HCI Design Approaches
Eberts (1994)  describes four Human-Computer Interaction (HCI) design approaches that may be applied to user interface designs to develop user-friendly, efficient, and intuitive user experiences for humans. These four approaches include the Anthropomorphic Approach, the Cognitive Approach, the Predictive Modeling Approach, and the Empirical Approach. One or more of these approaches may be used in a single user interface design.
The anthropomorphic approach to human-computer interaction involves designing a user interface to possess human-like qualities. For instance, an interface may be designed to communicate with users in a human-to-human manner, as if the computer empathizes with the user. Interface error messaging in often written this way, such as, “We’re sorry, but that page cannot be found.” Another example is the use of avatars in computer-based automation, as can be found in automated telephony systems. For example, when a voice-response system cannot understand what the user has spoken, after several attempts it may reply in an apologetic tone, “I’m sorry, I can’t understand you.”
Human affordances are perceivable potential actions that a person can do with an object. In terms of HCI, icons, folders, and buttons afford mouse-clicking, scrollbars afford sliding a button to view information off-screen, and drop-down menus show the user a list of options from which to choose. Similarly, pleasant sounds are used to indicate when a task has completed, signaling that the user may continue with the next step in a process. Examples of this are notifications of calendar events, new emails, and the completion of a file transfer.
Constraints complement affordances by indicating the limitations of user actions. A grayed-out menu option and an unpleasant sound (sometimes followed by an error message) indicate that the user cannot carry out a particular action. Affordances and constraints can be designed to non-verbally guide user behaviors through an interface and prevent user errors in a complex interface.
The cognitive approach to human-computer interaction considers the abilities of the human brain and sensory-perception in order to develop a user interface that will support the end user.
Using metaphors can be an effective way to communicate an abstract concept or procedure to users, as long as the metaphor is used accurately. Computers use a “desktop” metaphor to represent data as document files, folders, and applications. Metaphors rely on a user’s familiarity with another concept, as well as human affordances, to help users understand the actions they can perform with their data based on the form it takes. For instance, a user can move a file or folder into the “trashcan” to delete it.
A benefit of using metaphors in design is that users who can relate to the metaphor are able to learn to use a new system very quickly. A potential problem can ensue, however, when users expect a metaphor to be fully represented in a design, and in reality, only part of the metaphor has been implemented. For example, Macintosh computers use the icon of a trashcan on the desktop, while PCs have a recycle bin. The recycle bin does not actually “recycle” the data; instead it behaves like the Macintosh trash can and is used to permanently delete files. On the other hand, in order to eject a mounted disc on a Macintosh, the user must drag the icon of a CD-ROM to the trashcan. When this was first introduced, it was confusing to users because they feared losing all the data on their CD-ROM. In more recent versions of the Mac OS, the trashcan icon turns into an eject symbol when the user drags a mounted disc to the trashcan. This does not make the metaphor flawless, but it does prevent some user confusion when they are ejecting the mounted disc.
Attention and Workload Models
When designing an interface to provide good usability, it is important to consider the user’s attention span, which may be based on the environment of use, and the perceived mental workload involved in completing a task. Typically, users can focus well on one-task-at-a-time. For example, when designing a web-based form to collect information from a user, it is best to contextually collect information separately from other information. The form may be divided into “Contact Information” and “Billing Information”, rather than mixing the two and confusing users.
By “chunking” this data into individual sections or even separate pages when there is a lot of information being collected, the perceived workload is also reduced. If all the data were collected on a single form that makes the user scroll the page to complete, the user may become overwhelmed by the amount of work that needs to be done to complete the form, and he may abandon the website. Workload can be measured by the amount of information being communicated to each sensory system (visual, auditory, etc.) at a given moment. Some websites incorporate Adobe Flash in an attempt to impress the user. If a Flash presentation does not directly support a user’s task, the user’s attention may become distracted by too much auditory and visual information.
