It is the latest product from the W3C’s Cognitive and Learning Disabilities Task Force. It is a tour de force and literally years in the making!
I could not be more proud of our task force.
I could not be more proud of our task force.
Bring together experts in:
to explore the potential of maps for the Web.
Follow all the latest updates on @a11y_bos on Twitter.
This is a conference about making technology accessible, especially the web. It is an opportunity for programmers, designers, developers, students, usability professionals, accessibility experts, and end-users to share information and learn from each other.
2019 sponsors include my own program, INDEX, which has free information about programs, providers, and services for people with disabilities in Massachusetts. See DisabilityInfo.org. We build accessible web applications and online courses. See INDEX Technical Services. We also develop mass-scale, artificial-intelligence-driven Web text simplification for people with cognitive disabilities. See EasyText.AI.
I will soon present part of my AI-Driven Web Text Simplification research.
We tested if people with intellectual disabilities understand Web text simplified with plain-language standards. (Spoiler: They do!)
We are operationalizing plain-language standards essentially to develop:
For my AI-Driven Web Text Simplification research, I lead a coalition of corporate and academic partners. They include:
Make Web text so simple people understand it the first time they read it.
Text comprises the vast majority of Web content. Poor reading comprehension presents significant challenges to many populations, including people with cognitive disabilities, non‐native speakers, and people with low literacy.
Text simplification aims to reduce text complexity while retaining its meaning. Manual text simplification research has been ongoing for decades. Yet no significant effort has been made to automate text simplification except as a preprocessor for natural-language processing tasks such as machine translation and summarization.
In the short term, my partners and I are improving manual text simplification by creating effective, replicable methods for humans to produce it. We use national and international plain language standards. We conduct pilot studies to see if people comprehend our human-curated, simplified Web text better than typical Web text.
In the long term, my partners and I are developing artificial intelligence (AI) capabilities to produce simple Web text on a mass scale. We are training AI with enormous sets of aligned sentence pairs (typical/simple). We will soon start crowd-sourcing the generation of training data.
I will provide details in future blog posts.
Using a website search tool is difficult for people with cognitive disabilities. Finding a relevant result is often thwarted by spelling errors they make, their inability to detect them, or a lack of understanding about how to correct them. Determining which search results are best can be equally difficult.
This post is a synopsis of an approach to circumventing such problems. An example has been implemented on a web site of the German Institute for Human Rights, which is an easy-to-read version of a United Nations convention on the rights of people with disabilities. A typically-appearing site search incorporates novel spelling-correction features and a simplified presentation of search results.
The site search suggests spelling alternatives only for words that actually appear within the content of the website. Searches for correctly-spelled words that produce no search results would be very frustrating for anyone.
To enable spelling suggestions, a manually-edited index of syntactically-similar words was created. Point values were assigned for similarities in the number of the same letters and the word length. A higher value was given to alternative words with the same first letter, but that was not essential.
To enable search-word spelling correction within the fewest steps possible, the most-similar alternatives are displayed in a word cloud. Of those, typically three, the one with the highest probability of matching the intended search word is presented in a larger text size.
The German word for “contact” is “kontakt”. Initiating a search with the misspelled word “kontat” produces a word cloud as shown in the following image.
The developers believe the word cloud makes it very easy to recognize the correctly-spelled word, and to select a search word. I don’t know why the first letters are capitalized.
Search results are presented in plain language. Each has a bulleted, succinct summary of information on the linked page; and a contextually-relevant image to aid comprehension.
The following image shows a single search result translated from German to English using Google Translate.
One aspect of the search results I do not favor is that links to the search-result pages are not underlined. It is only when the cursor is hovered over a link, such as “Contact” in the example search result, that an underline appears.
I am impressed with this approach. This is the first time I have seen search results presented so simply, and with accompanying relevant imagery. I think the spelling-correction features are also worthwhile. In a pilot study of them, 9 of 34 people with learning disabilities could use the search site independently. I expect the developers will continue user testing. With funding and time, I would like to develop a site search using similar techniques.
I am working on a project to make the website, of a university program for people with learning disabilities, more usable by prospective students. Small groups of faculty and students were shown the first mockup last week. Listed below is their feedback and brief descriptions of a few possible remediation efforts.
I am working on a project to make the website of a local university, which has a campus-based program for students with learning disabilities, more usable by them. The current site is designed for parents of prospective students and professionals who serve them. We anticipate our work will make the site easier to use and to understand for everyone.
Over the past few months, an adjunct faculty member has reduced the amount of content, simplified its language, and reorganized it. I created a functional site mockup to demonstrate that work. Yesterday, we showed it to a small group of students, then to a small group of faculty.
Our attempt to separate content into small chunks produced more pages. This exacerbated a problem experienced by the students, which was that navigating the many layers of the site is perplexing. Moreover, faculty indicated frustration with having to click many links to find desired information.
The current first-year curriculum page contains short descriptions for twenty courses. For the mockup, we moved each description to its own page, reducing the curriculum page to a list of course titles. This design requires extra clicks to see course descriptions. As well, the groups indicated the curriculum page is still too long.
We will next shorten the curriculum page by dividing it into sub-pages by topic. One- to two sentence descriptions of the courses under their titles may obviate the need for extra clicks to view more-detailed information. We will know if this has achieved any success only after testing with students.
Overall, I am describing an approach designed to resolve a larger dilemma. How can we provide information about the program in a simple way for students while also supplying a level of detail that may be required by professionals, parents, and even the students themselves? I suppose this is an adventure to find out.
I believe it is common knowledge that providing feedback while teaching is very important. In particular, positive reinforcement consequent to successful performance is essential for increasing the likelihood a skill will be acquired (that a behavior will occur again). As it is my intention to teach basic Web skills via the Web itself, tutorials must be designed so reinforcing feedback is provided automatically.
It is my hope to approximate on a simple level the sophisticated feedback features that Dr. Janet Twyman, who is guiding me in this project, has had built into software for teaching children to read. From the beginning, she has stressed to me the importance of detecting and reinforcing the pressing of the correct key sequence. I will post the details of this effort as the three of us develop them.
Notes: This post is the fourth in a series about Teaching Web Page (Text) Enlargement. Please post a comment with any suggestions.