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• Inclusion as a Process: Co-Designing an Inclusive Robotic Game with Neurodiverse Classrooms

  Patricia Piedade, Isabel Neto, Ana Cristina Pires, Rui Prada, Hugo Nicolau · 2024 · Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '24)

  This paper documents a seven-month co-design process in which researchers worked with 80 children (18 of whom were neurodivergent) across four neurodiverse classrooms in Lisbon, Portugal, to design an inclusive tabletop robotic game. The children, aged 6 to 12, included those…

  neurodiversity · children · co-design · inclusive play · robotics

• Towards Designing Digital Learning Tools for Students with Cortical/Cerebral Visual Impairments: Leveraging Insights from Teachers of the Visually Impaired

  Adele Smolansky, Miranda Yang, Shiri Azenkot · 2024 · Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '24)

  This paper investigates how digital learning tools should be designed to support students with cortical/cerebral visual impairment (CVI), a neurological condition that affects the brain's ability to process visual information rather than the eyes themselves. CVI is now the most…

  cortical visual impairment · education · digital learning tools · visual impairment · assistive technology

• Beadwork Bridge: Understanding and Exploring the Opportunities of Beadwork in Enriching School Education for Blind and Low Vision (BLV) People

  Shumeng Zhang, Weiyue Lin, Zisu Li, Ruiqi Jiang, Chen Liang, Mingming Fan, Raul Masu · 2024 · ASSETS '24: Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper investigates how beadwork — the craft of creating patterns and objects by threading beads onto wire, string, or thread — serves as a rich educational tool for blind and low-vision (BLV) students, and explores what the HCI field can learn from these established…

  blind and low vision · education · beadwork · tactile learning · embodied cognition

• Using Convolutional Neural Networks for Visual Sign Language Recognition: Towards a system that provides instant feedback to learners of sign language

  Rami Aldahir, Ronald R. Grau · 2024 · Proceedings of the 21st International Web for All Conference (W4A)

  This short paper presents a prototype system that uses computer vision and a convolutional neural network (CNN) to recognize finger-spelled letters in British Sign Language (BSL), providing real-time feedback to learners. The system addresses a gap in sign language instruction:…

  sign language · British Sign Language · computer vision · deep learning · fingerspelling

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