Plain language (AAA)

Plain language:  Allow the user to use plain language and provide clear and simple language in all content so that all of the following are true:

• Simple tense: Use the present tense and active voice. (See exceptions for different context and language.) 
• Simple, clear and common words: Use words or phrases that are most frequently used for the current context, unless this will result in a loss of meaning or clarity. This includes not using abbreviations, words or phrases, unless they are the common form to refer to the concept for beginners. Where word frequencies are known for the context, they can be used.
• Double negatives are not used
• Literal language: Non-literal language is not used, or can be automatically replaced, via an easy-to-set user setting. All meaning must be retained when non-literal text is replaced.

• When a passive voice or other tense can be clearer. Other voices, tenses and terms may be used when it has been shown, via user testing, to be easier to understand, friendlier, or appropriate.
• In languages where present tense and active voice do not exist, or are not clearer in the language of the content, use the tense and the voice that are clearest for the content.
• When describing or discussing past or future events, the present tense is not required.
• If the writing style is an essential part of the main function of the site, such as a game, a literary work, or teaching new terms.
•  Where less common words are found to be easier to understand for the audience. Such findings are supported by user testing that includes users with cognitive disabilities.
• The writing style items may be replaced for a location or type of content in which user testing has shown a more effective writing style to aid comprehension for people with cognitive disabilities. Such as for content written in a specific natural language.
• The content will be penalized for not conforming to a given writing style (such as a CV, dissertation, or Ph.D. proposal).

What Principle and Guideline the SC falls within.

Under WCAG 3.1

Suggestion for Priority Level

AAA or AA depending on whether technology can ensure that this is reasonable via alternative content.

Related Glossary additions or changes

concrete wording

concrete wording uses literal language, is specific and describes things you experience through your senses: smoke, mist, a shout.

 

 word frequencies

word frequency are lists of a language's words grouped by frequency of occurrence within some given text corpus. Word lists should also give the meaning of the usage

 

non-literal language

non-literal is language that uses words or expressions with a meaning that is different from the literal interpretation. Figurative language includes, but is not limited to, metaphor, sarcasm, simile, personification, hyperbole, symbolism, idioms, and cliché. For example:

• "I've told you a million times to clean your room!"
• "The sun is like a yellow ball of fire in the sky."
• "You are what you eat."
• "Busy as a bee."

 

Description

The intent of this Success Criterion is to ensure people can understand and use all content. For language to be usable by many people with cognitive disabilities it needs to be written in plain, clear language. This is an important accessibility principle.

It should be noted that the exceptions ensure it is widely applicable.

Benefits

This success criterion supports those who have reading difficulties, language disabilities, and some visual perceptual difficulties. It can include people with intellectual disabilities, receptive aphasia, and/or acquired dyslexia, as well as those with general cognitive learning disabilities. This supports those who have dementia, and/or acquire cognitive disabilities as they age.

Related Resources

Stroke Association Accessible Information Guidelines http://www.stroke.org.uk/professionals/accessible-information-guidelines

Computers helping people with special needs, 14 international conference ICCHP 2014 Eds. Miesenberger, Fels, Archambault, et al. Springer (pages 401). Paper: Never Too Old to Use a Tablet, L. Muskens, et al. pages 392 - 393.

[i.49]    Vogindroukas, I. & Zikopoulou, O. (2011). Idiom understanding in people with Asperger syndrome/high functioning autism. Rev. soc. bras. fonoaudiol. Vol.16, n.4, pp.390-395.
NOTE:    Available at http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-80342011000400005&lng=en&nrm=iso .
[i.50]    Oi, M., Tanaka, S. & Ohoka, H. (2013). The Relationship between Comprehension of Figurative Language by Japanese Children with High Functioning Autism Spectrum Disorders and College Freshmen's Assessment of Its Conventionality of Usage, Autism Research and Treatment, vol. 2013, Article ID 480635, 7 pages, 2013. doi:10.1155/2013/480635.
NOTE:    Available at http://www.hindawi.com/journals/aurt/2013/480635 /.
[i.51]    de Villiers, P. A. et al. (2011). Non-Literal Language and Theory of Mind in Autism Spectrum Disorders. Poster presented at the ASHA Convention, San Diego.
NOTE:    Available at http://www.asha.org/Events/convention/handouts/2011/de-Villiers-de-Villiers-Diaz-Cheung-Alig-Raditz-Paul/ .
[i.52]    Norbury, C. F. (2005). The relationship between theory of mind and metaphor: Evidence from children with language impairment and autistic spectrum disorder.; Oxford Study of Children's Communication Impairments, University of Oxford, UK; British Journal of Developmental Psychology, 23, 383-39.
NOTE:      Available at http://www.pc.rhul.ac.uk/sites/lilac/new_site/wp-content/uploads/2010/04/metaphor.pdf.

