TableView: Enabling Efficient Access to Web Data Records for Screen-Magnifier Users
Hae-Na Lee, Sami Uddin, Vikas Ashok · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020) · doi:10.1145/3373625.3417030
Summary
This paper addresses a significant usability challenge faced by people with low vision who use screen magnifiers to browse the web: the difficulty of comparing data records on websites such as job listings, flight search results, shopping products, and restaurant listings. Because screen magnifiers enlarge only a portion of the screen at a time, users must repeatedly pan back and forth across the page to compare attributes of different items — a process that is cognitively demanding, physically tiring, and error-prone. The authors first conducted a semi-structured interview study with 16 low-vision participants (visual acuity ranging from 20/100 to 20/500) to document the specific pain points of interacting with web data records through a screen magnifier. Participants reported excessive panning to revisit previously viewed records, inability to remember attribute values across records, difficulty distinguishing visited from unvisited links, and fatigue that caused them to stop reviewing records prematurely — often missing better options. Based on these findings, the authors designed and developed TableView, a Chrome browser extension that uses the STEM (suffix tree-based extraction method) algorithm to automatically detect and extract data records from webpages, then presents them in a compact two-dimensional table within a popup overlay. This tabular format significantly reduces the screen area that needs to be panned, packing more records into the magnifier viewport simultaneously. TableView also includes an attribute filter feature that lets users select which columns to display, further reducing horizontal panning.
Key findings
In a within-subject user study with the same 16 low-vision participants, TableView dramatically reduced the time needed to navigate and compare data records. On unfamiliar websites, task completion times dropped by 72.9% compared to using a screen magnifier alone, and by 66.5% compared to a state-of-the-art space compaction method. On familiar websites (Amazon), reductions were 66.4% and 56.1% respectively. All differences were statistically significant (Kruskal-Wallis test, p < 0.001). The NASA Task Load Index scores showed a 65.9% reduction in cognitive workload compared to screen magnifier alone, and 55.4% compared to space compaction. The SUS usability scores were significantly higher for TableView conditions (ANOVA, F = 186.67, p < 0.00001). Error rates also decreased substantially: 26 errors with screen magnifier alone versus only 2 with TableView plus attribute filters. Participants with tunnel vision (e.g., from glaucoma) found the tabular layout especially beneficial, as it allowed them to scan content by moving in a single direction rather than searching the entire viewport. The attribute filter feature proved particularly valuable, letting users focus on the specific attributes that mattered most for their comparison task.
Relevance
This research highlights a critical but often overlooked accessibility gap: while screen readers for blind users receive significant research attention, screen magnifier usability for people with low vision remains understudied. The findings demonstrate that simply enlarging content is insufficient — the spatial layout of information creates substantial barriers for magnifier users. For web developers and designers, this paper underscores the importance of considering how data-rich pages (product listings, search results, comparison tables) are experienced through magnification. The TableView approach of extracting and restructuring content into compact tabular formats offers a compelling model for assistive technology development. The study also reveals that low-vision users employ sophisticated but exhausting cognitive strategies to manage information overload, suggesting that tools supporting information filtering and comparison could significantly improve web accessibility for this population.
Tags: low vision · screen magnifier · web accessibility · usability · browser extension · data records · information extraction · assistive technology