Nonvisual Support for Understanding and Reasoning about Data Structures

2026-01-27

AI Summary

This work addresses the challenges faced by blind and visually impaired computer science students in comprehending data structures, as existing accessibility approaches often merely translate visual appearances without conveying underlying topological relationships. To bridge this gap, the authors propose Arboretum, a system that automatically compiles code-generated data structure diagrams into three synchronized non-visual representations: tabular views, navigable digital interfaces, and tactile graphics—preserving structural semantics and enabling multimodal understanding. Design requirements were refined through a Wizard-of-Oz study, leading to the implementation of structure-aware multimodal outputs and synchronized interaction mechanisms. User studies demonstrate that tactile graphics significantly improve performance on complex tasks such as binary search, while the integration of multiple representations enhances structural reasoning; however, purely digital navigation alone proves insufficient for expressing topological relationships.

Technology Category

• Computer Vision: Multi-modal Vision
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning
• Humans and AI: AI for Accessibility

Application Category

• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs
• Semantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semantics
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

Blind and visually impaired (BVI) computer science students face systematic barriers when learning data structures: current accessibility approaches typically translate diagrams into alternative text, focusing on visual appearance rather than preserving the underlying structure essential for conceptual understanding. More accessible alternatives often do not scale in complexity, cost to produce, or both. Motivated by a recent shift to tools for creating visual diagrams from code, we propose a solution that automatically creates accessible representations from structural information about diagrams. Based on a Wizard-of-Oz study, we derive design requirements for an automated system, Arboretum, that compiles text-based diagram specifications into three synchronized nonvisual formats$\unicode{x2013}$tabular, navigable, and tactile. Our evaluation with BVI users highlights the strength of tactile graphics for complex tasks such as binary search; the benefits of offering multiple, complementary nonvisual representations; and limitations of existing digital navigation patterns for structural reasoning. This work reframes access to data structures by preserving their structural properties. The solution is a practical system to advance accessible CS education.

Problem

• accessibility
• data structures
• blind and visually impaired
• nonvisual representation
• computer science education

Innovation

• nonvisual representation
• data structures accessibility
• tactile graphics
• automated diagram generation
• inclusive CS education