[i.53]     Language and Understanding Minds: Connections in Autism; Helen Tager-Flusberg, Ph.D; Chapter for: S. Baron-Cohen, H. Tager-Flusberg, & D. J. Cohen (Eds.), Understanding other minds: Perspectives from autism and developmental cognitive neuroscience. Second Edition. Oxford: Oxford University Press.

NOTE:      Available at http://www.ucd.ie/artspgs/langimp/TAG2.pdf.

Phiriyapkanon. Is big button interface enough for elderly users, P34, Malardardalen University Press Sweden 2011.

Neilson-aging

Top Five Instructional Tips for Students with Down Syndrome"http://specialedpost.org/2013/01/31/top-five-instructional-strategies-for-students-with-down-syndrome/

http://www.autism.org.uk/working-with/autism-friendly-places/designing-websites-suitable-for-people-with-autism-spectrum-disorders.aspx (downloaded 08/2015)

Students with Down Syndrome, http://www.downssa.asn.au/__files/f/3203/A%20Student%20with%20Down%20Syndrome%202014.pdf

Task force links

• Gap analysis
• User needs tables (See tables number 3, 5, and 7)
• Background research document (section 2.3)
• COGA Techniques

Issue papers

• Multi-modal Content Delivery

Testability

The success criterion is testable if each of the bullet points are testable. If all the content fails any bullet point, it is not conformant to this success criterion. If it passes all of the bullet points, it is conformant.

Bullet points:

• Simple tense: Use present tense and active voice. (See exceptions for different context and language.) 

Tense and voice are objective, and hence are verifiable. Also, it is expected that natural language processing algorithms will be able to confirm this automatically with reasonable accuracy.

Testing for exceptions:

If present tense and active voice have not been used, the tester will need to confirm if one of the exceptions is relevant. If an exception is not relevant, and present tense and active voice have not been used, then the content fails this success criterion.

• Simple and clear words: Use words or phrases most frequently used for the current context, unless this will result in a loss of meaning or of clarity. Where word frequencies are known for the context, they can be used. This includes not using abbreviations, words, and phrases unless they are the common forms to refer to the concept for beginners.

Even languages with a small number of users have published lists of the most frequent words (such as Hebrew). If there is a natural language that does not have one, algorithms exist that calculate these lists for a language, or for specific contexts. Testing content against these word lists can be done manually. However, it is expected there will be a natural language processing testing tool by the time this goes to CR. (It is already integrated into a tool by IBM.)

Testing for exceptions is as discussed above.

• Double negatives are not used.

Use of double negatives is a fact, and hence is verifiable. It is assumed a natural language processing tool will also test for this. Testing for exceptions is as discussed above.

• Literal text: Metaphors and non-literal text are not used, or can be automatically replaced via an easy-to-set user setting. All meaning must be retained when non-literal text is replaced.

Non-literal text and metaphors can be identified when the meaning of the sentence is something other than the meaning of the individual words. This is human testable. Cognitive computing algorithms can test for this as well.

If the text is not literal, then the tester must confirm that personalization and an easy user setting enables it to be replaced, such that all meaning is retained.

Techniques

• Using common words
• Using personalization and COGA semantics to provide easily available plain language
• Using active voice in English, and the present tense
• Using an alternative word frequency list for a given context
• Using concrete wording
• Using clear terms in menu items that describe functions
• Associating a common word or clear definition when a proprietary word is used.
• Failure of SC 3.1.x due to requiring users to learn new terms or new meanings for terms or symbols;
• Failure of SC 3.1.x due to showing words that are common, but not in the correct context or with an unclear meaning;
• Failure of SC 3.1.x due to use of non-literal text without an easy-to-use literal text replacement