HCI Track-A Understanding People 1 Week43

Lecture Notes: Human-Computer Interaction (HCI)

Introduction

In this lecture, we delve into the theoretical aspects of Human-Computer Interaction (HCI), focusing on understanding human perception, cognition, and motor skills, and how these can be applied in designing user interfaces (UIs).

Key Points:

• Understand the basics of human perception
• Understand the key mechanisms of visual perception
• Understand gestalt principles and their application to design of UIs
• Understand basic motor tasks and the laws that govern them
• Understand basics of human-cognition that governs how we interact with computers

Understanding People in HCI

Why Do Software Developers Need to Understand People?

• Designing for Usability: Systems must be usable by people; if users can’t use them effectively, the system fails.
• Enhancing User Experience: A good understanding of human behavior leads to better user experiences, encouraging continued use.
• Informing Design Decisions: Knowledge of human abilities and limitations helps in making informed design choices.
• Predicting User Behavior: Helps in anticipating how users will interact with the system.

Example:

• Software Adoption: If a software product is frustrating to use due to poor design, users are less likely to adopt it, impacting its success.

Aspects of Understanding People Relevant to HCI

• Perception: How people see, hear, and feel.
• Motor Skills: How people control their limbs and interact physically with interfaces.
• Cognition: How people think, remember, and pay attention.
• Needs and Motivation: What drives people to use certain technologies.
• Communication and Collaboration: How people interact with each other, especially in collaborative systems.

Perception

• Perception is the prime means to acquire information about the state of a computer.
• The ability to collect and organise information about the environment using our physiological sensory system.

Importance in HCI

• Designing Display Technologies: Requires knowledge of how eyes perceive information.
• Explaining Empirical Findings: Understanding perception helps explain user behaviors during studies.
• Designing Visualizations and Interaction Techniques: Requires understanding of perceptual principles.

Human Sensory modalities

• Primary Senses Used in HCI:
  • Vision: The most critical sense in computing, enabling users to see and interpret information.
  • Hearing: Used in auditory alerts and feedback.
  • Touch (Tactition): Used in tactile feedback like vibrations.

How they differ?

• Information rate
  • How much information can be sensed per unit of time?
• Parallelism
  • How much parallel processing of information can occur?
• Sensitivity
  • How much stimulation is needed for a receptor to activate?
• Receptive field
  • How large is the region of the brain that produces a feature from stimuli?
• Adaptation
  • How the sense attenuates signals?

Perceptual tasks

• Discrimination
  • The task of telling whether a difference occurs in sensory stimulation(e.g. light intensity, sound pitch, or texture)
• Detection:This task focuses on determining whether a specific event of interest occurs.
  • The task of telling whether an event of interest occurs (or not) in the environment(e.g. Seeing a notification pop up on a screen.)
• Recognition
  • The task of categorizing stimulus as something
• Estimation:This task pertains to quantifying a property of an object or event.
  • The task of estimating a property of an object of event in the environment(e.g. Estimating the distance to a car while driving.)
• Search
  • The task of localising an object of interest(e.g. Searching for a friend’s name in a contact list.)

Visual Perception

The Eye: Structure and Function

• Components:
  • Pupil: Allows light into the eye.
  • Iris: Controls the size of the pupil.
  • Cornea and Lens: Focus light onto the retina.
  • Retina: Contains photoreceptors (cones and rods) that convert light into neural signals.
  • Fovea: Area with high concentration of cones for sharp central vision.
  • Optic Nerve: Transmits visual information to the brain.

Photoreceptors(光感受器)

• Cones:
  • Responsible for color vision.
  • Concentrated in the fovea.
  • Function best in bright light.
• Rods:
  • Sensitive to low light levels.
  • Located in peripheral areas of the retina.
  • Do not perceive color.

Limitations and Brain Processing

• Blind Spot: Area where the optic nerve exits; no photoreceptors present.
• Perceptual Processing: The brain fills in gaps and makes assumptions to create a coherent visual experience.
• Example: Only the central 1-2 degrees of our visual field (the size of your thumbnail at arm’s length) is in sharp focus and color; the rest is peripheral and less detailed.

Gestalt Principles

Human vision is biased to perceive structure

Our visual system is biased to perceive structure and patterns, leading to principles that can be applied in UI design:

1. Proximity: Elements close to each other are perceived as a group.
2. Similarity: Similar elements are grouped together.
3. Enclosure: Objects enclosed together are perceived as a group.
4. Continuity: The eye is drawn along paths, lines, and curves, perceiving continuous patterns.
5. Closure: The mind completes incomplete figures to form familiar shapes.
6. Connection: Elements connected by lines are seen as related.

