Tools and Applications for Cognitive Accessibility

This session reflects R&D on User Centered Design and Development and User Participation (in short UCD in the following) for/with people with disabilities. Better guidelines, methods, techniques and tools are needed to improve the quality of R&D and practice both in the domain of Assistive Technology (AT), eAccessibility and eInclusion itself but also for improving the quality of mainstream R&D through UCD and participation of people with disabilities. We analyze the state of the art, identify gaps and problems as well as discuss examples and new approaches presented in 5 papers. The introduction integrates the topic into the broader context of UCD in Information and Communication Technology (ICT) and Human-Computer Interaction (HCI) playing a major role for AT, eAccessibility and digital inclusion. We underline the need for ongoing and more intense R&D on UCD to improve quality and usability. By promoting this session in the ICCHP conference series we aim at establishing a comprehensive point of access to scientific work in this domain.

Section: At/accessibility/hci/ict and Ucdmentioning

confidence: 99%

“…R&D still tend to be more “about” then “with” people with disabilities what risks lower quality of output and restricted uptake. Recent studies provide evidence both on these gaps but on the other hand also on the benefits of UCD leading to increased quality of R&D [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

User Centered Design and User Participation in Inclusive R&D

Miesenberger

Edler

Dirks

et al. 2020

“…Often creativity, methods and tools to support communication and interaction to adequately involve the target group are missing. There is also a lack of access and support for the target group in developing digital media [ 6 , 18 ].…”

Section: State Of the Artmentioning

confidence: 99%

IPAR-UCD – Inclusive Participation of Users with Cognitive Disabilities in Software Development

Edler¹

2020

This article presents a new inclusive research concept for research and development (R&D) IPAR-UCD. An adaptation for collaborative R&D with peer-researchers for cognitive accessibility is still missing. This inclusive research concept investigates and combines two methodological approaches: Inclusive Participatory Action Research, IPAR [ 1 ] and User-Centered Design, UCD. With this inclusive research and development method, a concept is presented that has already been successfully applied and further developed in the »Easy Reading« project (ER) itself, together with the target group [ 2 , 14 ].

“…These tools embed alternative easy-to-read or clarified content directly into the original Web document being visited when the user requests it, thereby enabling persons with a cognitive disability to independently browse the Web. Access methods may be tailored to the specific users based on personal data, generally created by supporting staff or educators [ 8 ]. Besides these semi-automatic tools, current approaches to making websites accessible to people with cognitive and learning impairments still mostly rely on manual adaptations performed by human experts [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…Access methods may be tailored to the specific users based on personal data, generally created by supporting staff or educators [ 8 ]. Besides these semi-automatic tools, current approaches to making websites accessible to people with cognitive and learning impairments still mostly rely on manual adaptations performed by human experts [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Automatic Assistance to Cognitive Disabled Web Users via Reinforcement Learning on the Browser

Murillo-Morales

Heumader

Miesenberger

2020

This paper introduces a proof of concept software reasoner that aims to detect whether an individual user is in need of cognitive assistance during a typical Web browsing session. The implemented reasoner is part of the Easy Reading browser extension for Firefox. It aims to infer the user’s current cognitive state by collecting and analyzing user’s physiological data in real time, such as eye tracking, heart beat rate and variability, and blink rate. In addition, when the reasoner determines that the user is in need of help it automatically triggers a support tool appropriate for the individual user and Web content being consumed. By framing the problem as a Markov Decision Process, typical policy control methods found in the Reinforcement Learning literature, such as Q-learning, can be employed to tackle the learning problem.