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Keystroke-Level Model (KLM)
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Today, we're going to start with the Keystroke-Level Model or KLM. KLM is the simplest model within the GOMS family. Can anyone tell me what GOMS stands for?
Goals, Operators, Methods, Selection rules.
Correct! KLM emphasizes the linear breakdown of task execution into observable atomic operators. Does anyone remember what some of these operators are?
Keystroke, Pointing, and Mental preparation!
Great job! Each operator has a specific average time associated with it. Why is KLM particularly beneficial for designers?
Because it allows for rapid time estimates before prototypes are built!
Exactly! The predictive nature is essential for early design decisions. Let's remember that KLM provides a quick yet formalized approach to evaluating user performance efficiently.
Natural GOMS Language (NGOMSL)
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Moving on to NGOMSL, can anyone explain what makes it a useful tool for designing GOMS models?
It has a consistent syntax, which helps in understanding and analyzing models more effectively!
Right! This structured notation improves clarity and allows for automated analysis. In lengthy models, what problems might NGOMSL help solve?
It can help in identifying inconsistencies or errors systematically.
Exactly! This formal approach increases reliability in user interactions. Remember, structured models equal clearer implementations, which are vital in design.
Cognitive Perceptual Motor GOMS (CPM-GOMS)
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Now let's dive into CPM-GOMS. How does it differ from basic GOMS and KLM?
It accounts for parallel processing, mimicking real human cognitive functioning!
Correct! CPM-GOMS allows multiple actions to occur simultaneously, unlike KLM, which struggles with this complexity. Why might this be particularly useful?
It provides a more accurate execution time and reflects how users actually interact with systems!
Excellent insight! Understanding this parallel processing is essential for crafting highly efficient user experiences. Always remember, higher complexity models can better guide design but require more effort!
Introduction & Overview
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Quick Overview
Standard
The section offers a comprehensive overview of important variations of the GOMS modeling approach, exploring KLM as a basic predictive model, NGOMSL for structured notation, and CPM-GOMS for parallel processing analysis. Each model serves specific needs in evaluating user-performance efficiency in human-computer interactions.
Detailed
In this section, we delve into important variations and extensions of the GOMS family, which includes innovative models that enhance the original GOMS structure founded by Card, Moran, and Newell. The Keystroke-Level Model (KLM) simplifies and focuses on linear time predictions for tasks by breaking them down into atomic actions, making it accessible for rapid estimations. The Natural GOMS Language (NGOMSL) serves as a formalized syntactic tool for building GOMS models, promoting clarity and automation in analysis. Lastly, the Cognitive Perceptual Motor GOMS (CPM-GOMS) introduces a more complex framework that acknowledges parallel human information processing, adapting principles from project management to offer a more accurate representation of execution time in high-performance scenarios. These extensions vary in complexity and applicability, showcasing the versatility of GOMS in improving user interface designs by providing structured methods for estimating task performance.
Audio Book
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KLM (Keystroke-Level Model)
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As previously discussed, KLM is the simplest GOMS model, focusing exclusively on the linear summation of operator execution times without explicitly modeling goals, methods, or selection rules. It's often used for rapid, low-fidelity time predictions.
Detailed Explanation
The Keystroke-Level Model (KLM) is a foundational model in the GOMS family. It simplifies user actions into a series of discrete operations, allowing analysts to predict how long a task will take based on an average time for each type of action (e.g., keystrokes, mouse clicks). KLM doesn't account for cognitive aspects such as the user's goals or methods but rather focuses solely on timing, which makes it excellent for quick assessments of interface designs. This model is particularly useful for evaluating tasks that expert users perform routinely and consistently, as it can provide rapid predictions without the need for complex analysis.
Examples & Analogies
Imagine a chef who knows the exact time it takes to chop onions, sautΓ© vegetables, and cook pasta. If the chef only cares about efficiently preparing a dish (like KLM), they wonβt worry about the recipe steps (goals) or different ways to combine the ingredients (methods). They just want to know how long it takes to execute each chopping and cooking action to estimate when the meal will be ready.