Examples in UI Design:

• File Browsers: Use of grouping and alignment to represent hierarchical relationships.
  • Proximity: In the file browser, the folders under “Previous 7 Days” (e.g., Design, Images, Meeting Notes) are grouped closely together, while the files within the “Images” folder (e.g., Image-1.png, Image-2.png) form another group.
  • Similarity: All file icons (e.g., Image-1.png to Image-12.png) are similar in design, helping users intuitively understand that they are files, as opposed to the folder icons, which are visually distinct.
  • Enclosure: The folders and files are visually grouped within distinct sections:
    • “Previous 7 Days” folders are enclosed in their own area.
    • The files within the “Images” folder are enclosed in a separate scrolling list on the right.
  • Connection: The selection highlight (blue box around Image-4.png) and the preview window on the right establish a connection, reinforcing that the selected file is linked to its preview.

• Sliders and Controls: Use of lines and shapes to indicate interaction possibilities.
  • Closure: seeing the whole even when only parts are visible
  • Continuity: seeing the whole even if partly occluded
  • Symmetry: choose interpretation that has highest symmetry

Visual Search Task Example

• Task: Find the price of a double room at a specific hotel from a list.
• Observation: Structured information (using Gestalt principles) allows users to complete tasks faster than unstructured information.
• Conclusion: Visual structure significantly impacts the ease and speed of information processing.

Perception Summary

• Sensor data is noisy, a lot of processing and guesswork happens
  • The raw information that our senses (like vision, hearing, touch, etc.) capture from the environment is often incomplete, ambiguous, or “noisy.”
• We can exploit that we have a tendency to perceive structure and things that stick out
  • This is connected to Gestalt principles and the broader idea that perception works by finding patterns or groupings in visual or sensory data.
• Perception is an active process
  • Perception is not passive—it’s not like a camera capturing the world as it is. Instead, it’s active and dynamic, involving constant interaction between your brain and the sensory input.
  • When walking in a forest, you may first see something that looks like a snake. As you get closer, your brain processes more details and adjusts its perception, realizing it’s just a curved branch. (Filters, Interprets, Adjusts)

Motor Control

Importance in HCI

Understanding motor control helps in designing interfaces that accommodate the physical actions users must perform, such as clicking, dragging, and typing.

Types of Motor Tasks

1. Target Acquisition:
   • Spatially Constrained Aimed Movements: Spatially constrained targeting actions are actions that have a specific target location to reach in physical or visual space.These actions are usually constrained by the boundaries, shape, or range of the target and require one to precisely aim at the target through visual or haptic feedback.
     • Discrete Aimed Movements: Discrete means that the goal has a clear start and end point, and the action stops when a task is completed. Like moving to and selecting a target (e.g., clicking a button).
     • Continuous Aimed Movements: In the absence of an obvious bounding box, it is necessary to keep the control point (e.g., mouse cursor, stylus, or hand) within a certain path or area by means of a sustained action.Like Maintaining control within a boundary (e.g., drawing with a mouse).
   • Temporally Constrained Movements: Time-constrained targeting actions require not only spatially aiming at the target, but also completing the action within a specific time window. Actions that must be completed within a time frame (e.g., catching a moving object).

Examples:

• Discrete Movement: Clicking on icons or buttons.
• Continuous Movement: Selecting text or drawing shapes.
• Temporally Constrained Movement: Less common in standard UIs; prevalent in games.

Fitts’ Law

A predictive model that estimates the time required to move to a target area, considering the distance to and size of the target.

Formula:

\[\text{Movement Time} = a + b \times \log_2 \left( \frac{D}{W} + 1 \right)\]

• D: Distance to the target.
• W: Width of the target.
• a,b: Empirically determined constants.(Device-dependent variables)

Fitts’ experiment

Key Terms:

• Width (Tolerance):
  • The width of the target, also known as the tolerance zone, defines how large the target is.
  • Larger targets are easier to hit and reduce movement time, while smaller targets require more precision and increase movement time.
  • The blue arrows in the image highlight the target width.
• Distance (Amplitude):
  • The distance from the starting point to the center of the target.
  • Greater distances require longer movements, which take more time to complete.
  • The blue arrows in the image highlight the distance from the starting point to the target.

