Using multimedia to enhance the accessibility of the learning environment for disabled students: reflections from the Skills for Access project

As educators' awareness of their responsibilities towards ensuring the accessibility of the learning environment to disabled students increases, significant debate surrounds the implications of accessibility requirements on educational multimedia. There would appear to be widespread concern that the fundamental principles of creating accessible web‐based materials seem at odds with the creative and innovative use of multimedia to support learning and teaching, as well as concerns over the time and cost of providing accessibility features that can hold back resource development and application. Yet, effective use of multimedia offers a way of enhancing the accessibility of the learning environment for many groups of disabled students. Using the development of ‘Skills for Access’, a web resource supporting the dual aims of creating optimally accessible multimedia for learning, as an example, the attitudinal, practical and technical challenges facing the effective use of multimedia as an accessibility aid in a learning environment will be explored. Reasons why a holistic approach to accessibility may be the most effective in ensuring that multimedia reaches its full potential in enabling and supporting students in learning, regardless of any disability they may have, will be outlined and discussed

Evaluating the Usability of Automatically Generated Captions for People who are Deaf or Hard of Hearing

The accuracy of Automated Speech Recognition (ASR) technology has improved, but it is still imperfect in many settings. Researchers who evaluate ASR performance often focus on improving the Word Error Rate (WER) metric, but WER has been found to have little correlation with human-subject performance on many applications. We propose a new captioning-focused evaluation metric that better predicts the impact of ASR recognition errors on the usability of automatically generated captions for people who are Deaf or Hard of Hearing (DHH). Through a user study with 30 DHH users, we compared our new metric with the traditional WER metric on a caption usability evaluation task. In a side-by-side comparison of pairs of ASR text output (with identical WER), the texts preferred by our new metric were preferred by DHH participants. Further, our metric had significantly higher correlation with DHH participants' subjective scores on the usability of a caption, as compared to the correlation between WER metric and participant subjective scores. This new metric could be used to select ASR systems for captioning applications, and it may be a better metric for ASR researchers to consider when optimizing ASR systems.Comment: 10 pages, 8 figures, published in ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '17

Avoiding communication barriers in the classroom: the APEINTA project

Education is a fundamental human right, however unfortunately not everybody has the same learning opportunities. For instance, if a student has hearing impairments, s/he could face communications barriers in the classroom, which could affect his/her learning process. APEINTA is a Spanish educational project that aims for inclusive education for all. This project proposes two main accessible initiatives: (1) real-time captioning and text-to-speech (TTS) services in the classroom and (2) accessible Web-learning platform out of the classroom with accessible digital resources. This paper presents the inclusive initiatives of APEINTA. Also an evaluation of the into-the-classroom initiative (real-time captioning and TTS services) is presented. This evaluation has been conducted during a regular undergraduate course at a university and during a seminar at an integration school for deaf children. Forty-five hearing students, 1 foreign student, 3 experts in captioning, usability and accessibility, and 20 students with hearing impairments evaluated these services in the classroom. Evaluation results show that these initiatives are adequate to be used in the classroom and that students are satisfied with them.Publicad

Improving fairness in machine learning systems: What do industry practitioners need?

The potential for machine learning (ML) systems to amplify social inequities and unfairness is receiving increasing popular and academic attention. A surge of recent work has focused on the development of algorithmic tools to assess and mitigate such unfairness. If these tools are to have a positive impact on industry practice, however, it is crucial that their design be informed by an understanding of real-world needs. Through 35 semi-structured interviews and an anonymous survey of 267 ML practitioners, we conduct the first systematic investigation of commercial product teams' challenges and needs for support in developing fairer ML systems. We identify areas of alignment and disconnect between the challenges faced by industry practitioners and solutions proposed in the fair ML research literature. Based on these findings, we highlight directions for future ML and HCI research that will better address industry practitioners' needs.Comment: To appear in the 2019 ACM CHI Conference on Human Factors in Computing Systems (CHI 2019

Crowdsourcing Accessibility: Human-Powered Access Technologies

People with disabilities have always engaged the people around them in order to circumvent inaccessible situations, allowing them to live more independently and get things done in their everyday lives. Increasing connectivity is allowing this approach to be extended to wherever and whenever it is needed. Technology can leverage this human work force to accomplish tasks beyond the capabilities of computers, increasing how accessible the world is for people with disabilities. This article outlines the growth of online human support, outlines a number of projects in this space, and presents a set of challenges and opportunities for this work going forward

Determining Accessibility for iOS Applications: Piloting a Checklist for Practitioners

Background: Mobile technologies have infiltrated every part of daily life, including the school system. While these technologies are highly customizable, there are 6.4 million children with disabilities who may not be able to utilize these devices because of their lack of accessibility. The iOS Application Accessibility Checklist (iA2C) is a “first of its kind” tool, used to determine if an iOS app is accessible for users with a variety of disabilities. Hypothesis: When using the iA2C, novice users with little experience in accessible design will determine apps to have a statistically similar number of accessibility features as experts, assessing the app in the same way. Additionally, users will better be able to rank apps, based on accessibility, when using the iA2C. Method: Fifteen participants assessed a total of six apps. They evaluated three apps with the use of the iA2C and three without. Apps were matched across groups as educational, classroom support or entertainment apps. The assessments addressed both the positive and negative features of the app. Novice ratings were then compared to a “gold standard” rating created from a collaborative evaluation of three experts. Experts assessed the apps in the same way as the novices. Groups were statistically compared using 1-sample t-tests. Results: When the participants assessed the apps without the iA2C, there was a significant difference between novices and experts for all assessments. However, when apps were assessed using the iA2C, no significant differences was observed between expert and novice ratings for the number of positive features present in the entertainment app and the accessibility features absent in educational and classroom support apps. Discussion: Results of this small preliminary study suggests that novice participants may be more likely to assess an app similar an expert, when using the iA2C. The tool needs to undergo continued modifications to meet the changing technology and user demands. Additionally, future testing needs to be conducted regarding the measure in order to increase the power of the findings