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• Contextual Scaffolding and Self-Efficacy: Supporting Computer Skill Development among Blind Learners in India

  Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This paper presents a four-month contextual inquiry at two Indian computer training centers serving 94 blind or visually impaired (BVI) students — one urban center in Bengaluru focused on job-oriented ICT training (KEONICS certification) and one rural residential blind school in…

  screen readers · blind and low vision · computer literacy · Global South accessibility · India

• Building Care That Fits Its People: Insights from Social Media-Enabled Community-Based Rehabilitation in Thailand

  Acarima Nanthanasit, Sophia Ppali, Wan-Jou She, Panote Siriaraya, Thammathip Piumsomboon, Siwaporn Sukittanon, Chee Siang Ang, Alexandra Covaci · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper reports on a six-month, multi-platform social media intervention for Community-Based Rehabilitation (CBR) of stroke patients in rural Chiang Mai, Thailand. The authors co-designed content with clinicians, Village Health Volunteers (VHVs), and community…

  Community-Based Rehabilitation · digital health · social media · Global South accessibility · stroke recovery

• Human-Centered Explainable AI for Brain-Computer Interface-driven Rehabilitation

  Param Rajpura · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA ’26)

  This CHI Extended Abstract presents a doctoral research agenda developing human-centered explainable AI (HCXAI) frameworks for brain-computer interfaces (BCIs) used in stroke rehabilitation. Rajpura argues that current BCI systems prioritize technical performance, such as…

  brain-computer interface · explainable AI · stroke rehabilitation · aphasia · human-centered AI

• VisionAid: A Multimodal Assistive Application Supporting Safe Road Navigation for Visually Impaired People in Bangladesh

  Asif Mahbub, Nabil Bin Hannan · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA ’26)

  VisionAid is an Android pedestrian-safety app for blind and low vision (BLV) users in Bangladesh, where road crossing is dangerous because traffic is unstructured: lane discipline is rare, drivers run signals, and crosswalks are inconsistent. The authors argue that…

  blind and low vision · pedestrian navigation · mobile accessibility · computer vision · haptic feedback

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