The Experimental Setup:

• Participants use a pointing device (like the pen in the image) to move back and forth between two rectangular targets.
• The goal is to hit the target accurately and quickly.
• The width of the target and the distance between the targets are adjustable to create varying levels of difficulty.

Experimental Conditions:

• Four Target Distances (Amplitude):
  • 2, 4, 8, and 16 inches. Longer distances increase task difficulty.
• Four Target Widths (Tolerance):
  • 0.25, 0.5, 1, and 2 inches. Smaller widths require greater precision, making the task harder.

Key Points:

• Movement time increases with distance and decreases with target size.
• Doubling the distance has the same effect as halving the target size.
• Applicable across various devices (mouse, stylus, touchscreens).

Application in UI Design:

• Larger Buttons: Easier and quicker to click.
• Closer Targets: Reduce the distance users must move the cursor.

Reaction Types

1. Simple Reaction:
   • Responding to a single stimulus with a single response.
   • Something appears on the display and the user must respond to it a quickly as possible
   • Among the fastest human responses in HCI (measured in milliseconds from event to onset of response)
   • Example: Pressing a key when a light appears.
2. Choice Reaction:
   • Selecting one response from multiple options based on stimuli.
   • n options are available
   • Performance measured as choice reaction time (CRT)
   • Example: Pressing different keys depending on the color of a light.

Hick’s Law:

\[\text{Choice Reaction Time(CRT)} = a + b \cdot \log_2(n)\]

If “no reaction” is also a possible choice:

\[\text{Choice Reaction Time(CRT)} = a + b \cdot \log_2(n + 1)\]

• n: Number of choices.
• Reaction time increases logarithmically with the number of options.

Implications:

• Limit the number of choices presented to the user to reduce decision time.
• Organize options logically to aid quick decision-making.

Cognition

Cognitive Abilities in HCI

1. Control
2. Memory
3. Attention
4. Reasoning
5. Decision-making

What we know about cognition

• Cognition serves the control of action
• Cognition is limited
• Cognition is learned and adapts
• Cognition computes on representations of reality
• Cognition consumes energy

Cognitive Control

• Goal-Directed Behavior: Ability to direct thoughts and actions toward achieving a goal.
• Goal activation model (Altmann & Trafton)
  • Contextual Cues: Using environmental cues to trigger subgoals.
  • Contextual cues prime subgoals
  • postcompletion error (difficult to remember actions that has to be taken after completing a goal)
• Example: Navigating to a destination using familiar landmarks rather than planning the entire route beforehand.

Limitations

• Inattentional Blindness: Failing to notice unexpected stimuli when focused on a task.
• Energy Consumption: Cognitive processes consume significant energy, leading to fatigue
• Avoidance of Effort: The brain prefers to minimize energy expenditure by avoiding unnecessary thinking.

Multitasking

• Resource Competition: Performing multiple tasks can lead to decreased performance due to shared cognitive resources.
• Multiple Resource Theory: Explains how tasks compete for cognitive resources based on modality (visual, auditory), processing stages, and response type.

Example Analysis:

• Playing a Video Game and Following Social Media:
  • Both tasks require visual attention and manual responses, leading to high competition for resources.
  • Combining these tasks can significantly reduce performance in one or both tasks.

Cognitive Workload

• Definition: The total amount of mental effort being used in working memory.

• Measurement:

  NASA Task Load Index (TLX) assesses perceived workload across several dimensions:

  • Mental Demand
  • Physical Demand
  • Temporal Demand
  • Performance
  • Effort
  • Frustration

Application in UI Design:

• Minimize unnecessary cognitive load to prevent fatigue.
• Design interfaces that are intuitive and require less conscious effort.

Memory and Learning

Human Memory vs. Computer Memory

• Human Memory:
  • Prone to forgetting.
  • Requires repetition and rehearsal to strengthen memories.
  • Information can decay over time.
• Computer Memory:
  • Stores data reliably as long as hardware remains functional.
  • Does not forget unless data is overwritten or deleted.

Types of Memory

1. Short-Term Memory (Working Memory):
   • Limited capacity (about 2-6 items).
   • Information is transient and decays quickly without rehearsal.
2. Long-Term Memory:
   • Declarative Memory (Explicit):
     • Episodic: Personal experiences.
     • Semantic: Facts and general knowledge.
   • Non-Declarative Memory (Implicit):
     • Procedural Memory: Skills and actions (e.g., riding a bike).
     • Conditioning: Learned responses to stimuli.
     • Habituation: Decreased response to repeated stimuli.

Memory Experiment Example

Task: Memorize a list of words within two minutes.

