Christian Murphy

In light of the growing "student mental health crisis" and the lingering effects of the COVID-19 pandemic, the field of Computer Science (CS) must address student mental health concerns as it seeks to become more welcoming and accessible to students of all identities and abilities. As these concerns are often related to CS courses, it is necessary to get a sense of instructors' current perspectives before we can understand how to address them: do CS instructors feel responsible for supporting student mental health? do they actually consider it when designing their courses? how do these answers vary depending on instructor demographics? To answer these questions, we conducted a nationwide survey in which 69 CS faculty members shared their perspectives on student mental health. Although a majority of respondents are concerned about student mental health and feel responsible for supporting it, only around half actually do consider it when designing their courses. Further analysis reveals that instructors who identify as living with a mental health condition, women, and faculty members with less than 10 years of experience feel more responsible for supporting student mental health, indicating that there may be significant variations in faculty perspectives on this topic.

As our community seeks to make Computer Science education more accessible amidst a global mental health crisis, we must not overlook the unique needs of students living with ongoing mental health conditions such as anxiety and depression, who are often stigmatized, misunderstood, and marginalized in our field. However, these students' experiences are not uniform: not only is there variation in experience among different mental health conditions, but aspects of students' identity such as their gender, race and ethnicity, sexual orientation, socioeconomic status, etc. also affect their sense of belonging and feelings of accomplishment. Thus, further exploration is needed to better understand these intersectional experiences so that structures and pedagogical approaches can be put in place to help these students thrive. This session seeks to explore ways in which current diversity, equity, inclusion, and accessibility efforts in CS in higher education can be modified to be more inclusive of students living with mental health conditions by considering their intersectional experiences. We seek to create a space for a constructive and open conversation in which we will discuss how current outreach efforts, recruitment and retention strategies, community building, and career advancement can be broadened to meet the unique needs of these students, while at the same time seeking to erase any stigma and misconceptions that may cause others to marginalize and exclude them. Participants will have an opportunity to discuss issues around intersectionality, share resources, and describe efforts to foster a culture of understanding and support.

Exploring the intersection of identity, mental health, and computer science (CS) education, we focus on the unique challenges faced by Asian American students living with mental health conditions such as anxiety and depression. In a nationwide survey, participants shared experiences around mental health stigma and impacts of the model minority myth. Preliminary findings reveal a reluctance among Asian American CS students to address their mental health. This study aims to fill a research gap, helping to identify educational strategies that can support the well-being of students living with mental health conditions in CS.

As our community seeks to make Computer Science education more accessible amidst a global mental health crisis and with many students living with chronic illnesses and other medical conditions, it becomes more and more urgent to address student health concerns in CS classes and in the spaces that we create. Despite the important and long overdue increase in the number of diversity, equity, inclusion, and accessibility (DEIA) initiatives in CS, these efforts run the risk of overlooking the needs of students living with ongoing mental health and medical conditions, who are underrepresented and marginalized in our field. This session seeks to explore ways in which current DEIA efforts in CS in higher education can be expanded to be more inclusive of students living with mental health and medical conditions. We seek to create a space for a constructive and open conversation in which we will discuss how current outreach efforts, recruitment and retention strategies, supportive accommodations, mentorship opportunities, community building, and career advancement can be broadened and modified to meet the unique needs of these students, while at the same time seeking to erase any stigma and misconceptions that may cause others to marginalize and exclude them. Participants will have an opportunity to discuss issues that affect CS students living with mental health and medical conditions, share resources that are available for both students and educators, and describe efforts to create and foster a culture of understanding and support for these communities within our field.

Along with the growing number of students with disabilities in higher education comes an opportunity to explore the difficulties they experience, especially in the post-pandemic era, as well as how to better support them, thus making post-secondary education more inclusive. A considerable amount of research has been done in providing accommodation for students with physical disabilities, but other hindrances to accessibility such as mental health conditions are prone to be overlooked, perhaps in part due to the stigmatization and subjective invisibility of this topic, specifically in rigorous, competitive fields such as Computer Science (CS). In order to bridge this gap, we conducted a nationwide survey in which 53 undergraduate CS students who identify as living with a mental health condition shared their experiences in their CS courses, instructor and TA office hours, interactions with other students, and the rest of the field. This paper summarizes the most common negative and positive experiences, as well as respondents' recommendations for CS instructors, including recognizing these students' struggles, making themselves approachable, and providing flexible formats of lectures and office hours. The results of this study provide a glimpse of the academic lives of CS students living with mental health conditions, so that CS instructors could foster a more inclusive environment by supporting more students in their paths of pursuing higher education.

A pandemia global de COVID-19 teve impacto não apenas na saúde física, mas também na saúde mental, especialmente entre os estudantes universitários. Estudos anteriores demonstraram que estudantes de Ciência da Computação, em particular, já apresentam mais sintomas de ansiedade e depressão do que a população em geral e estudantes de outras áreas. O estudo teve como objetivo medir o impacto da COVID-19 na saúde mental dos estudantes de Ciências da Computação, avaliando a prevalência e fatores associados aos sintomas de ansiedade e depressão, bem como os fatores que mais afetaram o seu bem-estar. Uma pesquisa transversal on-line com foco nas preocupações e impactos da COVID-19 foi projetada. Os Inventários de Ansiedade e de Depressão de Beck foram usados para medir os sintomas de ansiedade e depressão. Os dados foram coletados anonimamente e analisados por meio do software TIBCO Statistica™, por meio de testes não paramétricos. 174 estudantes (135 homens; idade=21,07 ± 2,47 anos) participaram do estudo. A prevalência de sintomas foi de 36,7% para ansiedade e 60,3% para depressão. 81% dos alunos relataram que seu bem-estar foi afetado negativamente pela pandemia, com as preocupações mais relatadas incluindo isolamento social e atraso no progresso acadêmico. Foram encontradas correlações entre sintomas de ansiedade e depressão, relacionamentos sociais fortes, prática regular de exercícios físicos e nível de satisfação dos alunos com seu curso acadêmico. Este artigo lança luz sobre o impacto da pandemia de COVID-19 na saúde mental dos estudantes de Ciência da Computação, sugere maneiras pelas quais eles podem reduzir os sintomas de ansiedade e depressão e melhorar sua saúde mental durante e após a pandemia.

For large, complex software systems, it is typically impossible in terms of time and cost to reliably test the application in all possible execution states and configurations before releasing it into production. One proposed way of addressing this problem has been to continue testing and analysis of the application in the field, after it has been deployed. A practical limitation of many such automated approaches is the potentially high performance overhead incurred by the necessary instrumentation. However, it may be possible to reduce this overhead by selecting test cases and performing analysis only in previously-unseen application states, thus reducing the number of redundant tests and analyses that are run. Solutions for fault detection, model checking, security testing, and fault localization in deployed software may all benefit from a technique that ignores application states that have already been tested or explored.