CSE 556A Milestone 3 GOMS

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Author:
geschw66
ID:
311540
Filename:
CSE 556A Milestone 3 GOMS
Updated:
2015-11-15 23:18:04
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Goals Operators Methods Selection rules
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Description:
GOMS Overview: Goals, Operators, Methods and Selection rules (GOMS) is a modeling technique (more specifically, a family of modeling techniques) that analyzes the user complexity of interactive systems. It is used by software designers to model user behavior.
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  1. GOMS: What is it?
    is a modeling technique (more specifically, a family of modeling techniques) that analyzes the user complexity of interactive systems. It is used by software designers to model user behavior.
  2. GOMS stands for ___ ___ ___ ___ (?)
    GOMS stands for: Goals, Operators, Methods and Selection rules
  3. GOMS: Model consists of?
    Briefly, a GOMS model consists of

    • Methods that are used to achieve Goals.
    • A Method is a sequential list of Operators that the user performs and (sub)Goals that must be achieved.
    • If there is more than one Method which may be employed to achieve a Goal, a Selection rule is invoked to determine what Method to choose, depending on the context.
  4. The GOMS models can be used for a
    variety of purposes:
    • Functionality Coverage
    • Execution time
    • Help systems
  5. Help systems in GOMS model
    Since GOMS models are an explicit representation of expert user activity, they can assist in designing help systems and tutorials to assist users in achieving goals.
  6. Functionality Coverage in GOMS model
    If the designer has a list of likely user goals, GOMS models can be used to verify that a method exists to achieve each of these goals.
  7. Execution time in GOMS model
    GOMS models can predict the time it will take for the user to carry out a goal (assuming an expert user with no mistakes). This allows a designer to profile an application to locate bottlenecks, as well as compare different UI designs to determine which one allows users to execute tasks quicker.
  8. GOMS Principles:
    • Operators
    • Methods
    • Selection rules
    • Keystroke-Level Model
  9. Operators: GOMS Principles:
    • Operators are the elementary perceptual, motor or cognitive actions that are used to accomplish the goals (e.g. DOUBLE-CLICK-MOUSE, PRESS-INSERT-KEY).
    • Operators are not decomposable: they are atomic elements in the GOMS model.
    • It is generally assumed that each operator requires a fixed amount of time for the user to execute, and that this time interval is independent of context (e.g. CLICK-MOUSE button takes 0.20 seconds to execute)
  10. Methods: GOMS Principles:
    • Methods are the procedures that describe how to accomplish goals.
    • A method is essentially an algorithm that the user has internalized that determines the sequence of sub-goals and operators necessary to achieve the desired goal.
  11. Methods: Example:
    • For example, one method to accomplish the goal DELETE-WORD in the Emacs text editor would be to MOVE-MOUSE to the beginning of the word, and PRESS-ALT-D-KEY-COMBINATION (the use-mouse-delete-word method).
    • Another method to accomplish the same goal could involve using the arrow keys to reach the beginning of the word (the use-arrows-delete-word method).
  12. Selection rule: GOMS Principles:
    Selection rules specify which method should be used to satisfy a given goal, based on the context.
  13. Selection rule: Form:
    Selection rules generally take the form of a conditional statement, such as "if the word to be deleted is less than 3 lines away from the current cursor location, then use the use-arrows-delete-word-method, else use the use-mouse-delete-word method".
  14. Keystroke-Level Model: GOMS Principles:
    • The Keystroke-Level Model is a simplified version of GOMS.
    • It was proposed as a method for predicting user performance.
    • Using KLM, execution time is estimated by listing the sequence operators and then summing the times of the individual operators.
    • KLM aggregates all perceptual and cognitive function into a single value for an entire task, using a heuristic.
    • Does not employ selection rules
  15. KLM: Six Classes of Operators:
    • The original KLM had six classes of operators:
    • K for pressing a key
    • P for pointing to a location on screen with the mouse
    • H for moving hands to home position on the keyboard
    • M for mentally preparing to perform an action
    • R for system response where the user waits for the system.
    • For each operator, there is an estimate of execution time.
    • Additionally, there is a set of heuristic rules to account for mental preparation time.
  16. GOMS: Variants:
    • Keystroke-Level Model (KLM)
    • Card, Morn, and Newell GOMS (CMN-GOMS) original.
    • Natural GOMS Language (NGOMSL)
    • Cognitive-Perceptual-Motor GOMS (CPM-GOMS)
  17. GOMS: Classification
    • As a theory of HCI, GOMS models can be classified as
    • predictive
    • descriptive
    • prescriptive.
  18. GOMS: Predictive classification:
    A GOMS model is predictive because it can be used to predict the time it will take a user to perform the tasks under analysis, as long as the developer can come up with time estimates for the operators involved in each model.
  19. GOMS: Descriptive classification
    • A GOMS model is descriptive in the sense that it is a representation of the way a user performs tasks on a system.
    • The methods, sub-goals and selection rules provide the designer with a description of the process, rather than simply a time estimate.
  20. GOMS: Prescriptive classification
    • A GOMS model can also be considered prescriptive because it can as serve a guide for developing training programs and help systems.
    • Once a GOMS model has been developed for achieving a certain goal, this model can be used to teach new users how to achieve the goal.
  21. GOMS:  is it falsifiable? and why is that important
    Since the theory underlying GOMS models may not be truly falsifiable, GOMS should not be concerned a legitimate theory of human cognition.
  22. GOMS: Limitations:
    Its most significant fault is that the predictions are only valid for expert users who does not make any errors.

    • First of all, even expert users will make mistakes.
    • GOMS does not take into account novices who are just learning the system, or intermediate users who make occasional errors. Since one of the goals of HCI is to aim for maximum usability for all users, especially novices, this is a serious deficiency in the model

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