Notes: Understanding users

Understanding Users

  • Why Consider Users?

    • Computing is used by many people, not just technical professionals.

    • Problems arise if products or services cannot be used effectively by their intended user groups.

    • It's crucial to consider people's capabilities, limitations, needs, and desires.

    • There are many different users with varied abilities and needs; one cannot assume everyone is the same.

    • "Technology may change rapidly, but people change very slowly. The principles of good design never change."

  • History of User-Centered Computing Research

    • Late 1960s: Personal computing grew, leading to concerns about usability (ease and efficiency of interaction).

    • 1970s: Software engineering shifted focus to non-functional requirements like usability and maintainability.

    • 1980s: Human-Computer Interaction (HCI) emerged, focusing on improving people's interaction with computers.

  • Disciplines in User-Centred Design

    • Interaction Design: Creating intuitive and engaging user interfaces.

    • Human-Computer Interaction (HCI): Studying user interaction to improve usability.

    • User Experience (UX) Design: Enhancing overall user satisfaction and ease of use.

    • Requirements Engineering: Defining system functions and qualities, including usability and security.

  • Human Abilities and Capabilities

    • Design needs to consider physiological aspects (senses, movement, strength, fatigue) , cognitive aspects (attention, memory, learning, cognitive load) , and affective aspects (emotional responses like engagement, frustration).

    • Individuals' abilities vary and can change over time (e.g., due to aging), though some (like coping with stress) remain constant.

  • Limitations to Understanding Users

    • Humans are complex, so understanding their needs is always partial; it's impossible to predict every need or behavior.

    • Users are all different, making it impossible to design for every possible user or use case.

    • Users may struggle to articulate their needs.

    • Users' actual use may differ from what they say they will do.

  • Techniques for Considering Users

    • Scenarios: Stories describing how users interact with a system, helping designers imagine usage and identify problems.

    • Personas: Fictional "character portraits" representing typical users, based on real data, used to understand different user types and their unique needs.

Usability

  • Definition of Usability

    • "Usability refers to ensuring that interactive products are easy to learn, effective to use, and enjoyable from a user’s perspective" (Rogers et al., Interaction Design).

    • "The extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use” (ISO 9241-11).

  • Jakob Nielsen's Usability Engineering (1993)

    • Nielsen suggested "usability" over "user friendly," emphasizing it's multifaceted.

    • Usability is part of usefulness, which includes utility (does the system do what users need?) and usability (can users easily use its features?).

    • System acceptability depends on social and practical factors, with usefulness (utility + usability) being key.

  • Nielsen's Usability Characteristics

    • Learnability: The system should be easy to learn and have a reasonable learning curve.

    • Efficiency: Once learned, the system should be efficient to use and make the user productive.

    • Memorability: It should be easy to remember how to use the system, even after a break.

    • Errors and Safety: Users should make few errors, and if errors occur, they should be easy to recover from.

    • Satisfaction: The system should be pleasant and enjoyable to use.

  • Nielsen's Usability Mottos (Highlighting Complexity)

    • Your best guess is not good enough; design based on user data.

    • The user is always right (user feedback reflects real experiences).

    • The user is not always right (users may not know the best design solutions).

    • Users are not designers (they understand needs, not design).

    • Designers are not users (designers can't assume their preferences match users').

    • Less is more (simplicity improves usability).

    • Details matter (small design details greatly impact experience).

    • Help doesn’t (if users need help, the design isn't intuitive enough).

  • Evaluating Usability

    • Analytic approaches (Expert Evaluation): Assessing a system using guidelines or heuristics.

      • Heuristic Evaluation: Experts check against usability principles.

      • Walkthroughs: Experts simulate user interactions.

      • Standards/Guideline Checklists: Review compliance.

    • Empirical approaches (User Evaluation): Involving actual users.

      • Observations: Watching users.

      • Interviews/Focus Groups: Gathering feedback through discussions.

      • Questionnaires: Collecting structured feedback.