Observation:

• Most people recall fewer than half the items.
• Demonstrates the limitations of short-term memory.
• Grouping or categorizing information can enhance memory retention.

Enhanced Example:

• Organizing words into categories (animals, colors, furniture) aids recall by providing contextual cues.

Implications for UI Design:

• Avoid overloading users with information.
• Use meaningful groupings and categories.
• Provide external aids (labels, icons) to reduce reliance on memory.

Human Memory

Types of Memory

1. Short-Term Memory (STM)
   • Temporary storage of information.
   • Limited capacity and duration.
2. Long-Term Memory (LTM)
   • Stores information over extended periods.
   • Involves processes of encoding and retrieval.

Encoding and Retrieval

• Encoding
  • Process of storing information into memory.
  • Requires attention and cognitive effort.
  • Memory traces are formed; some reach LTM, others are filtered out.
• Retrieval
  • Accessing stored information from memory.
  • Two main types:
    • Recall
      • Retrieving information without cues.
      • More challenging; relies solely on memory.
    • Recognition
      • Identifying familiar information when presented.
      • Faster and less error-prone.

Use of Environmental Cues

• We often rely on environmental cues to aid memory without conscious effort.
• Examples:
  • Navigating to the University
    • We use landmarks like the bakery or intersections as cues.
    • No need to remember the exact route; cues trigger memory.
  • External Aids
    • Notes and Post-it Notes
      • Writing reminders helps externalize memory.
      • Example: Writing “Remember the purple idea?” on a post-it can trigger associated memories.

Distributed Cognition

• Cognition is distributed between the mind and the environment.
• We manipulate our environment to support thinking and memory.
• Important insight: Our mind doesn’t function in a vacuum; it’s heavily influenced by surroundings.

Forgetting

• Forgetting is fundamental to how our memory system functions.
• Reasons for Forgetting:
  1. Decay Theory
     • Memory traces lose activation over time if not used.
  2. Interference Theory
     • Memory traces gets mixed up.
• Probability of Recall
  • Increases with the frequency of encountering or being reminded of the memory.

Practice and Automaticity

• Practice leads to Automaticity
  • Skills become automatic with extensive practice.
  • Example: Riding a bicycle becomes second nature over time.
• Learning Curve
  • Rapid initial improvement followed by diminishing returns.
• Spaced Repetition
  • Learning technique involving increasing intervals of time between reviews.
  • Flashcards and Tools:
    • Anki: Software that uses algorithms for optimal spaced repetition.
  • Application in Game Design:
    • Example: Legend of Zelda
      • Abilities are introduced and practiced over time.
      • Skills are reinforced through spaced repetition within the game.

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Reasoning and Decision-Making

• Reasoning(推理) is about thought processes that allow us to conclude something that we do know know already.
• Predictions are reasonings about the future
• Decision(决策) making is any situation where a number of options are given and one or a subset of them must be chosen.
  • Kahneman’s two systems

Cognitive Heuristics and Biases

Two Systems of Thinking (Kahneman)

1. System 1: Fast Thinking
   • Intuitive, emotional, and automatic.
   • Relies on cognitive heuristics and biases.
2. System 2: Slow Thinking
   • Analytical, deliberate, and effortful.
   • Monitors and intervenes in System 1 when necessary.

Common Cognitive Heuristics

1. Anchoring(锚定效应)
   • Centering decisions around an initial reference point.
   • Example: Shopping for a Gift
     • Find earrings for $100 (over budget).
     • Later find a necklace for $75.
     • The necklace seems cheaper relative to the earrings, leading to a purchase despite being over budget.
2. Decoying(诱导效应)
   • A reference point prevents us from seeing other options.
   • Example: Popcorn Pricing at the Cinema
     • Small: $3, Medium: $6.50, Large: $7.
     • The large seems like a better deal compared to the medium.
     • Customers buy the large, influenced by the pricing structure.
3. Availability Heuristic(可得性启发)
   • Relying on immediate examples that come to mind.
   • Example: Employee Promotion Decision
     • Jane is the best performer but once deleted a project unintentionally.
     • The memorable negative event weighs heavily.
     • Decision is biased due to the availability of that memory.
4. Status quo(现状偏好)
   • People tend to stay as they are and avoid change. Even when change may lead to better outcomes, the choice is still made to conservatively stick with the current option.
   • When companies make changes, employees are more inclined to stick with the old system rather than take a chance on trying a new one.
5. Bandwagon(从众效应)
   • People tend to follow the choices of others, believing that their behavior provides some sort of reliable reference.
   • On social media, a product that is recommended by a lot of people makes you more likely to buy it as well.

