Background and Context: Advances in treatment have led to a growing population of cancer survivors, many of whom experience disease and treatment-related cognitive and physical effects that shape how they interact with software. Cancer-related impairments are rarely discussed in computing curricula, yet incorporating this context into accessibility education broadens students’ understanding of inclusive design while preparing them to address real-world, treatment-induced barriers affecting a substantial and growing user population.

While accessibility education for designing for people with disabilities has become more common in university computing classrooms, instruction focused on designing for neurodivergent users remains limited. In this work, we developed accessibility games to teach students about accessible design for neurodivergent users and evaluated them on 43 students in a university Human-Computer Interaction course. Students found the games to be engaging and learned about designing accessible solutions for neurodivergent individuals. Some challenges emerged in terms of making the games more universal across languages and cultures.

Teaching accessibility is an essential step towards supporting the integration of accessibility principles in software and other technologies, especially as ADA Title II regulations increase awareness around educational accessibility considerations.While existing literature captures the prevalence of accessibility in computing curriculums, understanding how accessibility can be taught across different disciplines is critical to effective accessibility education.This interdisciplinary workshop invites researchers and educators to discuss approaches to teaching accessibility in different disciplines, especially with respect to Title II compliance.Through sharing experiences and lessons learned, this workshop consolidates accessibility education methods while analyzing the role of teaching accessibility in developing accessible courses, classrooms, and technologies.

Accessibility is a critical topic in computing education, yet its integration into K-12 curricula has been limited. This gap highlights a significant need to introduce knowledge, awareness, and empathy regarding the challenges people with disabilities face with inaccessible software to K-8 students, as well as to present accessible software solutions. We conducted interviews with 21 K-8 students to gauge their current accessibility knowledge, observed their performance when playing simulation games developed to teach accessibility, and asked them about their experience with the gameplay and its impact on their accessibility awareness. Our findings revealed a notable lack of accessibility education in current K-8 curricula. However, after engaging with the accessibility games, participants showed a marked increase in their curiosity and awareness of the need for accessible design. Our study advances the goal of integrating accessibility education into early computer science education to foster a more inclusive future technological landscape.

Cancer survivors experience a wide range of impairments arising from cancer or its treatment, such as chemo brain, visual impairments, and physical impairments. These impairments degrade their quality of life and potentially make software use more challenging for them. However, there has been limited research on designing accessible software for cancer survivors, despite the rich literature on CSCW technologies for cancer survivors. To bridge this research gap, we conducted a formative study including a survey (n=46), semi-structured interviews (n=20), and a diary study (n=10) with cancer survivors. Our results revealed a wide range of impairments experienced by cancer survivors, including chemo brain, neuropathy, and visual impairments. Cancer survivors heavily relied on software for socialization, health purposes, and cancer advocacy, but their impairments made software use more challenging for them. Based on the results, we offer a set of accessibility guidelines that software designers can utilize when creating applications for cancer survivors. Further, we suggest design features for inclusion, such as health resources, socialization tools, and games, tailored to the needs of cancer survivors. This research aims to spotlight cancer survivors' software accessibility challenges and software needs and invite more research in this important yet under-investigated domain.

Teaching accessibility is crucial to ensuring that accessibility principles are integrated into the design and adoption of software and other aspects of lives. The existing literature on accessibility education is largely siloed, appearing primarily in computer science and related disciplines. Understanding the similarities and differences in teaching accessibility across different disciplines is vital for enhancing educational effectiveness by leveraging lessons learned from each field. This workshop aims to serve as an interdisciplinary forum for researchers and education practitioners to discuss topics taught, approaches taken, resources utilized, and challenges encountered when teaching accessibility in different disciplines.

