The next decade in accessibility research

Author:

Gerling Kathrin1,Rauschenberger Maria2,Tannert Benjamin3,Weber Gerhard4

Affiliation:

1. 150232 Karlsruhe Institute of Technology (KIT) , Karlsruhe , Germany

2. 38976 University of Applied Science Emden/Leer , Emden , Germany

3. 38966 Hochschule Bremen, Institut für Digitale Teilhabe , Bremen , Germany

4. Fakultät Informatik , 9169 Technische Universität Dresden , Dresden , Germany

Abstract

Abstract Accessibility research has matured over the last three decades and developed a better understanding of accessibility technologies, design and evaluation methods, systems and tools as well as empirical studies in accessibility. We envision how progress in new contexts over the next decade can be made to develop stronger links to other areas in Human-Centered Computing and address the research communities. A human-centered perspective on disability needs to develop from a medical model to a social model. New methods will utilize generative AI in design and development processes that address accessibility from the start of system design. We build on AI embedded into future design processes to address participation of small numbers of users better, and new technologies to allow for personalization of multi-modal interaction to improve verbal and non-verbal communication, making body-centric computing and natural interaction truly accessible.

Publisher

Walter de Gruyter GmbH

Reference42 articles.

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2. Rous, B. Major Update to ACM’s Computing Classification System. Commun. ACM 2012, 55 (11), 12. https://doi.org/10.1145/2366316.2366320.

3. Kelly, M.; McDonnell, E.; Jain, D.; Wang, L. L.; Froehlich, J. E.; Findlater, L. What Do We Mean by “Accessibility Research”? A Literature Survey of Accessibility Papers in CHI and ASSETS from 1994 to 2019. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21); Association for Computing Machinery: New York, NY, USA, 2021; p. 18.

4. Yesilada, Y., Harper, S., Eds. Web Accessibility; Springer: London, 2019.

5. Koller, O. Quantitative Survey of the State of the Art in Sign Language Recognition, 2020. arXiv:2008.09918 [cs.CV].

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