Sanchita Kamath's Preliminary Examination
PhD candidate Sanchita Kamath will present her dissertation proposal, "Advancing Accessible 3D Scientific Data Visualization Interpretation and Learning for Blind and Low-Vision Learners: Design and Evaluation of an AI-Enabled VR Multi-modal Learning Environment." Her preliminary examination committee includes Chair & Director of Research Assistant Professor Dr. JooYoung Seo, Associate Professor Dr. Jessie Chin, Associate Professor Dr. Matthew Turk, Professor Dr. Robb Lindgren, and Professor Dr. Nicholas A. Giudice.
Abstract
Blind and low-vision (BLV) learners may encounter barriers when interpreting scientific data visualizations because conventional representations often communicate patterns, relationships, and spatial structures primarily through vision. Although prior research has examined accessible statistics instruction, tactile and auditory representations, and multimodal technologies, limited research has addressed how BLV learners develop and evaluate mental models of continuous three-dimensional scientific data or assess conversational AI explanations when direct visual verification is constrained. This dissertation proposal proposes to investigate how VR-based, multimodal instruction can support these processes among BLV novice learners in Grades 9–12, alongside teachers of students with visual impairments (TVIs). The proposed research will collect surveys, focus-group data, VR interaction logs, AI dialogues, interpretation assessments, concept maps, verbal reasoning, stimulated-recall data, and measures of trust, reliance, and verification. Expected results include characterizing instructional needs, mental-model development, and AI-supported reasoning and verification. Findings may inform TVIs, researchers, and designers of accessible learning technologies.
Questions? Contact Sanchita Kamath.