Skip to main content

Testing Methods: Animation from Interactions

A mobile phone being held, with the user tapping on the screen of an apparent travel app, and an animation being presented on the screen

Note: The creation of this article on testing Animation from Interactions was human-based, with the assistance of artificial intelligence.

Explanation of the success criteria

WCAG 2.3.3 Animation from Interactions is a Level AAA conformance level Success Criterion. It is designed to protect users from motion-triggered discomfort, including seizures, dizziness, or nausea. It focuses on animations activated by user interactions, clicks, hovers, or gestures, ensuring that motion is predictable, controlled, and non-disruptive. By addressing these risks, organizations create interactive experiences that are safer, calmer, and more inclusive for everyone, particularly those with vestibular disorders, photosensitive epilepsy, or sensory sensitivities.

While Level AAA is aspirational rather than mandatory, striving for 2.3.3 signals a deeper commitment to accessibility. Organizations that embrace this standard demonstrate that accessibility is not just a compliance checkbox, it is a strategic priority that puts real user experiences first.

Who does this benefit?

This criterion benefits a wide range of users, including:

  • People with vestibular disorders who may experience disorientation or nausea from interactive motion.
  • Individuals with epilepsy or photosensitive conditions sensitive to rapid or repeated animations.
  • Users with cognitive or sensory sensitivities who find sudden motion distracting or overwhelming.
  • Anyone relying on assistive technologies that can be disrupted by interactive animations.

In essence, 2.3.3 helps make interactive content more predictable, safer, and universally accessible.

Testing via Automated testing

Automated testing is quick and scalable, scanning entire websites or applications to detect common animation patterns. While efficient, they often miss context-dependent interactions and can produce false positives or negatives, since they cannot fully interpret dynamic user-triggered behaviors.

Testing via Artificial Intelligence (AI)

AI-Based testing adds a layer of sophistication, simulating user interactions and predicting motion-related risks. AI can uncover subtle issues that automated scans might miss, though it may still struggle with highly complex or dynamic interfaces and requires careful validation to avoid inaccurate results.

Testing via Manual Testing

The most precise approach, manual testing allows evaluators to experience the site as real users would, observing the timing, intensity, and potential impact of animations. While highly reliable for nuanced issues, it is labor-intensive, time-consuming, and subject to tester variability.

Which approach is best?

No single approach for testing Animation from Interactions is perfect. A hybrid approach combines the efficiency of automated testing, the predictive power of AI, and the nuance of manual testing for comprehensive coverage.

First, automated tools can quickly scan the site or application to identify common animation patterns and elements likely to trigger motion, flagging obvious violations. Next, AI-based testing simulates user interactions, such as clicks, hovers, or form inputs, to detect subtler or context-dependent animations that may cause discomfort, providing insights that static automation might miss. Finally, manual testing allows human evaluators to interact with the content in real-world scenarios, assessing both the intensity and timing of animations and verifying that any motion is safe, optional, or can be disabled.

By layering these methods, organizations can efficiently address both large-scale and nuanced accessibility concerns, demonstrating leadership in creating truly inclusive, user-centered digital experiences.

Related Resources

Write a reply or comment

Your email address will not be published. Required fields are marked *