Collaborative Research: An Intelligent Natural Language Interface to Improve the Accessibility of Complex Data Tasks for Blind or Visually Impaired STEM Employees
- Institution
- Northeastern University, MA
- Principal investigator
- Hari Prasath Palani
- Funding
- $833K
- Duration
- 2024–2027
Moonbase score
Still being scored
Abstract
Researchers at Northeastern University, the University of Maine, and Colby College are conducting research focused on developing and testing a technology-based solution that improves the accessibility of spreadsheet data tasks for blind and low vision (BLV) STEM employees. Data tasks include data exploration, data manipulation, and data analysis, which are often inaccessible to BLV employees due to the visual attributes of commonly used data tools and the limitations of current keyboard-based functions. Through this research, keyboard functions will be enhanced with the addition of natural language-based functions, resulting in an intuitive and accessible approach to performing complex data tasks. Proficiency in the use of data is foundational for many STEM jobs. This project addresses a longstanding accessibility issue faced by BLV employees in STEM fields Employing a user-centered approach, this project has three phases: 1) establish design considerations and guidelines for developing BLV-focused natural language (NL) interfaces that can facilitate data analytics tasks, 2) develop a prototype NL interface to support BLV users to perform data analytics tasks on STEM-specific datasets, and 3) empirically measure the practical utility of the prototype system for its ability to support BLV users in performing these data tasks and assess its acceptability and usability among target end users. With BLV STEM professionals and researchers involved across all aspects of the research, the methods include interviews, co-design workshops, Wizard of Oz prototyping, and experimental evaluation. The results of this research will be a prototype of an intelligent natural language-based system, called Auxel, that will support BLV STEM professionals with spreadsheet data tasks. This award has been made in response to the NSF solicitation “Workplace Equity for Persons with Disabilities in STEM and STEM Education” (NSF 23-593). The Directorate funds this project for Social, Behavioral and Economic Sciences’ Office of Multidisciplinary Activities and the Division of Graduate Education’s EDU CORE Research program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Hari Prasath PalaniPI
- Nicholas Giudice
- Melanie Tory
LOADING MOONBASE SCORE
Questions for Northeastern University
Answered by the team behind this research.
No questions yet. Sign in to ask the first one
Related grants
Same researchers, same institution, same topic, scored first.
- NSF · University of MaineNot yet scored
HCC: Medium: Multisensory maps for inclusive indoor navigation by people with visual impairments
Nicholas Giudice · $1.1M · 2023–2026
- NSF · University of MaineNot yet scored
Proto-OKN Theme 1: Safe Agricultural Products and Water Graph (SAWGraph): An OKN to Monitor and Trace PFAS and Other Contaminants in the Nation's Food and Water Systems
Torsten Hahmann · $1.5M · 2023–2026
- NSF · Saint Louis UniversityNot yet scored
NSF Convergence Accelerator Track H: Addressing the Fragmented Information Access Problem - A Community-Driven, AI-Powered Platform for Multimodal Content Creation
Jenna L Gorlewicz · $5.0M · 2023–2026