GOMS is a family of predictive models of human performance that can be used to improve the efficiency of human-machine interaction by identifying and eliminating unnecessary user actions. GOMS stands for (Goals, Operators, Methods, and Selection).
The simplest and most frequently used GOMS variant is KLM-GOMS (Keystroke-Level Model), where empirically derived values for basic operators like keystrokes, button presses, double clicks, and pointer movement time, are used to estimate task times.
The other three major GOMS variants (CMN-GOMS, NGOMSL, and CPM-GOMS) require extensive training and familiarity with Human-Computer Interaction principles to perform an analysis.
Lifecycle: Interaction design
Sources and contributors:Costin Pribeano and Georgios Christou (as part of MAUSE), Ben Werner.