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Improving Information Accessibility with Sign Language First Technology

This project takes a human-centered computing approach to build a foundation that advances understanding of how deaf individuals could work and learn in environments that are designed with their needs and preferences at the forefront.

Positions

We are recruiting PhD, MS and undergraduate students (including MQP, IQP) to work on this project.

We encourage applicants for graduate studies from the Deaf community for this project. This project is in close collaboration with Jeanne Reis and the Center for Research and Training at the Learning Center for the Deaf. Researchers will be joining a strong Deaf community there.

Prospective Graduate Students: Apply here! (Funded as Research/Teaching Assistant)

In addition to computer science, WPI also has graduate programs in data science, learning sciences, and interactive media and game design. If you are interested in this research project, but are not sure which program is best, don't hesitate to reach out to me and we can discuss which one is right for you.

WPI's Computer Science department in Worcester, MA (an hour outside of Boston) is an exciting place to study human-computer interaction, with outstanding faculty and a wonderful community. If you are applying to one of the graduate programs, and are interested in working in my group, make sure to indicate this as well as your research interests in your essay.

Related Publications

Jeanne Reis, Erin T. Solovey, Jon Henner, Kathleen Johnson, Robert Hoffmeister. ASL CLeaR: STEM Education Tools for Deaf Students. Proc. ASSETS’15. (Poster paper) ACM. 2015.

NSF Award Abstract

In the United States, American Sign Language (ASL) is the primary language of many deaf adults, and many deaf students receive classroom instruction in ASL while learning English as a second language. However, most interactive computing tools are presented and navigated exclusively in English, even those designed for deaf audiences. Making access to technology contingent upon a sufficient command of a second language creates significant barriers and access delays for deaf individuals.

This project takes a human-centered computing approach to build a foundation that advances understanding of how deaf individuals could work and learn in environments that are designed with their needs and preferences at the forefront. It investigates the feasibility and effectiveness of new SL1 technology, which will provide delivery of signed language (SL) content by allowing deaf signers to navigate, search, and interact with technology completely in their first language (L1). The optimization of SL1-based user interfaces has never before been attempted and could lead to a breakthrough in historic communication and learning barriers; determining preferences, needs and optimized presentation of information for Deaf users will benefit this population and future populations of ASL signers.

Technology that is truly accessible to deaf SL-signers has the power to facilitate lifelong learning, enhance access to educational content such as STEM topics, improve career opportunities, and allow SL-based organization of SL corpora, assessments, dictionaries, learning and employment resources. This work will directly impact deaf individuals, parents, interpreters, teachers, and students studying SL. Direct collaboration with deaf graduate and undergraduate students, deaf faculty, and deaf researchers, along with several partner schools for the deaf will ensure that the Deaf community has an instrumental leadership role in the design of future tools that meet their needs.

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