Promoting Comprehension and Engagement in Introductory Data and Statistics for Blind and Low-Vision Students: A Co-Design Study

Danyang Fan, Olivia Tomassetti, Aya Mouallem, Gene Kim, Shloke Patel, Saehui Hwang, Patricia Leader, Danielle Sugrue, Tristen Chen, Darren Our, Victor R Lee, Lakshmi Balasubramanian, Hariharan Subramonyam, Sile O Modhrain, Sean Follmer

Three sketches labeled A through C. A. Sketch showing two students, two educators, and four researchers seated around a square table. The two students are sitting side by side collaboratively creating a data representation using physical tokens. B. Sketch of a student interacting with a data physicalization consisting of tokens on a digital platform. The physicalization is of a univariate distribution. The distribution mean, median, and mode are labeled. C. Multiple sketch depictions of different activities participants designed. One shows a distribution representing hornets. One shows a physical spinner used to generate random events. One depicts accessible pedestrian intersections. One shows a coin spinning in front of a data physicalization.

A) Students (blue), educators (green), and researchers (red) participated in a sequence of co-design sessions discussing, designing, and reflecting on practices that build conceptual knowledge and engagement in data and statistics for students who are blind or have low vision (BLV). B) Throughout the co-design process, participants engaged in several inquiry-based activities exploring introductory statistical concepts of distribution and center using both low- and high-tech tools. C) Participants then incorporated knowledge-forming practices synthesized throughout the sessions into the design of their own learning activities.

Abstract

Statistical literacy involves understanding, interpreting, and critically evaluating statistical information in a contextually grounded way. Current instructional practices rely heavily on visual techniques, which renders them inaccessible to students who are blind or have low vision (BLV). To bridge this gap, we formed an extended co-design partnership with a statistics teacher, a teacher for students with visual impairments (TVI), and two BLV students to develop accessibility-first practices for building statistical literacy. Through several months of collaboration that included discussion, exploration, design, and evaluation, we identified specific approaches to promote comprehension and engagement. The enactive approaches we designed, using scaffolding and timely feedback, fostered insights through pattern recognition and analogical reasoning. Additionally, inquiry-based methods promoted contextually situated reasoning and reflection on how statistics can improve students’ lives and communities. We present these findings alongside participants’ experiences and discuss their implications for inclusive learning frameworks and tools.


Papers

Danyang Fan, Olivia Tomassetti, Aya Mouallem, Gene SH Kim, Shloke Nirav Patel, Saehui Hwang, Patricia Leader, Danielle Sugrue, Tristen Chen, Darren Reese Ou, Victor R Lee, Lakshmi Balasubramanian, Hariharan Subramonyam, Sile O’Modhrain and Sean Follmer. Promoting Comprehension and Engagement in Introductory Data and Statistics for Blind and Low-Vision Students: A Co-Design Study. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI’25). https://dl.acm.org/doi/10.1145/3706598.3713333