Plain language (A)

Plain language: Provide clear and simple language in instructions, labels, navigational elements, and error messages, which require a response to continue, so that all of the following are true.

For instructions, labels, and navigational elements:

Also on controls:

Also on instructions:


What Principle and Guideline the SC falls within.

Under WCAG 3.1

Suggestion for Priority Level


Related Glossary additions or changes

concrete wording
concrete wording uses literal language, is specific, and describe things experienced through one's 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. Words lists should also give the meaning of the usage.
non-literal language
non-literal language is language that goes beyond the dictionary meaning of the word or phrase. It 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 examples:
"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"; and "busy as a bee"; are a few of the many examples of figurative language in common usage.
easily available (or easily available mode or setting)



The  intent  of this success criterion is to ensure people can understand and use navigational elements, user interfaces, and instructions. Clear language for all content is an important accessibility principle. However, if the user does not understand words and terms in these critical areas, the whole application or web site often becomes unusable.

A real-life example is a person, with mild dementia, trying to use an application to turn on a heating and air conditioning unit. The menu item for selecting heat or air conditioning is labeled "mode". The user does not know that "mode" refers to heat or to air conditioning, and thus cannot use the whole unit because of this one term.

In this real-life example (reported by a task force member), a visitor turned on an air conditioner and did not turn it off when leaving the dwelling. The weather became a bit cooler. The user, who could not turn on the heat because of the language used, became hypothermic, and needed emergency treatment.

People with dementia have impaired short-term memory, and difficulty remembering new information. Therefore, learning and remembering new terms can be impossible. However, if an interface uses familiar terms and design, it is fully usable. Not being able to use these applications mean that more people require live-in help, and lose their independence.

In another example, many task force members cannot use GitHub because the terms it uses are not typical for functions (such as "push" instead of "upload").

Some users, particularly those on the autism spectrum, will have difficulty with figurative language, as they will try to interpret it literally. This will frequently lead to the user to failing to comprehend the intended meaning, and may instead act as a source of stress and confusion. (Taken from ETSI)

It should be noted that restrictions on scope make it practical from the content providers' perspective, and the exceptions ensure it is widely applicable. For example, error messages, which require a response to continue, are being included as a level A because, without understanding these messages, the user is completely unable to continue. Error messages, which do not require a response, may be frustrating, but do not always make the whole application unusable.


This supports those who have reading difficulties, language disabilities, and some visual perceptual difficulties. It can include people with intellectual disabilities, Receptive Aphasia, and/or 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

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.

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

[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 .
[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 /.
[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 .
[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

[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



Top Five Instructional Tips for Students with Down syndrome" (downloaded 08/2015)

Students with Down Syndrome,


Task force links

Issue papers

COGA Techniques


This success criterion is testable if each of the bullet points are testable. If 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:

Tense and voice are objective, and hence are verifiable. (It is expected that natural language processing algorithms will be able to conform to 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.

Even languages with a small number of users have published lists of most-frequent words (such as Hebrew). If there is a natural language that does not have such a list, algorithms exist that calculate these lists for languages, 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.

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.


Non-literal text, such as 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.

 This can be tested by identifying the function of the control, and checking if it is identified in the label.

This is human testable by completing the instructions literally, and confirming that the effect is correct.