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#30 Plain Language - Minimum #106
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#30 Plain Language - Minimum #106
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Glossary
Plain Language (Minimum)
A
New
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:
Exceptions:
Related Glossary Additions or Changes
What Principle and Guideline the SC falls within.
Guideline 3.1
Description
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 labelled "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.
Benefits
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
Resources are for information purposes only. No endorsement is intended or implied.
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.
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 verifiable. It is assumed a natural language processing tool will also test for this. Testing for exceptions is as discussed above.
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
Acknowledgments