Students with disabilities face a variety of challenges in computer science education including those related to stigma around disability, inaccessible curriculum, instruction and tools, disability disclosure, and a lack of mentors. In addition, few computer science classes teach students to understand accessibility and design accessible technology. This BOF will bring together individuals who are interested in increasing the representation of people with disabilities in computing and improving their success as well as those interested in teaching about accessibility. Participants will share strategies to help each other do a better job of addressing disability inclusion and accessibility in our classes and research projects. Resources related to accessible tools and instruction, universal design of learning, opportunities for students, teaching accessibility, and more will be shared.

Most software in the world is not accessible to people with disabilities, in part because most people who create software do not know how to make it accessible. Using the new free online book Teaching Accessible Computing, participants in this special session will learn how they can incorporate accessibility topics into their favorite CS courses, like introductory programming, data structures, or artificial intelligence courses. The editors of the book will lead the special session, and several authors of the book's 17 chapters will talk about their chapters and lead topic groups to go into more depth about how they incorporated accessibility into their CS courses. Participants will leave this session with increased enthusiasm and concrete resources to support teaching accessibility in their CS topic courses, establishing connections to the broader community of CS educators and researchers interested in teaching accessibility.

A growing body of research investigates how to make captioning experiences more accessible and enjoyable to disabled people. However, prior work has focused largely on English captioning, neglecting the majority of people who are multilingual (i.e., understand or express themselves in more than one language). To address this gap, we conducted semi-structured interviews and diary logs with 13 participants who used multilingual captions for accessibility. Our findings highlight the linguistic and cultural dimensions of captioning, detailing how language features (scripts and orthography) and the inclusion/negation of cultural context shape the accessibility of captions. Despite lack of quality and availability, participants emphasized the importance of multilingual captioning to learn a new language, build community, and preserve cultural heritage. Moving toward a future where all ways of communicating are celebrated, we present ways to orient captioning research to a language justice agenda that decenters English and engages with varied levels of fluency.

Disability culture celebrates the diversity disability brings. Its consideration of the positive aspects of the disability experience (community, solidarity, creativity) offers a contrast to many other framings of disability. Disability culture thus has the potential to deepen understandings of accessibility and inform approaches to the design and research of accessibility technologies. To explore this potential, we begin by presenting a preliminary synthesis of disability culture for the accessibility research community, based on works of disability studies scholars and activists. We highlight cultural processes of finding community and building solidarity, valuing disabled agency and knowledge, and rejecting ableist norms. To see how these cultural aspects might inform accessibility technology design, we studied accessibility technologies made by disabled people for disabled people - interviewing disabled innovators who had created and disseminated accessibility technologies. We asked these innovators to share their stories and reflect on goals and values they imbued in their innovations. We analyzed how cultural themes of belonging, knowledge, and creativity influenced their work. Our work highlights the potential of a cultural lens in aligning accessibility technology with disabled people's values as well as unearthing new directions for inquiry for the field.

Demographic data on disability is being collected more and more by computing organizations. However, the meaning of that data can vary drastically depending on the ways that disability is defined (e.g., disabling conditions versus functional limitations) and determined (e.g., by experts or self-reported). In this paper we analyze the varying definitions and determinations of disability and how data about disability is collected by different organizations. We discuss issues associated with certain ways of collecting disability data and offer ways that disability data can be used to inform action towards more inclusive computing education.

There is currently no easy way to look up signs in sign language. Feature-based dictionaries help overcome this challenge by enabling users to look up a sign by inputting descriptive visual features, such as handshape and movement. However, feature-based dictionaries are typically cumbersome, including large numbers of complex features that the user must sort through. In this work, we explore simplifying the set of features used in feature-based American Sign Language (ASL) dictionaries. We present two studies: 1) a simulation study focused on lookup accuracy for various reduced feature sets, and 2) a user study focused on understanding human preferences between feature sets. Our results suggest that it is possible to dramatically reduce the number of features needed to search for signs without significantly impacting the accuracy of search results, and that smaller feature sets can improve the user experience in some cases.

Despite the interest in equity, little research has considered students with disabilities in PreK-12 computer science education. The 2022 Computer Science Teachers Association and Kapor Center facilitated Landscape Survey of PreK-12 CS Teachers, which had over 2200 responses, gives us new insight. There were few significant differences between the experiences and perceptions of teachers with disabilities and those without. Accessibility was the least taught computing concept. Furthermore, teachers reported on a variety of barriers that students with disabilities encounter related to structural barriers, students choosing note to take CS, and teachers' perceptions of student ability. The findings point to the need for interventions related to resources, outreach, and policy.

Little research has examined the aspects of PMs' use among individuals who are blind or visually impaired (BVI) who face extra challenges while entering credentials, such as low typing rates, low typing accuracy, shoulder surfing attacks, and verification of the entered data. This paper explores how knowledgeable BVI individuals are of digital security threats; the status of accessibility in security software; awareness of PMs among BVI; and the factors that drive rejection or adoption of PMs. Our findings revealed that the self-reported knowledge of digital security threats is high; there are many accessibility shortcomings in various security software; and the awareness of PMs among BVI individuals is relatively high, although actual use is far less. About 1/4-th of the participants in the study who tried using PMs rejected them. We found that inaccessibility, cross-platform differences, and security concerns as the top rejection factors. By contrast, convenience, effort saving, and accuracy were the primary adoption factors.