Impact on Design

• Designers must be aware of cognitive biases.
• Design interfaces that minimize negative biases and leverage positive heuristics.
• Considerations:
  • Presenting information to aid System 2 processing when necessary.
  • Avoiding designs that inadvertently exploit negative biases.

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Applications of cognitive science in HCI

Guidelines

Cognitive Models

• Scientific models that describe what happens in a person’s mind during a task
• Cognitive modelling very popular in early HCI also criticised heavily in later HCI!

Design Guidelines Based on Cognitive Psychology

1. Recognition Over Recall
   • Interfaces should minimize the user’s memory load.
   • Implementation:
     • Provide visible options and actions.
     • Use familiar icons and symbols.
2. Figure-Ground Perception
   • Utilize Gestalt principles to create structured and intuitive designs.
   • Implementation:
     • Clear separation between elements.
     • Use contrast to highlight important information.
3. Design for Slips (Errors)
   • Anticipate and mitigate user errors.
   • Implementation:
     • Make dangerous actions visually distinct.
     • Provide confirmations for critical actions.

The Model Human Processor

• A model user of a computer
  • Eyes and ears for input
  • Arm-hand-finger for output
  • Brain with processors and memories
  • each with performance parameters and connections
• Three interacting subsystems
  • Perceptual system
  • Motor system
  • Cognitive system

Perceptual Memory

Perceptual memory is like a buffer for sensor data.

• For each sensor, incoming stimuli are stored for a short time
  • Visual Image store: ~200m
  • Audio store: ~1500ms
• The incoming data encoding is represented physically
  • Low-level features of images, sound…

Perceptual Processor

Content in perceptual memory is processed to be symbolically coded.

• Coding takes time!
• Cycle time: TP = 100ms
• Shorter for features that “pop out” (e.g. movement)（对于显著特征，处理时间更短，例如运动）
• Integration of multiple similar events in the same cycle（同一周期内整合多个相似事件）
• Bloch’s Law: R = I x t
  • R: 感知强度
  • I: 刺激强度
  • t: 持续时间
• The processor cannot code all information before the next stimulus arrives.
• We sense more than we can process.
• There is more in the Perceptual Memory can be coded before it is replaced by new sensations.
• Order of coding is influenced by attention:
  • Top-down by what we focus on (e.g. what we are looking for)
  • Bottom up by features that draw attention
• Type of coding is influenced by
  • Gestalt principles: patterns and shapes
  • Associations triggered (e.g. faces seen before)
• The way something is encoded at perception time impacts on how it is stored in memory, and how it can be retrieved from memory

Perceptual Processor

Cognitive processing is based on a recognize-act cycle
As result of perception, symbolic information is available in working memory, to be worked on by the cognitive system:

• Recognize(highly parallel): activate associations stored in long-term memory
• Act(serial): decide what to do next, modifying working memory (“loading” the next task and required information)
  • Recognition highly parallel, but Act is serial: one task at a time
• Cycle time: TC = 70ms
• Uncertainty Principle: Decision time increases with the uncertainty about the judgment to be made, requires more cognitive cycles.
  • e.g. deciding whether to turn left or right at a confusing intersection will take longer because your brain needs to process more information and evaluate possible options.
• Cycle time can be shorter when greater effort is induced by the task
• Cycle time also diminishes with practice

Processors and Memories

• Purpose: Simplify and model human cognitive performance for HCI.
• Components:
  1. Perceptual System
     • Responsible for transforming external environment into a form that the cognitive system can process
     • Composed of perceptual memory and perceptual processor
     • Visual Store: Holds images for 200–300 ms.
     • Auditory Store: Holds sounds for ~1500 ms.
  2. Cognitive System
     • Responsible for processing perceived information and deciding how to act upon it.
     • Composed of working memory, long-term memory and the cognitive processor
     • Interprets information and decides actions.
     • Working Memory: Limited capacity; used for current tasks.
     • Long-Term Memory: Stores knowledge and experiences.
     • Recognize-Act Cycle: Takes ~70 ms per cycle.
  3. Motor System
     • Translating thought into action
     • Motor processor also has cycle time: minimum time required to issue a command TM = 70ms
     • Executes actions.
     • Cycle Time: Minimum of ~70 ms to initiate movement.
• Processing Times:
  • Perceptual Processor: ~100 ms
  • Cognitive Processor: ~70 ms
  • Motor Processor: ~70 ms
• Applications:
  • Estimating user response times.
  • Designing interfaces that align with human capabilities.
  • Examples:
    • Click Perception:
      • Maximum of ~10 clicks per second can be perceived distinctly.
    • Video Frame Rates:
      • Minimum of ~10 frames per second for motion perception.
      • Higher frame rates needed for interactive content (~60 fps).
    • Audio-Visual Synchronization:
      • Delays over ~80 ms between audio and video become noticeable.