NGOMSL (Natural GOMS Language)
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This is a more formalized, structured notation for writing GOMS models. It provides a consistent syntax that facilitates automated analysis, consistency checking, and even the generation of simple simulations of user behavior. Its natural language-like structure makes it more readable than purely symbolic representations.
Detailed Explanation
NGOMSL offers a standardized method for documenting the GOMS models, making them easier to understand and analyze. By utilizing a structured language that resembles natural communication, it helps bridge the gap between technical modeling and readability. This structured format also allows researchers and designers to quickly validate their models and even run simulations based on them, making predictions about user behavior more straightforward.
Examples & Analogies
Think of NGOMSL as a recipe written in a clear format that anyone can read, compared to a traditional recipe that uses obscure abbreviations. If you have a friend who hasn't cooked the dish before, a well-written recipe (NGOMSL) will help them understand the steps easily, just as this notation helps designers grasp the user interactions laid out in GOMS models.
CPM-GOMS (Cognitive Perceptual Motor GOMS)
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This is the most advanced and complex variant of GOMS. CPM-GOMS explicitly models the parallel nature of human information processing. Instead of simply summing sequential operators, it accounts for situations where a human can perform multiple actions simultaneously (e.g., perceiving new information while a motor action is underway, or beginning to think about the next step while typing). It leverages concepts from Critical Path Method (CPM) from project management to identify the longest sequence of dependent operations (the 'critical path'), thereby providing a more accurate and tighter lower bound on execution time, particularly for highly skilled users who exploit parallel processing. This level of analysis is often reserved for highly optimized, high-performance systems.
Detailed Explanation
CPM-GOMS expands on the basic GOMS by recognizing that human cognition isnβt strictly linear; people often juggle multiple actions at once. It employs a more intricate mathematical framework to assess how various tasks can occur in parallel, thereby providing a nuanced understanding of user performance in complex situations. This parallel processing capability allows designers to appreciate the efficiencies that skilled users achieve, offering new insights into optimizing tasks designed for high performance.
Examples & Analogies
Think of a multitasking chef preparing a meal: while simmering sauce, chopping vegetables, and boiling pasta all at the same time, they mitigate how long the meal takes to prepare. CPM-GOMS models such parallel actions, capturing the complex interplay of tasks that occurs as the user processes information and executes commands, ensuring that the design of the kitchen (or interface) supports such multitasking effectively.
Definitions & Key Concepts
Learn essential terms and foundational ideas that form the basis of the topic.
Key Concepts
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KLM: A foundational model focusing on linear task performance prediction.
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NGOMSL: A structured notation that improves clarity and consistency in GOMS models.
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CPM-GOMS: Provides a framework for parallel processing analysis, enhancing predictive power.
Examples & Real-Life Applications
See how the concepts apply in real-world scenarios to understand their practical implications.
Examples
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KLM can rapidly estimate the time for a routine task that involves simple keystrokes.
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NGOMSL makes it easier to conduct automated error-checking in longer GOMS models.
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CPM-GOMS helps in understanding how users can perform cognitive actions and motor tasks simultaneously in an interface.
Memory Aids
Use mnemonics, acronyms, or visual cues to help remember key information more easily.
π΅ Rhymes Time
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GOMS is the way, to know what users say, by breaking tasks down, efficiency is found!
π§ Other Memory Gems
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Remember GOMS with 'GOMS: Goals Oriented, Model Simplifies!'
π Fascinating Stories
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Imagine a chef (G) with specific recipes (O), each requiring steps (M), and knowing when to use them (S) β that's how users interact!
π― Super Acronyms
For CPM-GOMS think 'CPM
- Critical Path Methods for model optimization!'
Flash Cards
Review key concepts with flashcards.
Glossary of Terms
Review the Definitions for terms.
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Term: GOMS
Definition:
An acronym for Goals, Operators, Methods, and Selection rules; a framework for analyzing user interaction with systems.
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Term: KLM
Definition:
Keystroke-Level Model; a method for predicting the time it takes a user to perform a task using a series of keystrokes.
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Term: NGOMSL
Definition:
Natural GOMS Language; a formalized notation for GOMS that aids in clarity and automated analysis.
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Term: CPMGOMS
Definition:
Cognitive Perceptual Motor GOMS; a model emphasizing parallel processing in human-computer interaction.