Browsing by Subject "Accessibility"

Now showing 1 - 5 of 5
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    Keeping Users in the Dark: The Design and Implementation of a Dark Mode for a University Library Website
    (2022-05-25) Maixner, Gary; Smith, Andy
    Dark modes of websites have become a popular feature for users in recent years. While the option to create a contrast mode has existed for decades at the system level, what we are seeing now are designs not only focused on accessibility, but also usability. Library personnel at the Indiana University - Purdue University Indianapolis University Library took it upon themselves to follow this trend and begin the design, development, and implementation of a dark mode version of the library’s website. This involved some trial and error in the initial prototype, taking feedback from users, and then writing the new stylesheet.
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    Not open for all: accessibility of open textbooks
    (Ubiquity Press, 2021) Azadbakht, Elena; Schultz, Teresa; Arellano, Jennifer; Library and Information Science, Luddy School of Informatics, Computing, and Engineering
    In order for open educational resources (OERs) to be truly open to all, they must be accessible to learners with disabilities, including those with visual, auditory, physical and cognitive disabilities. This study sought to determine the accessibility of a randomly selected sample of 355 open textbooks using a custom rubric based upon the World Wide Web Consortium’s (W3C’s) Web Content Accessibility Guidelines (WCAG), version 2.1, primarily at the Levels A and AA. Included books fell into one of four format types: HTML files/websites, PDFs, Microsoft Word documents and EPUBs. The average number of ‘fails’ – instances in which they ran afoul of a rubric category – across the whole sample was 5.93 and the median was 6, out of a total of 14 or 15 categories, depending on the format type. Overall, most of the books did not meet basic accessibility requirements, such as including alternative text for any images, properly coding/tagging any tables and following a logical heading order structure.
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    Universal Design for Learning: Interactive Handout
    (2023-05-03) Santamaría Graff, Cristina; Price, Jeremy F.; Waechter-Versaw, Amy
    This is an interactive handout created by CEISL team members for the purpose of introducing Universal Design for Learning (UDL) in higher education settings as a means to promote equitable, inclusive, and accessible pedagogy for community college courses and programs.
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    Usability and Vibration Analysis of a Low-Profile Automatic Powered Wheelchair to Motor Vehicle Docking System
    (MDPI, 2023) Lee, Chang Dae; Daveler, Brandon J.; Candiotti, Jorge L.; Cooper, Rosemarie; Sivakanthan, Sivashankar; Deepak, Nikitha; Grindle, Garrett G.; Cooper, Rory A.
    The QLX is a low-profile automatic powered wheelchair docking system (WDS) prototype developed to improve the securement and discomfort of wheelchair users when riding in vehicles. The study evaluates the whole-body vibration effects between the proposed QLX and another WDS (4-point tiedown system) following ISO 2631-1 standards and a systematic usability evaluation. Whole-body vibration analysis was evaluated in wheelchairs using both WDS to dock in a vehicle while riding on real-world surfaces. Also, participants rated the usability of each WDS while driving a wheelchair and while riding in a vehicle in driving tasks. Both WDSs showed similar vibration results within the vibration health-risk margins; but shock values below health-risk margins. Fifteen powered wheelchair users reported low task load demand to operate both WDS; but better performance to dock in vehicles with the QLX (p = 0.03). Also, the QLX showed better usability (p < 0.01), less discomfort (p’s < 0.05), and greater security compared to the 4-point tiedown while riding in a vehicle (p’s < 0.05). Study findings indicate that both WDS maintain low shock exposure for wheelchair users while riding vehicles, but a better performance overall to operate the QLX compared to the 4-point tiedown system; hence enhancing user’s autonomy to dock in vehicles independently.
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    Using Social Media Websites to Support Scenario-Based Design of Assistive Technology
    (2020-01) Yu, Xing; Brady, Erin; Palakal, Mathew; Bolchini, Davide; Chakraborty, Sunandan; Hasan, Mohammad
    Having representative users, who have the targeted disability, in accessibility studies is vital to the validity of research findings. Although it is a widely accepted tenet in the HCI community, many barriers and difficulties make it very resource-demanding for accessibility researchers to recruit representative users. As a result, researchers recruit non-representative users, who do not have the targeted disability, instead of representative users in accessibility studies. Although such an approach has been widely justified, evidence showed that findings derived from non-representative users could be biased and even misleading. To address this problem, researchers have come up with different solutions such as building pools of users to recruit from. But still, the data is not widely available and needs a lot of effort and resource to build and maintain. On the other hand, online social media websites have become popular in the last decade. Many online communities have emerged that allow online users to discuss health-related subjects, exchange useful information, or provide emotional support. A large amount of data accumulated in such online communities have gained attention from researchers in the healthcare domain. And many researches have been done based on data from social media websites to better understand health problems to improve the wellbeing of people. Despite the increasing popularity, the value of data from social media websites for accessibility research remains untapped. Hence, my work aims to create methods that could extract valuable information from data collected on social media websites for accessibility practitioners to support their design process. First, I investigate methods that enable researchers to effectively collect representative data from social media websites. More specifically, I look into machine learning approaches that could allow researchers to automatically identify online users who have disabilities (representative users). Second, I investigate methods that could extract useful information from user-generated free-text using techniques drawn from the information extraction domain. Last, I explore how such information should be visualized and presented for designers to support the scenario-based design process in accessibility studies.