Key points

• Understanding human performance in terms of time needed for different stages of information processing
  • Human performance can be understood by breaking it into distinct stages: perception, cognition (recognition and decision-making), and motor action.
• Perception cycle needed for coding of sensory information
  • Limits to perceiving stimuli as separate:
    • Sensory inputs (e.g., sights, sounds) need to be separated and processed individually in a perception cycle.
    • If stimuli arrive too quickly, the brain may struggle to differentiate them as distinct events.
  • Limits to how much sensory information can be processed:
    • The human brain has a capacity limit for processing sensory data.
    • Not all incoming stimuli can be fully perceived or encoded into memory.
• Cognitive cycles for recognition and decision-making
  • Once sensory input is perceived, the brain enters a cognitive cycle to recognize the input and make decisions about it.
  • More decisions = more cycles: Complex decisions require multiple cycles, increasing the total time needed to respond.
• Motor action
  • After a decision is made, the brain sends signals to muscles to perform the chosen action.
  • Minimum time to start or change a movement:
    • e.g. It takes time for the brain to process new information and update a hand movement when typing or clicking.
  • Perceive-recognize-act cycle:
    • The entire process of perceiving input, recognizing it, deciding on an action, and executing that action involves a minimum reaction time.
• Just a model!
  • This model simplifies the complex reality of human cognition and performance.
• Everything cannot be reduced to performance measures!

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Needs and Motivations

Maslow’s Hierarchy of Needs

1. Physiological Needs
   • Basic survival needs: food, water, warmth, rest.
2. Safety Needs
   • Security and safety.
3. Love and Belonging
   • Intimate relationships and friends.
4. Esteem
   • Prestige and feeling of accomplishment.
5. Self-Actualization
   • Achieving one’s full potential.

Motivations

• Motivation for using particular systems is related to which needs we anticipate these particular systems will fulfil.
• Needs are universal in contrast motives are individual

Limitations of Maslow’s Model

• Not universally applicable across cultures and individuals.
• Needs are complex, intertwined, and not strictly hierarchical.

Self-Determination Theory

• Modern approach to understanding motivation.
• Key Concepts:
  • People actively seek opportunities for growth and mastery.
  • Motivation is driven by:
    1. Autonomy
       • Desire to have control over one’s actions.
    2. Competence
       • Need to gain mastery and feel effective.
    3. Relatedness
       • Wanting to connect with others.

Intrinsic vs. Extrinsic Motivation

• Intrinsic Motivation
  • Engaging in activities for inherent satisfaction.
  • Examples:
    • Playing a game because it’s fun.
    • Learning a new skill out of curiosity.
• Extrinsic Motivation
  • Performing actions for external rewards or pressures.
  • Examples:
    • Using workplace software because it’s required.
    • Studying to get good grades.

Self-determination Continuum

Examples and Discussion

Systems Driven by Extrinsic Motivation

• Brightspace (Educational Platform)
  • Used because it’s required for courses.
  • Users have minimal intrinsic motivation to engage with it.
• Intranet at Work
  • Mandatory for job functions.
  • Design may suffer due to lack of user choice.

Systems Driven by Intrinsic Motivation

• Games
  • Played for enjoyment and challenge.
  • Exception: May become extrinsic if played professionally or to compete.
• Netflix
  • Used for entertainment and relaxation.

Motivation in Social Media Use

• Complex Interplay
  • Platforms like TikTok and Instagram can be both intrinsically and extrinsically motivating.
  • Snapchat Example:
    • Streaks Feature
      • Encourages daily interaction.
      • May shift motivation from intrinsic enjoyment to extrinsic obligation.

Internalization Process

• Movement from Extrinsic to Intrinsic Motivation
  • Over time, external activities can become internally rewarding.
  • Example:
    • A student initially studies to pass exams but develops a genuine interest in the subject.
• Intrinsic Motivation Undermined
  • Intrinsic enjoyment can diminish if external pressures increase.
  • Example:
    • An amateur musician starts playing gigs for money, shifting focus to financial gain.