Learning time can be estimated from the number of rules the user must newly acquire

What it is

Cognitive Complexity Theory (CCT) represents the user's task knowledge as a set of production rules of the form "under condition C, perform action A." Learning time is approximated as proportional to the number of rules the user must newly acquire.

Why it happens

Each new rule must be encoded, practiced, and automated, and the costs roughly add up per rule; already mastered rules drop out. Listing all rules required by a target interface, subtracting what the target users already know, and multiplying the remainder by a per-rule acquisition constant yields an estimate of learning time.

Studying it

Modelers write production-system models of the old and new interfaces, align them by matching conditions, and count newly introduced rules. A per-rule constant is fitted from novice learning curves and then tested on held-out tasks. The constant varies with task complexity, so calibration must stay within one measurement framework.

Where it stops holding

The estimate assumes users learn the logic the system presents; it does not cover exploration, trial and error, or confusion. Complex rules cost more than simple ones, so equal weighting is an approximation, and constants do not transfer across populations or training regimes.

Applying it

• When reviewing a new interface, list every operation rule a user must learn and label each as known, partially similar, or entirely new.
• Treat the count of entirely new rules as a learnability budget; compress novel rules before polishing familiar operations.
• Before a redesign, diff the old and new rule lists, minimize the new-rule set, and validate the estimate with first-use task completion times.

Related

• Same group: B4.14.2 Mastered rules transfer; the more two interfaces share, the cheaper the second is to learn · B4.14.3 The theory yields quantitative predictions of transfer gains between old and new systems · B4.14.4 Rule counts depend on the representation the modeler chooses, so different modelers may produce different counts
• Nearby: B4.11 GOMS models · B5.03 Learnability
• Search terms: cognitive complexity theory · production rules · learnability