Usability Analysis with Markov Models

How hard to users to find interactive devices to use to achieve their goals, and how can we get this information early enough to influence design? We show that Markov modeling can obtain suitable measures, and we provide formulas that can be used for a large class of systems. We analyze and consider alternative designs for various real examples. We introduce a “knowledege/usability graph,” which shows the impact of even a smaller amount of knowledge for the user, and the extent to which designers' knowledge may bias their views of usability. Markov models can be built into design tools, and can therefore be made very convenient for designers to utilize. One would hope that in the future, design tools would include such mathematical analysis, and no new design skills would be required to evaluate devices. A particular concern of this paper is to make the approach accessible. Complete program code and all the underlying mathematics are provided in appendices to enable others to replicate and test all results shown.