Models and Theories in Human-Computer Interaction/Mechanical models: Human as machine
The evolution of HCI with GOMS and HIP is a step in the right direction
[edit | edit source]With the proliferation of personal computing technology, human-computer interaction has increased its scope to include human-information processing (and by proxy, frameworks of human behavior) and its combination with task analysis. This is a step in the right direction for the new field of human-computer interaction for a number of different reasons.
- As an emerging field of study, HCI provides a unique opportunity to study engineering and human factors from both a qualitative and quantitative perspective. This is especially important to understand when deconstructing usability from a functional perspective as well as a form perspective. GOMS allows for this type of duality in the understanding of design. It is studied in segments, specifically user goals, operators (actions that the software allows the user to take), methods (well-learned sequences of operators and subgoals that help accomplish a user goal), and selection rules (in the case that there is more than one way to accomplish the same goal).
- By segmenting the studies of frameworks of human behavior and task analysis, we honor both sides of human-computer interaction: the human and the computer. There are quantitative ways to study both human factors and engineering output. On the other hand, there are a number of ways to qualitatively study human behavior as it pertains to HCI. Because there are a large number of ways a human can respond to a design – engaging with it in different ways, defining multiple selection rules, finding unique methods to complete a user goal, etc – it is important to consider qualitative feedback and direction to a design. Designing for humans is a complicated process because not only are they unpredictable, but they can correct as they go – a skill that computers will eventually perfect in due time.
- Human performance on specific tasks can vary due to many factors, such as the biology of perception and movement; the form factor in which the design is presented; the cognition process; biases for methods or operators that are specific to operating systems; and more. When considering these factors in a GOMS analysis, it allows for a more holistic understanding of why certain designs succeed and others fail.
Creating an Effective & Efficient Workplace Through GOMS
[edit | edit source]According to Carrol, early designs in HIP (human information processing) theory in HCI were psychologically equated to "stimulus-responhuma se" that consist of perceptual and motor activities. However, HIP were difficult to be used as a design tool since it's more descriptive such as task analysis, approximation and calculation than predictive such as searching targets determined from tasks without needing prior data. This prediction is known as "zero-parameter". Therefore Card, Moran and Newell introduced the Model Processor (MHP) in 1983 that predicts short tasks that are isolated such as memory speed or keyboard strokes speed. These prediction models that approximates actual performance by error-free performance are called GOMS (Goals, Operators, Methods and Selection rules) models.
Creating an effective and efficient model while implementing good HCI practices in the workplace can be applied using Goals, Operators, Method and Selection rules models. The goals objective are to simplify the user's accomplishments and can be met through:
1. Matching user interface to the task by matching user records or item information.
2. Making the user interface efficient by standard operation and consistency.
3. Providing appropriate feedback to users using acknowledge acceptance, recognition of input, notification of input verification and notification of completion.
4. Generating usable queries often using SQL database or excel to extract meaningful data that we don't have previously.
5. Improving the productivity of computer users from all the data that were successfully collected, identified and examined.
Cited
Kendall, Kenneth E., and Julie E. Kendall. "Human-Computer Interaction / Ch 14." Systems Analysis and Design. Upper Saddle River, NJ: Pearson/Prentice Hall, 2008. 533-89. Print.