Note: The creation of this article on testing Language of Page was human-based, with the assistance of artificial intelligence.
Explanation of the success criteria
WCAG 3.1.1 Language of Page is a Level A conformance level Success Criterion. It targets one of the most foundational aspects of digital accessibility: the ability for a page’s default human language to be programmatically determined. At its core, this criterion ensures that developers explicitly define the page’s primary language, commonly through HTML attributes like lang, so that assistive technologies, such as screen readers, can accurately pronounce words, apply linguistic rules, and enhance comprehension for all users.
Example of a language being declared on a web page:
<html lang="en-US" ... >
Proper language identification is far more than a technical formality; it is a critical pillar of inclusive design. When implemented correctly, it enables content to communicate clearly and effectively to diverse audiences, regardless of linguistic, cognitive, or technological differences.
Who does this benefit?
The impact of accurately identifying a page’s language reaches a wide spectrum of users:
- Screen reader users gain precise pronunciation and interpretation, which is essential for meaningful comprehension.
- Users of translation tools benefit from correct language tagging, allowing for accurate translations and seamless localization.
- Individuals with cognitive or learning disabilities experience improved understanding, reducing confusion when content is read aloud by text-to-speech tools.
- Multilingual users navigating content in multiple languages can switch between sections without encountering misinterpretation.
- All users relying on assistive technologies that depend on language information receive more reliable guidance and output, enhancing overall usability.
Testing via Automated testing
Automated tools are ideal for scanning large sites quickly to detect the presence of lang attributes and flag missing or improperly formatted declarations. This method is efficient, repeatable, and excellent for baseline audits. Yet, automation cannot verify whether the declared language truly reflects the content or handle pages that contain multiple languages.
Testing via Artificial Intelligence (AI)
Artificial intelligence adds contextual awareness by analyzing the page’s actual text to identify the predominant language. AI can highlight inconsistencies between the declared language and content, detect multilingual sections, and recommend more precise language tagging.
While offering a nuanced perspective beyond basic automation, AI may misclassify content in short, technical, or code-heavy passages, requiring human review to ensure accuracy.
Testing via Manual Testing
Human evaluation remains the gold standard for confirming that language declarations match the content. Manual testing is essential for complex pages with multiple languages, dynamically generated content, or specialized terminology. It ensures that language attributes meaningfully support assistive technologies and real-world comprehension.
The drawback lies in its time-intensive nature, making it less feasible for very large sites without targeted prioritization.
Which approach is best?
The most effective method for achieving WCAG 3.1.1 compliance is a hybrid testing strategy that integrates automated scanning, AI analysis, and manual validation.
Begin with automated testing to quickly identify missing or misconfigured language attributes, establishing a baseline of issues. Next, leverage AI to analyze content contextually, detect inconsistencies, and handle multilingual or dynamically generated sections. Finally, apply manual testing to validate nuanced cases, confirming that the language declarations truly support accessibility for all users.
By combining these three approaches, organizations achieve a balance of efficiency, precision, and human insight. This hybrid methodology not only ensures compliance with WCAG 3.1.1 but also elevates digital content to a standard of inclusivity and user-centered design, ensuring that every user, regardless of language, ability, or technology, can fully access and understand the content.