Overloading the user’s memory is another common problem on websites. For example, when there are too many options to choose from, a user may feel overwhelmed by the decision they have to make, become frustrated, and leave the website without completing their goal.
Human Information Processing Model
Human Information Processing (HIP) Theory describes the flow of information from the world, into the human mind, and back into the world. When a human pays attention to something, the information first gets encoded based on the sensory system that channeled the information (visual, auditory, haptic, etc.). Next, the information moves into Working Memory, formerly known as Short-Term memory. Working Memory can hold a limited amount of information for up to approximately 30 seconds. Repeating or rehearsing information may increase this duration. After Working Memory, the information may go into Long-Term Memory or simply be forgotten. Long-Term Memory is believed to be unlimited, relatively permanent memory storage. After information has been stored in long-term memory, humans can retrieve that information via recall or recognition. The accuracy of information recall is based on the environmental conditions and the way that information was initially encoded by the senses. If a human is in a similar sensory experience at the time of memory recall as he was during the encoding of a prior experience, his recall of that experience will be more accurate and complete.
The empirical approach to HCI is useful for examining and comparing the usability of multiple conceptual designs. This testing may be done during pre-production by counterbalancing design concepts and conducting usability testing on each design concept. Often, users will appreciate specific elements of each design concept, which may lead to the development of a composite conceptual design to test.
Human Task Performance Measures
In addition to a qualitative assessment of user preferences for a conceptual design, measuring users’ task performance is important for determining how intuitive and user-friendly a web page is. A researcher who is familiar with the tasks the web page has been designed to support will develop a set of test tasks that relate to the task goals associated with the page. Users may be given one or more conceptual designs to test in a lab setting to determine which is more user-friendly and intuitive. User performance can be assessed absolutely, i.e., the user accomplishes or fails to complete a task, as well as relatively, based on pre-established criteria. For instance, it may have been determined that users should be able to register for an account within five minutes, and with no more than two errors. If the researcher observes otherwise, and even if the user finally completes the task (perhaps after fifteen minutes and five errors), the time and number of errors may be compared to the desired standard as well as to the alternate conceptual design for the web page.
If two of three design concepts were rated highly during user testing, it may be advantageous to conduct an A/B Test during post-production. One way to do this is to set up a Google Analytics account, which allows a researcher to set up multiple variations of a web page to test. When a user visits the website, Google will display one variation of the web page according to the end user’s IP address. As the user navigates the website, Google tracks the user’s clicks to see if one version of the web page produces more sales than another version. Other “conversion” goals may be tracked as well, such as registering a user account or signing up for a newsletter.
Predictive Modeling Approach
GOMS is a method for examining the individual components of a user experience in terms of the time it takes a user to most efficiently complete a goal. GOMS is an acronym that stands for Goals, Operators, Methods, and Selection Rules (Card, Moran, & Newell, 1983). Goals are defined as what the user desires to accomplish on the website. Operators are the atomic-level actions that the user performs to reach a goal, such as motor actions, perceptions, and cognitive processes. Methods are procedures that include a series of operators and sub-goals that the user employs to accomplish a goal. Selection Rules refer to a user’s personal decision about which method will work best in a particular situation in order to reach a goal.
The GOMS model is based on human information processing theory, and certain measurements of human performance are used to calculate the time it takes to complete a goal. For example, the average time it takes a human to visually fixate on a web page, move eye fixation to another part of the web page, cognitively process information, and make a decision of what to do next can be measured in milliseconds. The times it takes for each of these operators can be added up to produce the total time for a particular method. Multiple methods can be compared based on the total time to complete a task in order to determine which is the most efficient method for accomplishing the task.
 Eberts, R. E. (1994). User interface design. Englewood Cliffs, NJ: Prentice Hall.  Card, S., Moran, T., & Newell, A. (1983). The psychology of human-computer interaction. Hillsdale, NJ: Lawrence Erlbaum Associates.