Note: The creation of this article on testing Reading Level was human-based, with the assistance of artificial intelligence.
Explanation of the success criteria
WCAG 3.1.5 Reading Level is a Level AAA conformance level Success Criterion. Its purpose is clear: digital content must be understandable to its intended audience. This extends beyond basic text to instructions, labels, and interactive elements, all of which must be written at a reading level appropriate for the target users. When higher-level or specialized language is unavoidable, content must include explanations, summaries, or simplified alternatives. This ensures that users with cognitive disabilities, limited literacy, or non-native language proficiency can access and comprehend content effectively.
While AAA conformance is aspirational rather than mandatory, adopting WCAG 3.1.5 signals a strategic commitment to accessibility. Organizations that implement this criterion demonstrate that accessibility is not just a compliance checkbox, it’s a design philosophy that elevates user experience, fosters inclusion, and builds trust. When thoughtfully applied, this success criteria promotes clarity, strengthens engagement, and transforms content into genuinely user-friendly experiences.
Who does this benefit?
- People with cognitive or learning disabilities: Simplified language and clear explanations improve comprehension.
- Users with limited literacy skills: Content becomes accessible without requiring advanced reading ability.
- Non-native speakers: Simplified, contextually clear language aids understanding in a second language.
- Older adults or users with age-related comprehension challenges: Instructions and content are easier to follow.
- Assistive technology users: Tools that simplify, summarize, or read content aloud work more effectively with clear language.
In essence, it serves anyone who may struggle with complex text, expanding accessibility and inclusivity across diverse audiences.
Testing via Automated testing
Automated tools quickly scan large volumes of content, analyzing sentence length, word complexity, and readability scores with metrics like Flesch-Kincaid, SMOG, or Gunning Fog. The advantages are clear: speed, scalability, and consistency allow organizations to flag potential readability issues across entire websites efficiently. The limitations are equally notable: automated testing cannot account for context, specialized terminology, or audience-specific comprehension, often resulting in false positives or missed nuanced challenges.
Testing via Artificial Intelligence (AI)
AI adds a layer of semantic intelligence. It interprets sentence structures, jargon, and acronyms, offering recommendations for simplification, alternative phrasing, or explanatory content. AI can also prioritize sections most likely to challenge users based on cognitive ability, literacy, or language proficiency. Its pros include contextual understanding and actionable guidance. The cons involve variability in results depending on the AI model, occasional oversimplifications, and the need for human oversight to maintain accuracy and nuance.
Testing via Manual Testing
Manual review remains essential for nuanced evaluation. Accessibility experts or representative users can confirm that readability adjustments preserve meaning, and that explanations, glossaries, or summaries are effective. Pros include high accuracy, real-world validation, and context sensitivity, while cons include resource intensity, subjectivity, and limited scalability for large content sets.
Which approach is best?
The hybrid approach to testing WCAG 3.1.5 Reading Level represents the most effective strategy for ensuring digital content is truly understandable by its intended audience. It integrates automated, AI-based, and manual testing, leveraging the unique strengths of each method to create a comprehensive and reliable evaluation of readability.
The process begins with automated testing, which scans the entirety of a site’s content, quickly identifying passages that may exceed recommended reading levels. By applying metrics such as Flesch-Kincaid, Gunning Fog, or SMOG, automated tools provide a broad, scalable overview, highlighting areas that warrant deeper, more nuanced investigation.
Once potential challenges are identified, AI-based analysis introduces contextual intelligence. Unlike simple formulas, AI can interpret the semantic meaning of complex sentences, detect specialized terminology or jargon, and suggest precise simplifications or explanatory alternatives. AI also allows for audience-specific prioritization, focusing on sections most likely to challenge users with cognitive disabilities, limited literacy, or non-native language skills. This approach enhances efficiency and improves the relevance of interventions, though it still benefits from human oversight to ensure that meaning and nuance are preserved.
Finally, manual testing validates and refines these findings through human judgment. Accessibility experts or representative users review flagged content to ensure readability improvements are effective in real-world conditions. They verify that summaries, glossaries, or alternative explanations convey the intended meaning and that the content is genuinely accessible to diverse audiences. Manual testing adds the critical layer of empathy and practical insight that automated and AI-driven methods alone cannot replicate.
By combining these three complementary approaches, organizations achieve a careful balance of speed, precision, and inclusivity. The hybrid methodology not only identifies potential readability challenges but ensures that content improvements are meaningful, audience-focused, and genuinely user-friendly. Executed thoughtfully, this approach positions accessibility as a strategic design principle, embedding it at the core of content creation rather than treating it as a regulatory obligation or afterthought.
Related Resources
- Understanding WCAG 3.1.5 Reading Level
- mind the WCAG automation gap
- Providing a text summary that can be understood by people with lower secondary education level reading ability
- Providing visual illustrations, pictures, and symbols to help explain ideas, events, and processes
- Providing a spoken version of the text
- Making the text easier to read
- Providing sign language versions of information, ideas, and processes that must be understood in order to use the content
- Flesch–Kincaid readability tests
- Flesch Kincaid Calculator
- Gunning fog index
- SMOG Index