Ather Sharif

Computing students with disabilities face a variety of difficulties in computing education and careers including inaccessible technology, difficulty arranging accommodations, attitudinal barriers, and a lack of mentors. This panel of computing students and recent graduates with disabilities will describe their experiences both in and out of the classroom. The goal is to provide the audience with an opportunity to hear first-hand how their educational needs were met as non-traditional computing students. In addition to the panelists' short presentations, the moderator will facilitate a dialog between the members of the audience and the panelists. 1 Summary Because of the 1975 Individuals with Disabilities Education Act (IDEA), the Rehabilitation Act of 1973, Section 504, and the Americans with Disabilities Act of 1990 (ADA) more and more students with disabilities are pursuing degrees in computing fields. As a result, teachers of computer science are more likely now than in the past to have a blind, low-vision deaf, hard of hearing, mobility disabled, or cognitively disabled students in our classrooms and research labs. And yet, we do not have systematic data about the representation of students with disabilities in postsecondary education [1] and many programming tools remain inaccessible to these students [2]. The purpose of this panel is for educators to learn first-hand from students about their educational needs and how they can be met. 2 Panel Structure The panel will consist of four diverse students and recent graduates with disabilities moderated by Richard Ladner. The panelists will make 10-minute presentations that include the following:  Demographic information: name, academic background, disability, and future goals.  Description of accessibility needs in their computing classes and other academic activities, such as office hours and group projects.  Description of how those needs were met at the university-, department-, and instructor-level.

In graduate school, people with disabilities use disability accommodations to learn, network, and do research. However, these accommodations, often scheduled ahead of time, may not work in many situations due to uncertainty and spontaneity of the graduate experience. Through a three-person autoethnography, we present a longitudinal account of our graduate school experiences as people with disabilities, highlighting nuances and tensions of situations when our requested accommodations did not work and the use of alternative coping strategies. We use retrospective journals and field notes to reveal the impact of our self-image, relationships, technologies, and infrastructure on our disabled experience. Using post-hoc reflection on our experiences, we then close with discussing personal and situated ways in which peers, faculty members, universities, and technology designers could improve the graduate school experiences of people with disabilities.

For over six decades, Fitts's law (1954) has been utilized by researchers to quantify human pointing performance in terms of "throughput, " a combined speed-accuracy measure of aimed movement efficiency. Throughput measurements are commonly used to evaluate pointing techniques and devices, helping to inform software and hardware developments. Although Fitts's law has been used extensively in HCI and beyond, its test-retest reliability, both in terms of throughput and model ft, from one session to the next, is still unexplored. Additionally, despite the fact that prior work has shown that Fitts's law provides good model fits, with Pearson correlation coefficients commonly at r =.90 or above, the model fit-ness of Fitts's law has not been thoroughly investigated for people who exhibit limited fine motor function in their dominant hand. To fill these gaps, we conducted a study with 21 participants with limited fine motor function and 34 participants without such limitations. Each participant performed a classic reciprocal pointing task comprising vertical ribbons in a 1-D layout in two sessions, which were at least four hours and at most 48 hours apart. Our findings indicate that the throughput values between the two sessions were statistically significantly different, both for people with and without limited fine motor function, suggesting that Fitts's law provides low test-retest reliability. Importantly, the test-retest reliability of Fitts's throughput metric was 4.7% lower for people with limited fine motor function. Additionally, we found that the model ftness of Fitts's law as measured by Pearson correlation coefcient, r , was .89 (SD=0.08) for people without limited fine motor function, and .81 (SD=0.09) for people with limited fine motor function. Taken together, these results indicate that Fitts's law should be used with caution and, if possible, over multiple sessions, especially when used in assistive technology evaluations.

Graphs are considered as one of the most important tools to represent information, and as such, they are widely used across the Internet in various formats to visualize statistics and data. However, for the visually impaired individuals, who can presently rely only on the ALT attribute of images, receiving and interpreting information displayed in graphs is a highly challenging task. This paper presents a novel solution to this problem, called evoGraphs, which is a jQuery plugin that allows users to create fully dynamic, customizable graphs that are easily read by screen readers. In contrast to traditional images, the proposed approach relies on HTML, CSS and jQuery components in order to create graphs while reducing page load time and making the graphs readable by voiceover software applications and screen readers. This paper presents the design and customization of evo-Graphs. Examples are provided to highlight the advantages of the proposed methodology by comparing page load times of traditional image-based graphs with those produced by evoGraphs.