Students with disabilities face a variety of challenges including those related to stigma around disability, inaccessible tools and instruction, disability disclosure, and a lack of mentors. This BOF will bring together individuals who are interested in increasing the representation of students with disabilities in computing and improving their success. Participants will share strategies to help each other do a better job of including these students in our classes and research projects. Resources related to accessible tools and instruction, universal design of learning, opportunities for students, and more will be shared.

The introduction of block-based programming has gradually changed the landscape of programming education, particularly for school children. Block languages today, however, have serious technical barriers to students with disabilities. For example, block languages are generally not screen reader accessible, incompatible with braille, and contain serious problems for users with motor impairments. No student with a disability should ever be denied access to learning computer science and they do not have to be. To help rectify this, we present a new approach to the design of block languages called Quorum Blocks. Quorum Blocks uses a custom hardware accelerated graphical rendering pipeline that takes into account how screen readers and other devices work under the hood. We discuss these technical details and demonstrate that accessibility support can be fully achieved without meaningfully losing either the look of modern blocks or their visual output. We present the results from focus groups that highlight the barriers students faced with a variety of disabilities when using the first version of Quorum Blocks. We focus especially on challenges with low vision users, screen reader users, or those using no mouse and only one hand to type. Block languages built using either our techniques, or on top of our libraries, would become accessible out of the box.

Sign languages are used as a primary language by approximately 70 million D/deaf people world-wide. However, most communication technologies operate in spoken and written languages, creating inequities in access. To help tackle this problem, we release ASL Citizen, the first crowdsourced Isolated Sign Language Recognition (ISLR) dataset, collected with consent and containing 83,399 videos for 2,731 distinct signs filmed by 52 signers in a variety of environments. We propose that this dataset be used for sign language dictionary retrieval for American Sign Language (ASL), where a user demonstrates a sign to their webcam to retrieve matching signs from a dictionary. We show that training supervised machine learning classifiers with our dataset advances the state-of-the-art on metrics relevant for dictionary retrieval, achieving 63% accuracy and a recall-at-10 of 91%, evaluated entirely on videos of users who are not present in the training or validation sets. An accessible PDF of this article is available at the following link: https://aashakadesai.github.io/research/ASLCitizen_arxiv_updated.pdf

Disability and accessibility are often left out of policies and actions related to diversity, equity, and inclusion (DEI). Despite progress on including disability and accessibility in broadening participation in computing (BPC) efforts over the past fifteen years, the idea of including people with disabilities in the groups that are minoritized in computing is still not universal. In this article we document successes in including disability in BPC efforts and where and how improvement can be made. We will argue that without explicitly calling out disability and accessibility, DEI policies and actions replicate the ableism present in our existing institutions.

Speechreading is the art of using visual and contextual cues in the environment to support listening. Often used by d/Deaf and Hard-of-Hearing (d/DHH) individuals, it highlights nuances of rich communication. However, lived experiences of speechreaders are underdocumented in HCI literature, and the impact of online environments and interactions of captioning with speechreading has not been explored in depth. We bridge these gaps through a three-part study consisting of formative interviews, design probes, and design sessions with 12 d/DHH individuals who speechread. Our primary contribution is to understand the lived experience of speechreading in online communication, and thus to better understand the richness and variety of techniques d/DHH individuals use to provision access. We highlight technical, environmental and sociocultural factors that impact communication accessibility, explore the design space of speechreading supports and share considerations for the design future of speechreading technology.

How do we ensure that the next generation of technologists creates computing products that are accessible to people with disabilities? As Computer Science educators, this means raising students' basic awareness and literacy about Accessibility principles and teaching more advanced software design principles so that students are empowered to design hardware and software products that can be used effectively by people who have difficulty reading a computer screen, hearing computer prompts, or controlling the keyboard, mouse, or touchscreen, and more. Accessibility is directly relevant to any course involving human-facing applications such as web and mobile development, software engineering, and human-computer interaction.

Millions of Deaf and hard-of-hearing (DHH) people primarily use a sign language for communication, but there is a lack of adequate sign language interpreting to fill these communication needs. Development of automatic sign language translation (ASLT) systems could help translate between a sign language and spoken language in situations where human interpreters are unavailable, and recent advances in large multi-lingual language models may soon enable ASLT to become a reality. Despite the potential for ASLT, Deaf community perspectives on and requirements for such technologies are poorly understood. In this work, we conduct a survey of Deaf community perspectives in the U.S. on ASLT in order to inform the development of ASLT systems that meet user needs and minimize harms. Our results shed light on scenarios where DHH users in the U.S. might want to use ASLT, their performance expectations for ASLT in these scenarios, design preferences for ASLT interfaces, and the benefits and harms they see in the development of ASLT.

Audio description (AD), an additional narration track that conveys visual information in media, improves video accessibility for blind or low vision (BLV) viewers. Despite being the primary beneficiaries of AD, BLV audiences are limited in how they can contribute to the AD writing process due to technology inaccessibility and societal biases. In this poster, we (1) prototype and test AccessibleAD, an accessible AD writing system, (2) analyze what context and features are valued by BLV description writers, and (3) explore nonvisual involvement in AD creation. This work expands on existing literature regarding audio description and explores best practices for expanding access to AD writing.