Human-Computer Interaction 4. Human models Dr. Sunyoung Kim School of Communication & Information Rutgers university
Last class 1. Understand tasks: Task analysis 2. Consolidation: Affinity diagram 3. Describe tasks 1. Task characteristics 2. Scenario: Storyboard
Hawthorne effect the alteration of behavior by the subjects of a study due to their awareness of being observed
Recap: Task analysis The process of examining the way in which people perform their tasks • You can discover what the system will be used for and what • functionalities the system must provide In HCI, task analysis is the recording of physical and perceptual actions of the user whilst executing the task.
Recap: Affinity diagram The affinity diagram brings together issues and insights across all users into a hierarchical diagram to reveal the scope of the problem. Gathers large amounts of language data (ideas, opinions, issues) and • organizes them into groupings based on their natural relationships A single picture of the customer population a design will address • Shows how the work hangs together rather than breaking it up in lists • and what matters Used to brainstorm and generate ideas •
Recap: Task analysis: questions 1. Who is going to use system? 2. What tasks do they now perform? 3. What tasks are desired? 4. How are the tasks learned 5. Where are the tasks performed? 6. What’s the relationship between user & data? 7. What other tools does the user have? 8. How do users communicate with each other? 9. How often are the tasks performed? 10. What are the time constraints on the tasks? 11. What happens when things go wrong?
Recap: Scenarios A concise descript of a persona • A narrative description of a task : the current use of a system • An informal narrative story, simple, “natural”, personal • Presented through storyboarding • Scenario should be simple and focused • Use personas in scenarios – how does it serve their needs? •
Recap: Storyboards The point of storyboards is to convey the experience of using the • system Include people experiencing the design and their reactions to it (either • good or bad) Visual elements: Detail, text, people, frame, portrayal of time •
Today’s agenda Human models
Human models
Freezer is too cold but fresh food is just right. How would you adjust the control?
Gulfs of Execution & Evaluation The gaps between the user and the interface, pointing to how to better design an interface so that the user can cope with it Gulf of execution: the distance between the user's goals and the • means of achieving them through the system Gulf of evaluation: the amount of effort required to determine • the system state
. I'm fat because my metabolism Obesity is due to eating too is slow, hormone and gland much and not enough problems and too much stress. exercise. The patient is to Health professionals should help blame, so solutions must start me lose weight. I am most with the patient. The biggest worried about difficulties getting concern is diabetes. to work.
Mental models “The models people have of themselves, others, the environment and the things with which they interact. People form mental models through experience, training and instruction” An explanation of someone's thought process about how something • works in the real world Enable people to reason about a system • Affect the way we see and interpret reality • When users approach an unfamiliar system, they subconsciously refer to • their mental model, User’s model “ To break a mental model is harder than splitting the atom.” --Albert Einstein
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The Model Human Processor Published by Card, Moran & Newell, 1983, in the book “The • Psychology of Human-Computer Interaction” Consider humans as information processing systems • Core cognitive aspects • Attention • Perception and recognition • Memory • Reading, speaking, and listening • Problem-solving, planning, reasoning and decision-making, learning • Describes how a user interacts with a computer system •
Processors: Perceptual • Cognitive • Motor • Memory: Working memory • Long-term memory •
Human performance modeling Why model human performance? To predict impact of new technology/interface • Apply model to predict effectiveness • We could build a simulator to evaluate user interface designs •
(1) Perceptual processor Physical store from our senses: sight, sound, touch,… Code directly based on sense used • Visual, audio, haptic, … features • Selective Spatial • Pre-attentive: color, direction… • Decay time for working memory: 200ms
Pre-attentive A limited set of visual properties that are detected very rapidly and • accurately by the low-level visual system Typically, tasks that can be performed on large multi-element displays • in less than 200 to 250 milliseconds are considered pre-attentive.
How many 3’s? 1281768756138976546984506985604982826762 9809858458224509856458945098450980943585 9091030209905959595772564675050678904567 8845789809821677654876364908560912949686
How many 3’s? 1281768756138976546984506985604982826762 9809858458224509856458945098450980943585 9091030209905959595772564675050678904567 8845789809821677654876364908560912949686
How many 3’s? 1281768756138976546984506985604982826762 9809858458224509856458945098450980943585 9091030209905959595772564675050678904567 8845789809821677654876364908560912949686
Visual pop-out: color (hue) Resources from : https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
Visual pop-out: shape (curvature) Resources from : https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
Feature conjunctions Resources from : https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
Pre-attentive features Line (blob) orientation Length, width Closure Size Resources from : https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
Pre-attentive features Number, estimation Curvature Density, contrast Color (hue) Resources from : https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
Pre-attentive features Intensity, binocular lustre Intersection Terminators 3D depth cues Resources from : https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
Change blindness A perceptual phenomenon that occurs when a change in a visual stimulus is introduced and the observer does not notice it Our visual intelligence can only detect changes in those parts of the image to which we explicitly attend.
Selective attention The act of focusing on a particular object for a period of time while simultaneously ignoring irrelevant information that is also occurring This occurs on a daily basis and can be seen in basically any of your interactions. Because it is impossible to give attention to every stimulus in our environment, we use selective attention to select what stimuli are important as events occur.
The problem with the classic ‘7 ± 2’ George Miller’s theory of how much information people can remember • People’s immediate memory capacity is very limited • The number of objects an average human can hold in working memory • (short-term) is 7 ±2 Example: • DECIBMGMC vs. DEC IBM GMC 6174591765 vs. 617 - 459 - 1765
The problem with the classic ‘7 ± 2’ Wrong application of ‘7 ± 2’ theory: Designers present only 7 • options/menus/icons/tabs. Why? People can scan lists of bullets, tabs, menu items till they see the • one they want They don’t have to recall them from memory having only briefly • heard or see them ‘7 ± 2’ applies to serial presentation of information •
Chunking
Chunking
Chunking Hierarchy
Experiment Start saying colors you see in list of words When slide comes up As fast as you can
Ship Night Triangle Bus Pencil
Blue Green Red Orange Yellow
Stroop effect When the color spelled out by a word is incongruent with the color used to show that word, naming the word color is slower and more error prone. Explanation: Relationship between meaning and physical form of stimulus are in conflict.
Processors: Perceptual • Cognitive • Motor • Memory: Working memory • Long-term memory •
Working memory Working memory is small Temporary storage • Decay • Displacement •
Recognition over recall Recall – information reproduced from memory • Recognition • – Presentation of information provides cues that information has been encountered before – Easier because of cues (context) for retrieval
Recognition over recall Command line interface (recall) vs. GUI (recognition) interface •
Cognitive processor Typical matching time Digits: 33ms • Colors: 38ms • Geometry: 50ms… • Fundamentally serial One locus of attention at a time • Eastern 401, December 1972 •
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