Backend
Beyond Checklist Compliance: A Tale of the Accessibility-Usability Dilemma across Government and Non-Government Web Systems in Bangladesh
arXiv cs.HC0 views
arXiv:2601.00592v2 Announce Type: replace Abstract: Examining whether technical accessibility measures align with users' usability experiences across web systems in Bangladesh is of utmost significance, given the country's rapidly expanding digital ecosystem. We, therefore, evaluated 207 web systems using WAVE, AChecks, and Squidler and surveyed 103 young adult users. Automated evaluation revealed mixed patterns across government and non-government sectors, with neither consistently performing better across accessibility, functionality, web practices, and performance. In contrast, participants clearly favored non-government platforms for navigation, usability, clarity, and cross-device experience. Qualitative analysis identified three barriers to practical access: system instability disrupting task completion, interaction and navigational friction, and socio-technical barriers involving information access, service continuity, and trust. These findings show that automated accessibility measures capture only part of users' experiences. Accessible web services therefore require attention beyond detectable accessibility problems to reliable task progression, understandable interaction, information access, and continuity across the broader service process.
Source:https://arxiv.org/abs/2601.00592PreviousHow K-12 Teachers Adapt Generative AI to Local Classroom Demands: Cultural Distance Between GenAI Defaults and Everyday Teaching PracticesNextAffectGPT-RL: Revealing Roles of Reinforcement Learning in Open-Vocabulary Emotion Recognition
Related posts
DeepSeek's Open-Source "Super-Agent" Codes Without Being Asked
0dev.to GitHub
All-in-one platform or a stack you assemble? Where do coaches and educators land?
0dev.to Discuss
I Wanted to Live on Coruscant. PAT Scared Me. Now My Alexa Lives on Mute.
0dev.to Discuss
Detect What You Can Name: PaliGemma 2 Object Detection with Transformers
0dev.to Machine Learning
When Should an LLM Router Stop Being Sticky? llm-d 1.0 Cache-Affinity Routing, Break-Even Math, and a Simulation
0dev.to Machine Learning

Understanding HackerTube: Karpathy’s Two-Hour Experiment in Better Recommendations
0dev.to Machine Learning