Evidence rating

Effect score (E): 4/5 Evidence for the underlying principle or measurement method.

Transfer score (T): 4/5 Evidence for reliable results in digital product practice.

Evidence level: High

[Plausible based on UX research] Analyze errors as an interaction between task, system, and context rather than attributing them prematurely to individual failure.

Scale and rating rules

Effect score: 5 established · 4 robust · 3 context-dependent · 2 weak · 1 preliminary.

Transfer score: 5 practice-proven · 4 field-supported · 3 partially supported · 2 plausible · 1 hypothesis.

Without a robust scientific or normative source, E is capped at 3. Blog and agency opinions support at most T=2. If evidence conflicts, the more conservative score applies until justified otherwise.

Evidence level: High = E ≥ 4 and T ≥ 3; Moderate = E ≥ 3; Preliminary = E ≤ 2 or T ≤ 1.

Error Models & User Errors

Errors are part of interacting with digital systems - but they are not a sign of stupidity, they can be systematically explained. UX design must understand and intercept them.

User errors are unintended actions or outcomes during interaction. Understanding whether an error is a slip or a mistake helps UX teams prevent it through clearer design and better recovery.

Definition

A user error is an unintentional action or an incorrect result that occurs when using a system - regardless of whether the system works “correctly”.

The three error types at a glance

The practical distinction is where the problem starts: execution, memory or planning. Norman distinguishes slips from mistakes; Reason also names lapses and describes how mistakes can arise.

Type	What goes wrong?	UI example	Useful design response
Slip	The user has the right goal but performs the wrong action	They select Delete instead of Archive because the controls are adjacent	Separate and label controls; offer undo
Lapse	The user forgets an intended step	After an interruption, they submit a form without completing a required field	Show progress and missing steps; preserve entered data
Mistake	The user’s goal, assumption or chosen rule is wrong	They choose “Save” expecting the item to be shared with the team	Explain concepts and consequences before the action

Slip: the right intention, the wrong action

A slip happens during execution. Someone may click the wrong control, mistype a value or repeat an action without noticing. The user knows what they want to do; the interface or context makes the intended action easy to miss.

Design focus: prevent near-misses with clear labels, adequate spacing and visible states. Make recovery easy with undo rather than relying only on a confirmation dialog.

Lapse: an intended step is forgotten

A lapse is a memory failure, not a wrong decision. For example, a user returns to a multi-step form after a phone call and overlooks a required address field.

Design focus: keep progress visible, identify incomplete fields at the point of need and preserve work when users navigate back.

Mistake: the plan or assumption is wrong

A mistake happens during planning or interpretation. A user may misunderstand a label, apply a familiar rule in a new situation or form an incorrect idea about what the system will do. In Reason’s model, mistakes can be rule-based (the wrong rule is applied) or knowledge-based (the situation is unfamiliar and the user reasons from incomplete information).

Design focus: use language users understand, make consequences explicit and align interface concepts with the system’s actual behavior.

How the models differ

Norman’s distinction focuses on whether the action or the intention is wrong: slips versus mistakes. Reason’s model also includes lapses and further classifies mistakes as rule-based or knowledge-based. A lapse is not simply another kind of mistake.

Design Against Errors

Principle	Implementation
Error tolerance	Undo, restore, queries before deletion actions
Feedback & status displays	What has been done? What is happening right now?
Error avoidance instead of error handling	Deactivate buttons instead of showing warning later
Consistency	Recognizable symbols, navigation, layouts
Explicit labeling	”Cancel” instead of “Back”

A practical error-prevention process

Observe where users make slips or form incorrect assumptions.
Classify the error as an execution problem, a missed step or a planning problem.
Remove avoidable error opportunities before adding warnings.
Add feedback, undo and recovery for errors that remain possible.
Re-test the complete flow with representative users.

For example, if users repeatedly submit a form with a missing delivery address, first make the required field and its error state visible, then preserve entered data and provide a clear route to correct it. A warning alone does not address the underlying interaction problem.

Conclusion

User errors do not occur because people are unfocused or incompetent - but because systems are designed to be complex, ambiguous or error-prone.
UX design should focus on being error-friendly rather than error-free.

Take Home Message

Errors are systemic - not individual. Good design makes mistakes unlikely and reversible.

Frequently asked questions (FAQ)

What are user errors in UX design?

User errors are unintentional actions or incorrect results when interacting with a system - regardless of whether the system functions technically correctly.

What types of errors does Donald Norman distinguish?

Norman distinguishes between slips (slips in the execution of a correct intention) and mistakes (wrong decisions due to incorrect assumptions or mental models).

What does James Reason's error model describe?

Reason distinguishes between knowledge-based errors, rule-based errors and skill-based errors. They show that errors can be explained systematically and are not just individual failures.

How can UX design avoid errors?

Through error tolerance (e.g. undo), clear feedback, consistent navigation, explicit labeling and the avoidance of error possibilities instead of subsequent warnings.

Why do errors often arise from the system and not from humans?

Complex or ambiguous interfaces, a lack of feedback and inconsistent structures lead to errors. Good design reduces these risks and eliminates errors.

Science corner: evidence data

Setting

Laboratory and field observations of human interaction

Replication status

Replicated / repeatedly studied

Evidence level

High (E=4, T=4)

Key sources (APA)

Norman, D. A. (1981). Categorization of action slips. Psychological Review, 88(1), 1–15. https://doi.org/10.1037/0033-295X.88.1.1
Reason, J. (1990). Human error. Cambridge University Press. https://doi.org/10.1017/CBO9781139062367
Rasmussen, J. (1983). Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. IEEE Transactions on Systems, Man, and Cybernetics, SMC-13(3), 257–266. https://doi.org/10.1109/TSMC.1983.6313160

Review date / version

2026-11-01 · 1.1

Next review

2027-11-01 (Review cycle: 12 months)

Last modified: 1 November 2026