This research paper explores the intersectionality of disabled students in engineering education, with a novel focus on using music as a reflective tool during the research process. Drawing from intersectionality frameworks - which emphasize the compounded nature of identities such as race, class, gender, sexuality, ethnicity, nationality, disability status, age, and geographical location - this study investigates the unique ways in which disabled students with multiple marginalized identities navigate through undergraduate engineering. Semi-structured interviews were conducted with seventeen disabled undergraduate engineering students over the 2023–2024 school year. At the end of each interview, students were asked to select songs that represented their experiences in engineering as individuals with multiple marginalized identities. The analysis of their chosen songs and the lyrics' relevance to their personal narratives provided a deeper understanding of the intersections of sexism, ableism, and capitalism within their educational experiences. The full paper expands on how music served not only as a method for eliciting rich, qualitative data but also as a reflective tool for both interviewees and researchers.

This work-in-progress innovative practice paper builds on existing studies highlighting the significant lack of diversity in the field of artificial intelligence (AI),with a particular emphasis on the role of identity in shaping biases, inequalities, and ethical considerations within AI systems. As AI becomes increasingly integrated into society, it is essential to critically examine its impact on disabled individuals. This paper advocates for the adoption of an anti-ableist framework, emphasizing the inclusion of disability perspectives throughout the AI development and deployment processes. Central to this position is a critical examination of the AI identity ecosystem, which includes the creators of AI, the technologies they produce, and the societal implications of these technologies-all viewed through a lens that prioritizes disability rights and perspectives. We introduce a conceptual framework designed to center disability within the AI ecosystem, particularly in educational settings. This framework aims to teach students the importance of accessibility and anti-ableism in AI, equipping them with the tools to integrate these principles throughout their work. By promoting an anti-ableist approach and integrating accessibility education, this paper seeks to inform future policies and initiatives in human-centered AI. It contributes to the ongoing discourse on ethical AI, urging a reevaluation of how disability is integral to AI's identity and its future trajectory.

Students with disabilities*, including those in engineering, are well known to face a multitude of challenges, including social, physical, emotional, and economic barriers, while navigating higher education. Institutional policies and practices are key drivers to the functioning of a university and, as such, play an important role in the protections, experiences, inclusion, and support of disabled students. This Work-in-Progress Research paper reviews institutional disability-related policies and practices at five U.S. higher education institutions. The five institutions were selected to represent a range of institutional types (private vs. public), geographic locations, and sizes (of their engineering programs). Building on the University Disability Inclusion Dashboard developed by The Johns Hopkins Disability Health Research Center, we focus our analysis on two specific aspects of institutional policies and practices: (1) accommodations for disabled students and (2) public image around disability inclusion. Our analysis found that vagueness within the accommodations process and limitations to publicly available information contributes to weakened robustness in the accommodations, support, and protections currently provided to disabled students across universities. This research represents a needed first step to assess the current state of structural, institutional support (or lack thereof) for disabled students in engineering. *In this paper, we chose to rotate between the usage of the terms “students with disabilities” (SWDs) and “disabled students” in an attempt to include all students and their identity-first or person-first language preferences.

This Work-in-Progress, Research paper presents the experiences of three engineering students who navigate STEM education with multiple marginalized identities. Using the Social Identity Wheel as a framework, the study aims to fill gaps in intersectionality research by exploring the positionality and experiences of these marginalized students in STEM. This paper showcases the practical application of the Social Identity Wheel in computing and engineering education research, particularly for studies with small sample sizes, to guide in participant selection and data interpretation techniques. The findings underscore the significance of incorporating intersectional perspectives in all forms of educational research and the importance in understanding the complexities of intersectionality. The research questions guiding this study are: (1) How can the use of the Social Identity Wheel be used to further contextualize and explore the positionality and experiences of marginalized students in STEM? and (2) In what ways does the interplay of one's non-visible identities and visible identities intersect to shape their STEM experience?

This Work in Progress, Research paper aims to address the well-documented discrimination against people with disabilities regarding the use of technology in education. Poor accessibility standards, a lack of administrative support, and numerous other barriers have contributed to the ever-present digital equity gap for students with disabilities. The digital equity gap has continued to widen as schools continue to increase the use of virtual or distance learning in the wake of the COVID-19 pandemic. This research aims to better understand students with disabilities’ barriers in accessing online undergraduate engineering education by addressing the following research question: What barriers do engineering students with disabilities face in an online learning environment? The Universal Design for Learning (UDL) framework guides the research questions, data collection, and data analysis. A fixed item survey has been developed and is currently being used to capture the experiences of students with disabilities in engineering who participated in online learning at four-year colleges and universities across the United States. The identification of these students’ barriers will be used to inform accessibility improvements and considerations to engineering online learning.