research-article

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Teaching American Sign Language in Mixed Reality

Authors:

Julien Blanchet,

Megan E. Hillis,

Themistoklis K. Haris,

Jason Lamberton,

Melissa Malzkuhn,

Lorna C. Quandt,

David J. M. Kraemer,

Devin BalkcomAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 4, Issue 4

Article No.: 152, Pages 1 - 27

https://doi.org/10.1145/3432211

Published: 18 December 2020 Publication History

Abstract

This paper presents a holistic system to scale up the teaching and learning of vocabulary words of American Sign Language (ASL). The system leverages the most recent mixed-reality technology to allow the user to perceive her own hands in an immersive learning environment with first- and third-person views for motion demonstration and practice. Precise motion sensing is used to record and evaluate motion, providing real-time feedback tailored to the specific learner. As part of this evaluation, learner motions are matched to features derived from the Hamburg Notation System (HNS) developed by sign-language linguists. We develop a prototype to evaluate the efficacy of mixed-reality-based interactive motion teaching. Results with 60 participants show a statistically significant improvement in learning ASL signs when using our system, in comparison to traditional desktop-based, non-interactive learning. We expect this approach to ultimately allow teaching and guided practice of thousands of signs.

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Index Terms

Teaching American Sign Language in Mixed Reality
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Embedded systems
2. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 4, Issue 4

December 2020

1356 pages

EISSN:2474-9567

DOI:10.1145/3444864

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Copyright © 2020 ACM.

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Published: 18 December 2020

Published in IMWUT Volume 4, Issue 4

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Shao QOkoshi TKo JLiKamWa R(2024)Weaving Physical and Physiological Sensing with Computational FabricsProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661385(748-750)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661385
Alam MLamberton JWang JLeannah CMiller SPalagano JBastion MSmith HMalzkuhn MQuandt L(2024)ASL champ!: a virtual reality game with deep-learning driven sign recognitionComputers & Education: X Reality10.1016/j.cexr.2024.1000594(100059)Online publication date: 2024
https://doi.org/10.1016/j.cexr.2024.100059
Imashev AKydyrbekova AOralbayeva NKenzhekhan ASandygulova A(2024)Learning sign language with mixed reality applications - the exploratory case study with deaf studentsEducation and Information Technologies10.1007/s10639-024-12525-1Online publication date: 23-Feb-2024
https://doi.org/10.1007/s10639-024-12525-1
Patibandla RRao BRao DRamakrishna Murthy M(2024)Reshaping the Future of Learning Disabilities in Higher Education with AIApplied Assistive Technologies and Informatics for Students with Disabilities10.1007/978-981-97-0914-4_2(17-33)Online publication date: 29-May-2024
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