Abstract
This work explores whether audio feedback style and user ability influences user techniques, performance, and preference in the interpretation of node graph data among sighted individuals and those who are blind or visually impaired. This study utilized a posttest-only basic randomized design comparing two treatments, in which participants listened to short audio clips describing a sequence of transitions occurring in a node graph. The results found that participants tend to use certain techniques and have corresponding preferences based on their ability. A correlation was also found between equivalently high feedback design performance and lack of overall feedback design preference. These results imply that universal technologies should consider avoiding utilizing design constraints that allow for only one optimal usage technique, especially if that technique is dependent on a user’s ability.
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Acknowledgments
The authors would like to thank the National Science Foundation and Arizona State University for their funding support. This material is partially based upon work supported by the NSF under Grant No. 1828010.
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Darmawaskita, N., McDaniel, T. (2020). Understanding Pattern Recognition Through Sound with Considerations for Developing Accessible Technologies. In: Stephanidis, C., Antona, M., Gao, Q., Zhou, J. (eds) HCI International 2020 – Late Breaking Papers: Universal Access and Inclusive Design. HCII 2020. Lecture Notes in Computer Science(), vol 12426. Springer, Cham. https://doi.org/10.1007/978-3-030-60149-2_17
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DOI: https://doi.org/10.1007/978-3-030-60149-2_17
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