Lecture 2 - Human cognition.pdf

Human Cognition SWE 482 2024 Adapted with permission from Dr. Thomas LaToza Overview - Human Cognition: Why is this important for us? - Human Psychology 101: Abridged for Engineers - Design Implications of Human Psychology: People Matter...

Human Cognition SWE 482 2024 Adapted with permission from Dr. Thomas LaToza Overview - Human Cognition: Why is this important for us? - Human Psychology 101: Abridged for Engineers - Design Implications of Human Psychology: People Matter 2 In Class Discussion Today’s question: What makes someone an expert? 3 What Makes Someone an Expert? We will revisit this later in the lecture… 4 Human Cognition Human cognition refers to the range of mental processes by which humans become aware of the world and make sense of it. These processes include: Perception: The ability to see, hear, or become aware of something through the senses. Attention: The concentration of awareness on some phenomenon to the exclusion of others. Memory: The process by which information is encoded, stored, and retrieved. Learning: The acquisition of knowledge or skills through experience, study, or being taught. Decision making: The process of making choices by identifying a decision, gathering information, and assessing alternative resolutions. 5 Why is Human Cognition Important? Importance of Understanding People “much of the design is done by engineers who are experts in technology but limited in their understanding of people. ‘We are people ourselves,’ they think, ‘so we understand people.’ But in fact, we humans are amazingly complex. Those who have not studied human behavior often think it is pretty simple. Engineers, moreover, make the mistake of thinking that logical explanation is sufficient: ‘If only people would read the instructions,’ they say, ‘everything would be all right.’” The Design of Everyday Things Don Norman 7 Real World Example: 3 Mile Island 8 Real World Example: 3 Mile Island 9 Thinking Fast and Slow 345 x 174 = ? Career paths? SW dev Tester Business analyst project manager other? Two Types of Human Cognition Type 1 System Type 2 System Automatic (unconscious) Voluntary Effortless (conscious) “Fast” thinking Effortful “Slow” thinking Associative Planning Heuristic Logical Gullible Lazy Can’t be turned off Usually only partly on 16 Examples of System 1 Facial Recognition: Instantly recognizing a friend's face in a crowd. Emotional Response: Feeling a surge of happiness when you hear someone. Social Cues: Intuitively understanding body language or social cues in a conversation, like knowing someone is bored without them saying it. Familiar Task Execution: Making a cup of tea or coffee in the morning on autopilot, without actively concentrating on each step. Learned Motor Skills: Riding a bicycle or typing on a keyboard Immediate Judgment: Making a snap judgment about a situation as safe or dangerous. Pattern Recognition: Noticing the similarity in a series of numbers or figures at a glance, such as recognizing a repeated sequence. 17 Examples of System 2 Problem Solving: Working through a complex math problem that requires conscious effort and understanding of each step. Decision Making: Considering which insurance plan to buy based on comparing benefits, costs, and your personal circumstances. Focused Attention: Driving in a new city Self-Control: Resisting the urge to eat junk food when trying to maintain a healthy Strategic Planning: Mapping out your career path, setting long-term goals Complex Learning Tasks: Learning to play chess well, Financial Planning: Budgeting your monthly expenses requires calculation and the discipline to stick to your budget. 18 Psychology 101: Attention Attentional Resources are Fixed 20 Attentional Resources are Fixed 21 Attentional Resources are Fixed System 2 activity takes conscious attention Attentional resources are fixed Pupils dilate as mental effort increase If demands exceed max, tasks prioritized. 