints¶

• The article offers no evidence about GenAI's effects on students with disabilities; the recommendation is untested in this review

Target Learners¶

• students with disabilities

Target Learning Goals¶

• personalized learning
• educational outcomes across academic achievement, higher-order thinking, and writing skills

Related Strategies¶

• Future research on special education class size should include rigorous quantitative designs and foreground the voices of children and young people with special needs
• Prioritise equity-centred approaches, methodological diversity, contextual specificity, implementation science and interdisciplinary collaboration in GenAI research

Examples¶

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Key Sources¶

• Ying Dong. (2026). Generative AI technologies and educational outcomes: a comprehensive meta-analysis comparing traditional and AI-driven approaches. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-026-06903-y