Customizable Tabular Access to Web Data Records for Convenient Low-vision Screen Magnifier Interaction

Author:

Lee Hae-Na1ORCID,Ashok Vikas2

Affiliation:

1. Stony Brook University, Stony Brook, NY

2. Old Dominion University, Norfolk, VA

Abstract

To interact with webpages, people with low vision typically rely on screen magnifier assistive technology that enlarges screen content and also enables them to pan the content to view the different portions of a webpage. This back-and-forth panning between different webpage portions makes it especially inconvenient and arduous for screen magnifier users to interact with web data records (e.g., list of flights, products, job advertisements), as this interaction typically involves making frequent comparisons between the data records based on their attributes, e.g., comparing available flights in a travel website based on their prices, durations. To address this issue, we present TableView+, an enhanced version of our previous TableView prototype—a browser extension that leverages a state-of-the-art data extraction method to automatically identify and extract information in web data records, and subsequently presents the information to a screen magnifier user in a compactly arranged data table to facilitate easier comparisons between records. TableView+ introduces new features aimed mostly at addressing the critical shortcomings of TableView, most notably the absence of interface customization options. In this regard, TableView+ enables low-vision users to customize the appearance of the data table based on their individual needs and eye conditions. TableView+ also saves these customizations to automatically apply them to the best extent possible the next time the users interact with the data records on either the same or other similar websites. A user study with 25 low-vision participants showed that with TableView+, the panning time further decreased by 8.5% on unfamiliar websites and by 8.02% on a familiar website than with TableView when compared to a screen magnifier.

Funder

NSF

NIH

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,Human-Computer Interaction

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1. Enabling Efficient Web Data-Record Interaction for People with Visual Impairments via Proxy Interfaces;ACM Transactions on Interactive Intelligent Systems;2023-09-11

2. Inclusive Augmented and Virtual Reality: A Research Agenda;International Journal of Human–Computer Interaction;2023-08-27

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5. Grid-Coding: An Accessible, Efficient, and Structured Coding Paradigm for Blind and Low-Vision Programmers;The 35th Annual ACM Symposium on User Interface Software and Technology;2022-10-28

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