Book chapter
Designing Mobile Tasks to Improve Art Description Accessibility for People with Visual Impairments
ArtsIT, Interactivity and Game Creation, pp.224-247
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer International Publishing
02/10/2022
DOI: 10.1007/978-3-030-95531-1_16
Abstract
All people should be able to experience museums, but there are barriers for people with visual impairments (VIs) including few museums that have accessibility accommodations and having to plan their visit. There are museum and technical efforts to supply accessible experiences, but they require curation by experts, making it difficult for these solutions to scale. To address this problem, we used the Art Beyond Sight (ABS) Accessibility Guidelines as a framework to develop mobile tasks to guide laypeople in composing accessible artwork descriptions. We compared the ratings of 31 people with VIs and four docents on curations from Amazon’s Mechanical Turk between two approaches: 1) baseline tasks inspired from prior museum HCI research, and 2) our designed tasks. Both people with VIs and docents rated the second descriptions higher than the first in understandability and adherence to the ABS Accessibility Guidelines. The second descriptions vivid details and orientation information. Our work shows the potential to bring these tasks to a museum space.
Details
- Title: Subtitle
- Designing Mobile Tasks to Improve Art Description Accessibility for People with Visual Impairments
- Creators
- Megan Corbett - University of IowaJeehan Malik - University of IowaVero Rose Smith - Greenfield Community CollegeKyle Rector - University of Iowa
- Resource Type
- Book chapter
- Publication Details
- ArtsIT, Interactivity and Game Creation, pp.224-247
- Publisher
- Springer International Publishing; Cham
- Series
- Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
- DOI
- 10.1007/978-3-030-95531-1_16
- eISSN
- 1867-822X
- ISSN
- 1867-8211
- Language
- English
- Date published
- 02/10/2022
- Academic Unit
- Computer Science
- Record Identifier
- 9984259475602771
Metrics
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