Keystroke-level Model - Example Calculation

Example Calculation

Change the code in Line 512 from "hte" to "the" ('the'the' in computer language) and then press Enter Key

or

" Change 512 'hte'the' "

Steps

• Mentally prepare
• 6 average speed keystrokes (for word "change")
• 1 average speed keystrokes for space bar
• 3 keystrokes for pressing numbers "512"
• 1 average speed keystrokes for space bar
• Mentally Prepare by reading what needs to be changed
• 6 average keystrokes for typing hte and the
• 3 keystrokes to press the 3 " ' "
• 1 keystroke to press Return Key

Values

K1 = average speed keystrokes (0.20 seconds)

K2 = typing random letters (0.50 seconds)

M = Mentally Prepare (1.35 seconds)

Put above steps into formula: M + 6K1 + K1 + 3K2 + K2 + M + 3K1 + K2 + 3K1 + K2 = 2M + 14K1 + 6K2 = 9.82 seconds

This method assumes that operator times are invariant and do not depend on the previous sequence of events. New physical operators can be added if their timing can be represented as a simple context-free function. KLM-GOMS does not account for either slips or mistakes automatically—the analyst must create separate models of error sequences and perform their own sensitivity analysis.

The placement of the keystrokes and pointer operations are straightforward, but the placement of the mental operations is not. Mental operations are placed by a set of rules that require some interpretation, such as determining a conceptual "cognitive unit" or grouping of actions. For instance, pressing ctrl and c simultaneously to perform a "copy" would be considered a single cognitive unit. Mental operations are inserted before each cognitive unit to account for cognitive preparation and decision-making.

The main reason a designer or analysts would use this technique is that it is a very fast. Different designs or systems can be compared against one another quickly. It does not require that the evaluator be an expert in GOMS because the procedure is an explicitly laid out recipe. A major caution is that the algorithm is designed to estimate the execution time for an expert user, which is typically faster than the time for a new user or an unfamiliar task.