Cognitive walkthrough targets learnability rather than expert efficiency
Aliases: first-use learnability · novice discoverability · expert efficiency
What it is
Cognitive walkthrough primarily evaluates first-use learnability: whether someone without product experience can progress from interface cues. It does not directly measure expert speed, shortcuts, or long-term retention. A longer novice path can be acceptable when each step is intelligible and teaches the system.
Why it happens
Early bottlenecks are discovery and mapping; practiced performance depends on action cost, automation, and retrieval. A visible wizard can aid first completion while slowing experts, whereas hidden shortcuts may preserve novice success but cap efficiency. Mixing stages produces conflicting recommendations.
Studying it
Record prior knowledge and learning feedback required at each step. Study efficiency separately with practiced users, repeated tasks, time, and action counts. Longitudinal work can trace change while separating practice, interface memory, and external instruction.
Where it stops holding
Learnability includes recovery and cross-session retention, not first success alone. Mandatory tutorials may improve immediate completion without autonomous learning. Expert tools may accept steep entry costs when training and long-term gains are explicit.
Applying it
- Define success separately for novice and practiced stages.
- Use walkthrough findings only for initial discovery, mapping, and feedback.
- Test repeated-task efficiency, shortcuts, and retention separately.
- Verify that novice guidance can recede without obstructing experts.