Accessibility continues to be a priority in computer science education, but the goals for accessibility education are non-standardized. We examine whether evaluation measures differ by disability, and whether accessibility training for some disabilities can translate to a different disability. In our work, 71 students played three accessibility simulation games. We evaluated both student empathy and their generation of accessibility design solutions pertaining to those three disabilities, as well as a fourth disability not portrayed in the games. Our findings indicate that though empathy and accessibility ideas increased for all three taught disabilities, only empathy improved for the fourth disability. We further found that initially, students had a harder time generating accessibility solutions for less relatable disabilities, but that difference disappeared after playing simulation games. Finally, we found that student empathy and ability to generate design solutions were positively correlated only before playing simulation games, suggesting that after obtaining a stronger understanding of accessibility, the effects of empathy on student design solutions are no longer as prominent. Overall, these findings suggest that simulations may inspire empathy even for disabilities not portrayed but should be supplemented with educational content about how to design accessibly for all.

Neurodiversity affects about 15-20% of the population and neurodiverse users can struggle with software usability. However, there are few initiatives geared at educating about accessibility for neurodiversity. We begin conversation about this topic by synthesizing accessibility guidelines for some of the neurodiverse population -- people on the autism spectrum, people with dyslexia and people with ADHD -- and giving guidelines about teaching about accessibility for neurodiverse users.

There is a great need to train future software developers in accessibility, and disability simulations can be a powerful way to engage students. In this work, we evaluate the effects of disability simulation games on student empathy and design choices. To do this we recruited 124 students and randomized them into two conditions: students playing simulation games and a control group of students who learned accessibility topics through a video lecture and readings. Although the accessibility lecture and readings were effective at inspiring student empathy towards people with disabilities, the effects were short-lived; in contrast, the simulations inspired greater and longer-lasting empathy and consideration of people with disabilities. However, more work should be done to determine whether these gains influence students' inclusion of people with disabilities in practice.

In order to increase empathy and foster conversation around accessibility, we created three games, simulating disabilities, that are geared towards engaging beginner CS and non-CS students to learn about accessibility. Each game has four rounds: game mode, simulation mode, game+accessibility mode, and simulation+accessibility mode. We tested the games on 113 students from two universities and report on performance and survey results that show that playing our games induced student empathy towards people with disabilities and motivated them towards accessible design.

We show that the Adaptive Greedy algorithm of Golovin and Krause achieves an approximation bound of (ln(Q/η)+1) for Stochastic Submodular Cover: here Q is the “goal value” and η is the minimum gap between Q and any attainable utility value Q'

We developed an educational serious game to teach basic cybersecurity concepts to novices. An evaluation of the game on introductory Computer Science and Business students suggests that playing the game resulted in both short-term learning gains in cybersecurity as well as longer-term retention of the concepts. We also saw evidence that students who played the game had increased interest in cybersecurity, and students self-reported interest in playing the game to learn more about and assess their knowledge of cybersecurity.

We developed a 3D serious game that teaches and reinforces programming concepts. An innovative feature allows instructors to create customized challenges that students solve in the context of the game, allowing instructors to use the game to effectively target course topics or skills. A web-based portal gives instructors access to data about student performance in the game.

University students graduating and entering into technology design and development fields are underprepared to support digital accessibility due to a lack of awareness and training. Teach Access is a consortium of 10 industry partners, 5 advocacy groups, and 20 university partners working to address this issue. In an attempt to bridge the gap between what is taught to students and the increasing demand from industry, the initiative described here was aimed at awarding instructor grants to support the development of accessibility modules in tech-related courses. In our study we surveyed student attitudes toward accessibility pre- and post-instruction of these modules, as well as, instructor strategy. We found that across all courses, student confidence in accessibility-related concepts increased. The largest increases were found in student confidence in defining the Americans with Disabilities Act (ADA) and the Web Content Accessibility Guidelines (WCAG). Our work makes the following contributions: 1) A detailed description of how accessibility was integrated into 18 different university and college courses 2) Instructional delivery methods found to be effective by participating instructors 3) Insights for resource materials development.

Consider the following Stochastic Score Classification Problem. A doctor is assessing a patient's risk of developing a certain disease, and can perform n tests on the patient. Each test has a binary outcome, positive or negative. A positive result is an indication of risk, and a patient's score is the total number of positive test results. Test results are accurate. The doctor needs to classify the patient into one of B risk classes, depending on the score (e.g., LOW, MEDIUM, and HIGH risk). Each of these classes corresponds to a contiguous range of scores. Test i has probability p_i of being positive, and it costs c_i to perform. To reduce costs, instead of performing all tests, the doctor will perform them sequentially and stop testing when it is possible to determine the patient's risk category. The problem is to determine the order in which the doctor should perform the tests, so as to minimize expected testing cost. We provide approximation algorithms for adaptive and non-adaptive versions of this problem, and pose a number of open questions.

