arXiv subjects

Zinat Ara

Publications and source records attributed to Zinat Ara.

5 recordsLinked to original sources

arXiv2026

Understanding ADHD Productivity in Construction Work: Toward AI-enabled VR Interventions

Attention-Deficit/Hyperactivity Disorder (ADHD) is identified as the most prevalent neurodivergent condition in the construction industry. While the construction industry may broaden employment opportunities, little is known about how ADHD traits shape workers' performance, sustained attention, and situational awareness in dynamic job-site environments. This work presents an exploratory interview study aimed at understanding how ADHD traits influence construction-specific productivity and how future interventions can reduce challenges while amplifying strengths. We conducted semi-structured interviews with construction workers with ADHD, safety managers, and ADHD researchers to capture their perspectives on attentional demands, task coordination, and workplace adaptation. As part of these discussions, participants also reflected on the potential of combining artificial intelligence (AI) and virtual reality (VR) to support future ADHD workers. Our analysis identifies two overarching themes: (1) workplace challenges, capturing difficulties that arise from both the nature of construction work and the specific needs of ADHD workers, and (2) productivity support strategies, describing effective methods to sustain focus and task engagement. Further, we derive design requirements for AI and VR-enabled interventions that provide adaptive attentional scaffolding, mediated social presence, and motivational support. We conclude by discussing how these insights can inform the future development of ADHD productivity enhancement support.

cs.HC↗

arXiv2026

Characterizing Creativity in Data Visualization: Reflections and Future Directions

Characterizing creativity in visualization design can lead to the design of more expressive representations and visualization authoring tools that prioritize human creativity. In this paper, we examine how creativity manifests itself in visualization design processes through two complementary studies. First, a systematic review of 63 papers yields a design space spanning three themes: creative design frameworks that focus on developing design processes by incorporating divergent and convergent thinking activities, creative visual representations that focus on developing unorthodox visualizations, and visualization-enabled creativity support tools that focus on supporting a creative task (e.g., writing) with visualization. Second, we conducted qualitative interviews with 11 visualization practitioners and researchers to understand practical challenges and contrast those with current academic framing through our design space. The interview findings indicate that artifacts or final products (unorthodox visualizations) are often disproportionately considered as the primary indicator of creativity, whereas the design process remains undervalued in practical and organizational contexts. We also found that ideation is a universal bottleneck, and organizational constraints are often the primary barrier to creative work. We discuss implications for rethinking the relationship between our design space categories, addressing organizational barriers, and designing future frameworks, tools, and evaluation methods that better support creativity in the age of AI-assisted visualization. The full list of coded papers is available here: https://vizcreativity.notion.site/coded-papers.

cs.HC↗

arXiv2025

You Are Not Alone: Designing Body Doubling for ADHD in Virtual Reality

Adults with Attention Deficit Hyperactivity Disorder (ADHD) experience challenges sustaining attention in the workplace. Body doubling, the concept of working alongside another person, has been proposed as a productivity aid for ADHD and other neurodivergent populations (NDs). However, prior work found no conclusive effectiveness and noted NDs' discomfort with social presence. This work investigates body doubling as an ADHD centered productivity strategy in construction tasks. In Study 1, we explored challenges ADHD workers face in construction and identified design insights. In Study 2, we implemented a virtual reality bricklaying task under three conditions: (C1) alone, (C2) with a human body double, and (C3) with an AI body double. Results from 12 participants show they finished tasks faster and perceived greater accuracy and sustained attention in C2 and C3 compared to C1. While body doubling was clearly preferred, opinions diverged between conditions. Our findings verify its effect and offer design implications for future interventions.

cs.HC↗

arXiv2024

Collaborative Job Seeking for People with Autism: Challenges and Design Opportunities

Successful job search results from job seekers' well-shaped social communication. While well-known differences in communication exist between people with autism and neurotypicals, little is known about how people with autism collaborate with their social surroundings to strive in the job market. To better understand the practices and challenges of collaborative job seeking for people with autism, we interviewed 20 participants including applicants with autism, their social surroundings, and career experts. Through the interviews, we identified social challenges that people with autism face during their job seeking; the social support they leverage to be successful; and the technological limitations that hinder their collaboration. We designed four probes that represent major collaborative features found from the interviews--executive planning, communication, stage-wise preparation, and neurodivergent community formation--and discussed their potential usefulness and impact through three focus groups. We provide implications regarding how our findings can enhance collaborative job seeking experiences for people with autism through new designs.

cs.HC↗

arXiv2024

Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems

Data annotation interfaces predominantly leverage ground truth labels to guide annotators toward accurate responses. With the growing adoption of Artificial Intelligence (AI) in domain-specific professional tasks, it has become increasingly important to help beginning annotators identify how their early-stage knowledge can lead to inaccurate answers, which in turn, helps to ensure quality annotations at scale. To investigate this issue, we conducted a formative study involving eight individuals from the field of disaster management, each possessing varying levels of expertise. The goal was to understand the prevalent factors contributing to disagreements among annotators when classifying Twitter messages related to disasters and to analyze their respective responses. Our analysis identified two primary causes of disagreement between expert and beginner annotators: 1) a lack of contextual knowledge or uncertainty about the situation, and 2) the absence of visual or supplementary cues. Based on these findings, we designed a Context interface, which generates aids that help beginners identify potential mistakes and provide the hidden context of the presented tweet. The summative study compares Context design with two widely used designs in data annotation UI, Highlight and Reasoning-based interfaces. We found significant differences between these designs in terms of attitudinal and behavioral data. We conclude with implications for designing future interfaces aiming at closing the knowledge gap among annotators.

cs.HC↗