      • Usability Testing: Users complete tasks while being observed to identify issues.

  • Nielsen's Usability Heuristics

    • A heuristic is a practical, rule-of-thumb approach to problem-solving, aiming for a sufficient solution rather than a perfect one.

    • 1. Simple and natural dialogue: Interfaces should be easy and intuitive.

    • 2. Speak the users’ language: Use familiar terms and concepts.

    • 3. Minimise memory load: Users shouldn’t need to remember too many rules.

    • 4. Consistency: Actions should always have the same effect.

    • 5. Feedback: The system should always inform users about its actions.

    • 6. Clearly marked exits: Make it easy to cancel or undo actions.

    • 7. Shortcuts: Provide shortcuts for experienced users.

    • 8. Good error messages: Error messages should be clear, helpful, and polite.

    • 9. Prevent errors: Design the system to avoid mistakes.

    • 10. Help and documentation: Provide easy-to-find, well-structured help, but keep it simple.

  • Pros and Cons of Heuristic Evaluation

    • Pros: Quick and inexpensive, provides fast feedback, fewer ethical/logistical concerns.

    • Cons: Requires expertise, trained experts may be hard to find, may miss bigger issues while identifying minor ones.

  • Survey Measures for Usability: System Usability Scale (SUS)

    • Often used after usability evaluations to get quantitative user feedback on perceived usability.

    • Consists of 10 statements where users rate agreement, assessing intuitiveness, consistency, and ease of use.

  • Usability Testing

    • Users are assigned specific tasks to simulate real use.

    • Performance measures are recorded, such as task completion time, number of errors, and success rates.

  • Usability Metrics

    • Effectiveness: Percentage of tasks successfully completed (tasks completed / total tasks * 100).

    • Efficiency: Time taken for users to complete a task (faster means higher efficiency).

User Experience (UX)

  • Origins of UX

    • The term was coined in the 1990s by Don Norman.

    • UX refers to the overall experience and feelings a user has when interacting with a system, device, or product, including its context of use.

    • It recognizes that technology is about creating a satisfying and seamless experience, focusing on both functional and emotional aspects.

  • UX vs. Usability

    • User Experience (UX): Focuses on how a system feels to the user, including emotional responses and satisfaction; it's subjective and covers enjoyment, ease, and engagement.

    • Usability: More objective, measuring how efficient, effective, and easy it is for users to complete tasks; it's about practical functionality and productivity.

  • Designing a Good User Experience

    • It's the intentional creation of experiences through technology.

    • WHY: Understand user needs, emotions, and motivations.

    • HOW: Design the interaction (how users achieve goals).

    • WHAT: Determine what activities the product enables.

Dark Patterns

  • Definition: Deceptive UI design features that mislead users into making choices not in their best interest, exploiting human weaknesses for the service provider's benefit.

  • Inverting Nielsen's Heuristics with Dark Patterns:

    • Simple and natural dialogue: Dark pattern conceals key information.

    • Speak the users’ language: Dark pattern uses ambiguous or misleading language (weasel wording).

    • Prevent errors: Dark pattern exploits user errors by not offering confirmation options.

  • Capitalizing on Human Behaviors with Dark Patterns:

    • Users scan rather than read: Dark pattern hides key information in dense text.

    • Users stick with default options: Dark pattern sets defaults that favor the business.

    • Users are influenced by others: Dark pattern prominently displays positive feedback while obscuring negative reviews.

  • Examples of Dark Patterns:

    • The Roach Motel: Easy to get into a situation (e.g., subscribing), but difficult to exit (e.g., unsubscribing).

    • Forced Continuity: Requiring credit card for free trials, then automatically billing without notice or easy cancellation.

    • Bait and Switch: Users intend one action, but an undesirable one occurs instead (e.g., seeing a low price, then presented with a higher one).

    • Privacy Zuckering: Designing confusing jargon and interfaces that deceive users into sharing more personal information than intended.