Intent
The intent of this success criteria is to help people better recognize and understand the intention of form inputs by attaching additional information (metadata) to the identified form inputs. This allows for additional machine-processing for personalization and other automation, such as identifying and applying familiar terms or symbols to the inputs, which are needed for users with cognitive disabilities to be able to use the web.
When a user-agent (browser or Assistive Technology) knows what an input is expecting it can then provide the ability for page customization, such as applying familiar icons or standardized labels next to the input. Additionally, using techniques such as the autocomplete attribute (from HTML) will make completing forms easier for everyone, by reducing the overhead of typing in common information such as address and credit card numbers. This benefits all users, but has a much greater impact on people with cognitive impairments.
The approach of adding metadata to indicate the purpose of elements is intended to be compatible with future work on personalization. Work done to implement this success criteria should continue to work when a wider range of personalization attributes are available in future. Although autocomplete provides a very limited scope for personalization, the mechanism for future work is similar which can be seen in the Personalization Semantics Content Module.
This approach will initially seem similar to adding role information (as required by 4.1.2 @@@ link) but actually provides higher level information so the user can understand the intent or purpose of the input. For example, that a field is intended for your name, it is not just a text field.
In the future a more robust set of personalization abilities should be available, such as this personalization demo provides. In this demo, a user can load a set of preferred symbols that are appropriate for them. These symbols can help a people comprehend intent via a toolbar or browser extension which overlays the symbols onto the page. When the autocomplete attribute is used, browser's and browser extensions can also populate form fields on command (or automatically) so the user does not have to remember or transcribe the information.
Benefits
Following the success criterion benefits users with various cognitive disabilities including people with language and memory related disabilities, and disabilities that affects executive function and decision making. (@@@ link to personas?)
- Personalization and the possibility for a familiar interface is available for users having trouble with understanding forms.
- The autocomplete function of user agents is able to support people by the filling in predetermined data.
Examples
Common ways to meet this success criteria include:
Providing the autocomplete attribute on suitable inputs - these techniques work on all the specified fields.
The list of values that should be used are available in the HTML5 specification: autocomplete values from HTML5.2.
Related Resources
Resources are for information purposes only, no endorsement implied.
- COGA friendly content and applications (@@@ link)
- User need Table 3: Entering data, error prevention & recovery (@@@ add link)
- User need Table 6: Familiar Interface (@@@ add link)
Techniques
Each numbered item in this section represents a technique or combination of techniques that the WCAG Working Group deems sufficient for meeting this Success Criterion. However, it is not necessary to use these particular techniques. For information on using other techniques, see Understanding Techniques for WCAG Success Criteria, particularly the "Other Techniques" section.
Sufficient Techniques
- Use HTML5.2 autocomplete attributes (@@@ link, Hxx?)
Key Terms
determined by software from author-supplied data provided in a way that different user agents, including assistive technologies, can extract and present this information to users in different modalities
Determined in a markup language from elements and attributes that are accessed directly by commonly available assistive technology.
Determined from technology-specific data structures in a non-markup language and exposed to assistive technology via an accessibility API that is supported by commonly available assistive technology.