206
Views
5
CrossRef citations to date
0
Altmetric
Research Papers

Modeling web-based information seeking by users who are blind

, , , &
Pages 511-525 | Published online: 08 Jun 2011
 

Abstract

Purpose. This article describes website information seeking strategies used by users who are blind and compares those with sighted users. It outlines how assistive technologies and website design can aid users who are blind while information seeking.

Method. People who are blind and sighted are tested using an assessment tool and performing several tasks on websites. The times and keystrokes are recorded for all tasks as well as commands used and spatial questioning.

Results. Participants who are blind used keyword-based search strategies as their primary tool to seek information. Sighted users also used keyword search techniques if they were unable to find the information using a visual scan of the home page of a website. A proposed model based on the present study for information seeking is described.

Conclusions. Keywords are important in the strategies used by both groups of participants and providing these common and consistent keywords in locations that are accessible to the users may be useful for efficient information searching. The observations suggest that there may be a difference in how users search a website that is familiar compared to one that is unfamiliar.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 340.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.