arXiv subjects

Andrew Begel

Publications and source records attributed to Andrew Begel.

5 recordsLinked to original sources

arXiv2026

Leveling the Playing Field: Temporal Video Segmentation for Individuals with ADHD in Computing Education

Individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) often face significant barriers in computing education. In asynchronous learning environments, instructional videos can impose high extraneous cognitive load, often relying on assumptions about sustained attention and working memory that do not align with ADHD neurocognitive profiles. In this work, we evaluate a post-hoc video processing intervention that segments instructional content into single-instruction chunks followed by fixed-length pauses to reduce cognitive load. In a within-participants controlled study with 17 individuals with ADHD and 10 without, we find that the intervention has an equalizing effect. Although it improved performance for all participants, gains were larger for those with ADHD, reducing their errors and hesitations to levels comparable to those of participants without ADHD under the same intervention. These results align with the goals of Universal Design for Learning (UDL), by showing that cognitively-aligned, post-hoc instructional video modifications can reduce performance disparities across diverse neurocognitive profiles.

cs.HC↗

arXiv2026

The Three Praxes Framework - A Thematic Review and Map of Social Accessibility Research

Research in social accessibility aims to improve the lives of disabled people across diverse abilities and experiences by assisting with communication, relationships, and ecosystems of access. We seek to understand this intersectional body of work through analyzing social accessibility research from 2011 to 2025. Through constructivist grounded theory analysis of 90 papers (curated from 605), we develop the Three Praxes Framework: three sites of practice Artifact (constructive), Ecosystem (relational), and Epistemology (theoretical) - two cross-cutting stances toward change (Temporal Orientation and Stakeholder Focus) - and one reflexive cycle modeling how insights can flow between praxes. Our analysis reveals these praxes operate largely in isolation, risking that insights remain academic exercises while assistive technologies reinforce existing barriers. We call on the field to realize a cycle where disabled people's lived experiences shape material realities, material practice generates theoretical knowledge, and both transform ecosystems of access.

cs.HC↗

arXiv2026

From Autonomy to Sovereignty - A New Telos for Socially Assistive Technology

Social accessibility research faces a persistent tension: assistive technologies (AT) predominantly pursue independence, yet disabled people's experiences reveal rich preferences for interdependence. Our analysis of 90 papers from 2011-2025 uncovered that this stems from a deeper issue - which crystallized through dialogue with three bodies of theories: (1) self-determination theory (SDT), (2) symbolic interactionism, and (3) posthumanist perspectives and crip technoscience. SDT illuminates individual needs; symbolic interactionism addresses construction of social meaning and stigma; Posthumanist and crip technoscience together challenges normalcy, governance, and the human-machine boundary. Through their tensions, we identify relational sovereignty as an alternative telos - or goal - to autonomy. While our corpus equates autonomy with independence, sovereignty centers the power to choose between independence and interdependence. To operationalize this shift - from "Can they do it?" to "Do they get to decide?" - we introduce the Relational Sovereignty Matrix and four design interventions: (1) a sovereignty-centered reframing of SDT, (2) generative questions for justice-oriented reflection, (3) the idea of building through sovereign technical primitives, and (4) explicit consideration of power in AT design.

cs.HC↗

arXiv2025

"I Hadn't Thought About That": Creators of Human-like AI Weigh in on Ethics And Neurodivergence

Human-like AI agents such as robots and chatbots are becoming increasingly popular, but they present a variety of ethical concerns. The first concern is in how we define humanness, and how our definition impacts communities historically dehumanized by scientific research. Autistic people in particular have been dehumanized by being compared to robots, making it even more important to ensure this marginalization is not reproduced by AI that may promote neuronormative social behaviors. Second, the ubiquitous use of these agents raises concerns surrounding model biases and accessibility. In our work, we investigate the experiences of the people who build and design these technologies to gain insights into their understanding and acceptance of neurodivergence, and the challenges in making their work more accessible to users with diverse needs. Even though neurodivergent individuals are often marginalized for their unique communication styles, nearly all participants overlooked the conclusions their end-users and other AI system makers may draw about communication norms from the implementation and interpretation of humanness applied in participants' work. This highlights a major gap in their broader ethical considerations, compounded by some participants' neuronormative assumptions about the behaviors and traits that distinguish "humans" from "bots" and the replication of these assumptions in their work. We examine the impact this may have on autism inclusion in society and provide recommendations for additional systemic changes towards more ethical research directions.

cs.CY↗

arXiv2024

"It's the only thing I can trust": Envisioning Large Language Model Use by Autistic Workers for Communication Assistance

Autistic adults often experience stigma and discrimination at work, leading them to seek social communication support from coworkers, friends, and family despite emotional risks. Large language models (LLMs) are increasingly considered an alternative. In this work, we investigate the phenomenon of LLM use by autistic adults at work and explore opportunities and risks of LLMs as a source of social communication advice. We asked 11 autistic participants to present questions about their own workplace-related social difficulties to (1) a GPT-4-based chatbot and (2) a disguised human confederate. Our evaluation shows that participants strongly preferred LLM over confederate interactions. However, a coach specializing in supporting autistic job-seekers raised concerns that the LLM was dispensing questionable advice. We highlight how this divergence in participant and practitioner attitudes reflects existing schisms in HCI on the relative privileging of end-user wants versus normative good and propose design considerations for LLMs to center autistic experiences.

cs.HC↗