Lawrence Obiuwevwi, Krzysztof J. Rechowicz, Jessica M. Johnson, Erika Frydenlund, Vikas Ashok, Sachin Shetty, Sampath Jayarathna — IEEE IRI 2026, submitted 1 Jul 2026 📄 Full text (arXiv)
Three-layer JavaScript pipeline (1500 lines) generates tactile 3D-printed statistical graphs for blind/low-vision students in under 250ms, with optional LLM-based chart extraction from images.
Key Contributions
- Three-layer JavaScript pipeline (1500 lines) generates tactile 3D-printed statistical graphs for blind/low-vision students in under 250ms, with optional LLM-based chart extraction from images.
Connections to AI in Education
This paper contributes to the growing body of research on AI applications in educational settings, specifically in the domains of llm-in-education, intelligent-tutoring-systems, and equity. The findings have implications for how educators design learning experiences that leverage AI while maintaining appropriate pedagogical oversight.
Related Pages
- equity — accessible education technology
- special-education — special education tools
- adaptive-learning — adaptive learning systems
- k-12 — K-12 inclusive education
- ai-literacy — AI literacy through accessibility
Citation
APA: Lawrence Obiuwevwi, Krzysztof J. Rechowicz, Jessica M. Johnson, Erika Frydenlund, Vikas Ashok, Sachin Shetty, Sampath Jayarathna (2026). Touching and Feeling the Data: A Reusable Software Pipeline for Tactile Statistical Graphs in Accessible Education. arXiv:2607.01214. IEEE IRI 2026, submitted 1 Jul 2026