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CMN-GOMS has been used to model word processors The CMN method can predict the operator sequence and the execution time of a task on a quantitative level and can focus its attention on methods to accomplish goals on a qualitative level. NGOMSL is a structured natural language notation for representing GOMS models and a procedure for constructing them.This program form provides predictions of operator sequences, execution time and time to learn methods.But both models include M-like operators for substantial time-consuming mental actions such as locating information on the screen and verifying entries.Both methods assign roughly the same time to unobservable perceptual and cognitive activities.
While it is not necessarily the most accurate method to measure human-computer interface interaction, it does allow visibility of all procedural knowledge.There are several different GOMS variations which allow for different aspects of an interface to be accurately studied and predicted.For all of the variants, the definitions of the major concepts are the same.KLM has a single M operator that precedes each cognitive unit of action.In contrast, GOMS assigns no time to such cognitive overhead.
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CMN-GOMS, KLM and NGOMSL assume that all of the operators occur in sequence and do not contain operators that are below the activity level.