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Final

IAT 201 Study Guide - Final Guide: Visual Thinking, Usability Testing, User Experience


Department
Interactive Arts & Tech
Course Code
IAT 201
Professor
Brian Fisher
Study Guide
Final

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IAT201 Exam Relevant Material
Week 1 Intro and the Big Picture
Readings
A Project Guide to UX Design
Chapter 1 "The Tao of UXD" 8 pages
Week 2 ID/UXD Intro
User experience, usability, utility, usability heuristics (Explain Compare & Contrast; Examples)
Explain design guidelines/heuristics [e.g. Visibility, Feedback, Constraints, Consistency,
Affordances, Mapping, Simplicity/Elegance] and how they contribute to effective ID
Design approaches: e.g. User-Centered Design (UCD) vs. Genius (aka Rapid Expert) Design:
compare & contrast, pros & cons
Readings
Designing for Interaction
Chapter 2 "The 4 approaches to ID" 16 pages
A Project Guide to UX Design
Chapter 5 "Understanding the Current State" 4 pages
Week 3 ID Lifecycle
Lifecycle models: sketch & label/explain one of them
Procedures & components of user-centered, effective ID
Why hypothesis-testing in ID/UXD? How? Examples
Readings
A Project Guide to UX Design
Chapter 2 "Choose your hats" 4 pages
Chapter 4 "Project Objectives and Approach" 15 pages
Week 4 Needs/Requirements
Heuristics, project requirements/requirements specification, project goals, usability goals, user
experience goals, user problems, design hypotheses, conceptual models: What are they? When
used? Why/how? How different? Examples e.g. difference between usability goals & user
experience goals 3 examples each
Functional vs. non-functional requirements: What's the difference? Examples
Heuristic evaluation: What? Why? How used? Drawbacks? Ability to perform one properly.
Personas: What? Why? How used?
“Don’t test users, test hypotheses”: What are "design hypotheses"? How can hypothesis-testing
be used in interaction design? Examples Why might it make sense (benefits)?
Why spend time & effort on ID1 “define” phase?
Why spend time & effort on user research?
Data gathering approaches: Explain; When to use what? Why? How?
Potential biases in user recruitment? Why care? How to avoid?
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