Rule-based reasoning plays an important role in interface design as it does in any science based discipline. One of the most commonly invoked rules related to navigation and menu selection is Hick’s Law. As it makes a case for simplicity, let me state it as simply as I can.
In cases where all items have an equal probability of being chosen, the time it takes to choose an item from alternatives is exponentially proportional to the number of choices.
Thus, the more alternatives (such as in a menu) that you present to a user, the longer the time it will take to choose. That is simple enough to understand and apply: keep the amount of choices low, especially where time is an important factor.
However, that interpretation is too reductionist. It does not take into account the condition of all items having an equal probability of being chosen.
This condition depends on the prior knowledge of the users and/or the varying conditions that may influence the range of choice. Where domain knowledge varies widely, Hick’s Law becomes less simple to interpret in terms of under what circumstances and in what manner you should provide fewer choices.
In the case of menu structures, if users generally possess sufficient prior knowledge, they can work with more initial choices, such as an alphabetized list of all choices. However, Hick’s Law can be applied to further reduce time by default settings and user-control of options to keep the choice count down to reasonable levels.
If users vary in their prior knowledge or the conditions that determine choice vary, then a more hierarchical (deeper) menu structure (with submenu levels) may be more efficient. Users begin with fewer, more high level choices in the knowledge domain and proceed through subsequently presented submenus to choose among alternatives of a given subset. In essence, they are learning what they need to know about the knowledge domain to make reasonable choices (in a top-down, general to specific manner).
As this is a form of navigation (through the menu structure), offering “escape” routes back to previous menu levels through “bread crumb” links or a site map (with links to the entire menu structure) can help maintain efficiency.
However, even in the case of experts, having all choices available initially might be too unwieldy. An expert may have knowledge of each item presented in an alphabetized list of names, but if that list is too long, it would be more efficient to create a two-level menu structure where the user would first choose an alphabetical letter (in a list from A to Z) that would link to a shorter, more manageable list of choices (representing names beginning with the chosen alphabetical letter).
All this brings me to the inherent limitation of applying Hick’s Law too uniformly. While it is tempting to do so, this reductionist approach can lead to more inefficient and frustrating user experience.
Navigational and control (response) systems can be designed to automatically adapt or can be manually adapted to varying conditions and user prior knowledge to present the most appropriate menu structure.
Hick’s Law applied in terms of these variables can provide the efficiency and ease of use that arises from offering the more “simple” of alternative choice structures.
Along with prior knowledge, domain-specific training (e.g., formal training, embedded documentation, wizards, etc.) can help to conceptually organize a range of conditions and choices so that they can be addressed by fewer, more selective responses.
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