The capability of a system to enable users to achieve and maintain competence with minimal training demand. It is not just about initial “ease of use”, but about the structural support for transition from novice to expert.

Dimensions

Temporal

• Initial learnability, e.g. performance of a first-time user.
• Extended learnability, i.e. change in performance over time.

Subject

• Interface: Can the user operate the system?
• Domain: Does the system help users understand the domain it embodies?

The tool frequently (always?) encodes domain knowledge—process logic, business rules, institutional decisions. Learning to use it well is domain learning. These dimensions interact: a user may be proficient with the interface but unfamiliar with certain domain areas, or understand the domain but struggle with the tool.

Training demand

The cognitive cost required to move from initial to extended learnability. This cost differs by subject:

• Interface training demand: effort to operate the system fluently
• Domain training demand: effort to understand what the system represents

Scaffolding

Temporary support structures that help users perform tasks they couldn’t yet do alone.

• For interface skills, effective scaffolding fades as competence grows—training wheels that eventually come off.
• For domain understanding, scaffolding may deepen rather than fade. As users master basics, they become ready for richer explanations of why the system works as it does.

Cognitive levels as a design heuristic

Bloom’s taxonomy provides a useful lens for two decisions that the concepts above leave underspecified:

1. What level does the user need to reach? Typical UI learning plateaus at Apply — users need to remember where things are, understand what they do, and operate them. Domain learning often requires Analyse or Evaluate — understanding why the system works as it does, or judging whether a recommendation is correct. Knowing the target level sharpens what “extended learnability” means for a given context.

2. What kind of scaffolding to provide? A tooltip that aids recall is different from an explanation that supports analysis. Scaffolding has not just an intensity dimension (how much support) but a cognitive level dimension (what kind of thinking it supports).

Some rough correspondences between cognitive levels and patterns in this library:

• Remember — annotation, consistent layout, familiar affordances
• Understand — explanation, transparent reasoning
• Apply — onboarding, direct manipulation
• Analyse — agent (contextual enrichment), comparison views
• Evaluate — transparent reasoning (judging system suggestions)
• Create — mastery-stage tools, composition patterns

Resources & references

• Anderson, L. W. & Krathwohl, D. R. (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives
• Andy Matuschak (2025). How might we learn? – synthesis of implicit and guided learning through AI-enhanced contexts
• Forsey et al. (2024). Designing for Learnability: Improvement Through Layered Interfaces. Ergonomics in Design
• Nielsen, J. (2006). Progressive disclosure. NN/g
• Grossman, T., Fitzmaurice, G., & Attar, R. (2009). A survey of software learnability
• Poretski, L., & Tang, A. (2022). Press A to Jump: Design Strategies for Video Game Learnability. CHI 2022.
• Carroll, J. M., & Rosson, M. B. (1987). The Paradox of the Active User
• Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43-52.