We report our experience teaching elective game development courses at two colleges at a public university. Over the past nine years these courses have been taught in a variety of languages on several platforms. As the courses evolved we introduced serious games with game-based-learning as a focus for the projects and ultimately offered a special topics elective in serious game development. In this paper, we discuss the merits of using serious games as a focus in game programming, including the benefits for students without a strong interest in gaming. We also describe the novel restructuring of one college's Computer Science elective sequence in response to recommendations from students, alumni, and an advisory board of computing professionals. By introducing 200-level electives, students are able to sample advanced topics including game development early in their academic sequence. This has led to involving more students in game-based undergraduate research which can result in increased interest and retention in Computer Science. We discuss our curriculum design and lessons learned including challenges and successes, and data from student surveys indicating student motivation and engagement.

Deshpande et al. presented a k(ln R + 1) approximation bound for Stochastic Submodular Cover, where k is the state set size, R is the maximum utility of a single item, and the utility function is integer-valued. This bound is similar to the ln Q/(eta+1) bound given by Golovin and Krause, whose analysis was recently found to have an error. Here Q >= R is the goal utility and eta is the minimum gap between Q and any attainable utility Q' < Q. We revisit the proof of the k(ln R + 1) bound of Deshpande et al., fill in the details of the proof of a key lemma, and prove two bounds for real-valued utility functions: k(ln R_1 + 1) and (ln R_E + 1). Here R_1 equals the maximum ratio between the largest increase in utility attainable from a single item, and the smallest non-zero increase attainable from that same item (in the same state). The quantity R_E equals the maximum ratio between the largest expected increase in utility from a single item, and the smallest non-zero expected increase in utility from that same item. Our bounds apply only to the stochastic setting with independent states.

We present a new approximation algorithm for the stochastic submodular set cover (SSSC) problem called adaptive dual greedy . We use this algorithm to obtain a 3-approximation algorithm solving the stochastic Boolean function evaluation (SBFE) problem for linear threshold formulas (LTFs). We also obtain a 3-approximation algorithm for the closely related stochastic min-knapsack problem and a 2-approximation for a variant of that problem. We prove a new approximation bound for a previous algorithm for the SSSC problem, the adaptive greedy algorithm of Golovin and Krause. We also consider an approach to approximating SBFE problems using the adaptive greedy algorithm, which we call the Q -value approach. This approach easily yields a new result for evaluation of CDNF (conjunctive / disjunctive normal form) formulas, and we apply variants of it to simultaneous evaluation problems and a ranking problem. However, we show that the Q -value approach provably cannot be used to obtain a sublinear approximation factor for the SBFE problem for LTFs or read-once disjunctive normal form formulas.

We present approximation algorithms for two problems: Stochastic Boolean Function Evaluation (SBFE) and Stochastic Submodular Set Cover (SSSC). Our results for SBFE problems are obtained by reducing them to SSSC problems through the construction of appropriate utility functions. We give a new algorithm for the SSSC problem that we call Adaptive Dual Greedy. We use this algorithm to obtain a 3-approximation algorithm solving the SBFE problem for linear threshold formulas. We also get a 3-approximation algorithm for the closely related Stochastic Min-Knapsack problem, and a 2-approximation for a natural special case of that problem. In addition, we prove a new approximation bound for a previous algorithm for the SSSC problem, Adaptive Greedy. We consider an approach to approximating SBFE problems using existing techniques, which we call the Q-value approach. This approach easily yields a new result for evaluation of CDNF formulas, and we apply variants of it to simultaneous evaluation problems and a ranking problem. However, we show that the Q-value approach provably cannot be used to obtain a sublinear approximation factor for the SBFE problem for linear threshold formulas or read-once DNF.