A persistent challenge in accessible computing is ensuring developers produce web UI code that supports assistive technologies. Despite numerous specialized accessibility tools, novice developers often remain unaware of them, leading to ~96% of web pages that contain accessibility violations.
AI coding assistants, such as GitHub Copilot, could offer potential by generating accessibility-compliant code, but their impact remains uncertain. Our formative study with 16 developers without accessibility training revealed three key issues in AI-assisted coding: failure to prompt AI for accessibility, omitting crucial manual steps like replacing placeholder attributes, and the inability to verify compliance.
To address these issues, we developed CodeA11y, a GitHub Copilot Extension, that suggests accessibility-compliant code and displays manual validation reminders. We evaluated it through a controlled study with another 20 novice developers. Our findings demonstrate its effectiveness in guiding novice developers by reinforcing accessibility practices throughout interactions, representing a significant step towards integrating accessibility into AI coding assistants.
Prior research on the experiences of students with disabilities in higher education has surfaced a number of barriers that prevent full inclusion. Generative artificial intelligence (GenAI) has begun to attract interest for its potential to address longstanding barriers to access. However, little is known about the impact of these tools on the living and learning experiences of post-secondary students with disabilities. As a mixed-abilities team, we investigated student experiences with GenAI tools by collecting survey and interview responses from 62 and 21 students with disabilities, respectively, across two universities to measure students' use of GenAI tools and their perspectives on the impact of these tools in ways related to disability, university support, and sense of belonging. Despite concerns over potential risks of GenAI and unclear university policies, students described GenAI tools as a useful resource for personalizing learning, promoting self-care, and assisting with important self-advocacy work. Guidance demonstrating safe, acceptable uses of GenAI tools, along with clear policies and resources that acknowledge diverse student needs, were desired. We discuss implications of these tools for accessibility and inclusion in higher education.
PDF inaccessibility is an ongoing challenge that hinders individuals with visual impairments from reading and navigating PDFs using screen readers. This paper presents a step-by-step process for both novice and experienced users to create accessible PDF documents, including an approach for creating alternative text for mathematical formulas without expert knowledge. In a study involving nineteen participants, we evaluated our prototype PAVE 2.0 by comparing it against Adobe Acrobat Pro, the existing standard for remediating PDFs. Our study shows that experienced users improved their tagging scores from 42.0% to 80.1%, and novice users from 39.2% to 75.2% with PAVE 2.0. Overall, fifteen participants stated that they would prefer to use PAVE 2.0 in the future, and all participants would recommend it for novice users. Our work demonstrates PAVE 2.0's potential for increasing PDF accessibility for people with visual impairments and highlights remaining challenges.
Existing commercial and in-house software development tools are often inaccessible to blind and low vision software professionals (BLVSPs), hindering their participation and career growth at work. Building on existing research on Do-It-Yourself (DIY) assistive technologies and customized tools made by programmers, we shed light on the currently unexplored intersection of how DIY tools built and used by BLVSPs support accessible software development. Through semi-structured interviews with 30 BLVSPs, we found that such tools serve many different purposes and are driven by motivations such as desiring to maintain a professional image and a sense of dignity at work. These tools had significant impacts on workplace accessibility and revealed a need for a more centralized community for sharing tools, tips, and tricks. Based on our findings, we introduce the "Double Hacker Dilemma" and highlight a need for developing more effective peer and organizational platforms that support DIY tool sharing.
People rely on online information for important life tasks such as managing personal finances and understanding medical symptoms. However, due to its intrinsically language-focused nature, online search poses considerable difficulties for people with language impairments. Currently these difficulties are poorly understood. We report findings from an observation of the information search behavior of 12 people with aphasia. We identify a wide range of difficulties and strategies aimed at combating them, spanning the entire information search process. Findings include previously unreported difficulties and strategies that highlight the importance of designing search technologies to better support the complex needs of people who find language challenging, such as by facilitating word finding cueing strategies, error prevention and recovery, browsing, appropriation, text interpretation and and by decreasing reliance on language competency in general. This has the potential not only to benefit searchers with language impairments, but to make information search easier for all.
Deceptive design patterns manipulate people into actions to which they would otherwise object. Despite growing research on deceptive design patterns, limited research examines their interplay with accessibility and visual accessibility technology (e.g., screen readers, screen magnification, braille displays). We present an interview and diary study with 16 people who use visual accessibility technology to better understand experiences with accessibility and deceptive design. We report participant experiences with six deceptive design patterns, including designs that are intentionally deceptive and designs where participants describe accessibility barriers unintentionally manifesting as deceptive, together with direct and indirect consequences of deceptive patterns. We discuss intent versus impact in accessibility and deceptive design, how access barriers exacerbate harms of deceptive design patterns, and impacts of deceptive design from a perspective of consequence-based accessibility. We propose that accessibility tools could help address deceptive design patterns by offering higher-level feedback to well-intentioned designers.
Today’s mapping tools fail to address the varied experiences of different mobility device users. This paper presents a large-scale online survey exploring how five mobility groups—users of canes, walkers, mobility scooters, manual wheelchairs, and motorized wheelchairs—perceive sidewalk barriers and differences therein. Using 52 sidewalk barrier images, respondents evaluated their confidence in navigating each scenario. Our findings (N=190) reveal variations in barrier perceptions across groups, while also identifying shared concerns. To further demonstrate the value of this data, we showcase its use in two custom prototypes: a visual analytics tool and a personalized routing tool. Our survey findings and open dataset advance work in accessibility-focused maps, routing algorithms, and urban planning.