The Clear Communication Index (Index) provides research-based criteria to develop and assess public communication products. The Index supports the efforts of the Centers for Disease Control and Prevention (CDC) to comply with the Plain Writing Act of 2010. Helps to achieve goals set forth in the National Action Plan to Improve Health Literacy and the CDC Action Plan to Improve Health Literacy.
The 20 items in the Index build on and expand plain language technique described in the Federal Plain Language Guidelines.
The Index at a Glance
Why Was the Index Developed?
The Index was developed to:
1. Identify the most important communication characteristics that enhance clarity and aid understanding of public messages and materials.
2. Provide a research-based tool for staff to develop and assess communication products for CDC’s audiences, no matter the format or distribution channel.
Who Should Use the Index?
CDC designed the Index for:
– CDC staff who write, edit, design, and review communication products for the public
– Contractors who produce materials for CDC
– Anyone who develops public health communication materials can use the Index.
How Does the Index Work?
The Index contains 20 items, each with a numerical score of zero or one. The individual scores are converted to an overall score on a scale of 100. Although 100 is an ideal score, 90 or higher is passing.
The Index assesses materials in these 7 areas:
1. Main Message and Call to Action
3. Information Design
4. State of the Science
5. Behavioral Recommendations
Estimated time required to complete the Index: 15 minutes.
CDC Clear Communication Index User Guide (.pdf)
AXS Chat recently posted to YouTube an interview of me about my artificial intelligence (AI) research and work for people with disabilities. I talk, in part, about:
- the promise of a text-comprehension parallel between AI and people with intellectual disabilities;
- how AI-driven Web text simplification will benefit other populations, such as non-native language speakers; and
- my work to make sure people with intellectual disabilities and/or autism are not left out of online education.
I thank the AXS Chat members, Neil Milliken, Debra Ruh, and Antonio Santos, for their tireless work to inform the world about inclusion and technology.
Amazon Machine Learning Research Awards generously sponsored my colleagues and me to participate in last week’s Amazon re:MARS Conference. It was a global artificial intelligence (AI) event focused on Machine Learning, Automation, Robotics, and Space.
The conference was great with accessibility. I was assigned an employee who guided me everywhere and was just wonderful. The conference website was accessible and easy to navigate. When I identified accessibility problems with the mobile app and with SageMaker tools, Amazon personnel immediately assured me they would be fixed.
The sponsorship included participation in the re:MARS VIP Leadership Networking Reception. I was honored to speak with members of Amazon leadership as well as senior researchers from industry and academia.
- my AI-driven, Web text simplification research;
- AI fairness for people with disabilities; and
- developing an Alexa skill for DisabilityInfo.org.
I will participate this week in a
I plan to discuss my AI Web text simplification research and AI fairness for people with disabilities. More about AI fairness soon.
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:
- a reliable, easy-to-use method for human editors to create simple text; and
- algorithms for AI to recognize and to create simple text.
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.
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.
A new Web site, TeachParentsTech.org, was announced by Google recently. Its purpose is to teach basic computer skills to parents. See the announcement and explanation.
The site teaches exclusively via videos. Among the 50+ videos now on the site, “How to make text bigger (or smaller)”, embedded below, is included in the first group displayed on the home page. My guess is that’s because learning how to make text bigger is one of the most common skills parents (older adults for whom vision may not be ideal) request to be taught.
The video starts be reassuring the audience that the task is “super easy”. The skill is then succinctly defined. It is taught exactly how I intend to do so, in that the audience is shown how to use a two-key combination within a Web browser. There is perhaps one main difference between the video and the one I hope to produce for people with cognitive disabilities. I intend to show an image of a keyboard, focusing specifically on how to press the correct two keys, in sequence, to make a Web page (text) larger.
Many people need to enlarge Web pages to better see information. People with cognitive disabilities often require larger text sizes to better comprehend information as well.
To develop a best practice for teaching a Web page (text) enlargement skill, I will conduct in-person teaching to groups of people with cognitive disabilities. Specifically, I intend to teach people to use a keyboard with a Web browser to enlarge Web pages. Many browsers will enlarge pages in response to the pressing of two keys: the plus key and the Control key (IBM) / Command key (Mac).
Given a Web page that may contain images, but must contain text, learners will press two keys to enlarge page content.
Learners will open a novel Web page and, without instruction or prompting, enlarge its contents.
Component Skills To Be Taught
- locate the correct keys (2)
- hold-down one key for at least 3 seconds with sufficient force to be recognized by the computer
- hold down the one key and tap the other key by pressing it with sufficient force to be recognized by the computer, and immediately releasing it
Completing Sequential Steps
- follow a multi-step chain of behaviors
- identify the start- and end points of the behavior chain
- repeat the behavior chain
Learners must be able to:
- respond to textual-, auditory- and/or video-based instruction
- press keys with their fingers or with equivalent assistive-technology
- press the correct keys only
- open a Web page with Internet Explorer
Computers must be:
- attached to a monitor and a keyboard or equivalent assistive-technology
- using Internet Explorer as the default Web browser
- connected to the Internet