22 Examples of Attention Limitations Can walk and talk But not walk and compute 23 x 78 Constructing complex argument better when still 23 Attentional Limitations - Demo Remember the following digits: 835219051 24 Attentional Limitations - Demo Would you prefer (a) (b) 25 Attentional Limitations - Demo More likely to choose (a) when attentional resources are stressed Self control require attention and effort 26 Coexistence of Systems 1 and 2 System 1 processes normal, everyday, expected activities at low cost. System 2 takes over when necessary, at higher cost. Law of least effort: pays for System 2 to be lazy. People tend to choose the easiest or least demanding option to achieve a desired outcome. Suggests that we naturally gravitate towards options that require less cognitive effort 27 Psychology 101: Memory Short Term Memory (STM) Working memory Primary, active memory used for holding current context for System 2 Unless actively maintained (or encoded to long-term memory), decays after seconds Capacity ~ 4-7 items 29 Chunking - Demo What is the easiest to remember? A. A lock combination with 8 numbers in order: 50, 30, 60, 20, 80, 10, 40, 70 B. A string of 10 letters: R, P, L, B, V, Q, M, S, D, G C. A string of 23 letters: I like to live in Riyadh city 30 Chunking Items in memory encoded as chunks A memory strategy that involves grouping individual items together into larger, more meaningful units. A chunk may be anything that has meaning # of chunks in STM fixed, but remembering bigger chunks lets you remember more By creating larger, more meaningful chunks, we can effectively increase the amount of information we can remember. Memory retention relative to the concepts you already have Learn how to drive a different car? Examples chunking, location, category, function 31 Long Term Memory (LTM) Items in short term memory may be encoded into storage in long term memory LTM capacity not limited Information must be retrieved from long term memory (i.e., through System 1) Many factors influence what is encoded into LTM and how it is encoded 32 Memory is Reconstructive - Example How fast was the car going when it hit the other vehicle? vs. How fast was the the car going when it smashed into the other vehicle? 2x more remember seeing broken glass 33 Memory is Reconstructive - Example How fast was the car going when it hit the other vehicle? vs. How fast was the the car going when it smashed into the other vehicle? 2x more remember seeing broken glass 34 Memory is Reconstructive - Example The study suggests question phrasing can alter memories. This has implications for eyewitness testimony reliability. 35 Memory is reconstructive Not stored files on a disk Encoded in brain, may be different every time retrieved Remember pieces, reconstruct other details based on expectations on what must have occurred Hard to distinguish similar memories Multiple visits to the same place? 36 Psychology 101: Learning Rehearsal Information may be repetitively experienced or actively repeated (“subvocalization”) 232 535 487 235 More times information is rehearsed, better memory Enhancing Rehearsal: Spacing effect: Spreading out rehearsal sessions over time, Interleaving: Practicing different skills or topics in a mixed order 38 Depth of Processing More time spent interacting with information, more likely it is to be remembered Deeper processing includes summarizing the key points or drawing a mind map, making connections. 39 Automaticity Perform actions or make decisions effortlessly This effect happens for sequences of actions (“scripts”) as well. Example: tying shoelaces More repetitions, faster, requires less conscious attention. Responsibility shifts from System 2 —> System 1 40 Habit formation takes time How long does it take to form an eating, drinking, or checking FB before bed habit? Mean: 66 days, Min: 18 days, Max: 254 days More complex behaviors take longer to become habit 41 Habit formation takes time How long does it take to form an eating, drinking, or checking FB before bed habit? Mean: 66 days, Min: 18 days, Max: 254 days More complex behaviors take longer to become habit 42 Psychology 101: Affect Affect Current emotional state Valence: positive or negative Arousal: strength of activation of sympathetic nervous system 44 Affect Affects Focus and Creativity Negative affect / high arousal Positive affect / lower arousal Escape from danger Better brainstorming and generating alternatives Fire & door doesn’t open —> push harder More likely to work around minor difficulties —> better usability Neurotransmitted bias brain to See bigger picture, less focused focus on problem & ignore distractions Tunnel vision on most relevant aspects 45 Performance / Arousal Curve Yerkes / Dodson law Arousal increases performance for System 1 tasks, but only increases performance on System 2 tasks up to a threshold 46 Design Implications from Psychology General Design Implications Take advantage of System 1 where possible Don’t confuse System 1 (e.g., consistent mapping in next lecture) Users can be stubborn (sunk cost investment in current strategy) People can get upset when have goals they cannot accomplish, as attentional resources exhausted solving problem and less self control Let users doing something else while waiting 48 Design Implications: What Makes an Expert? What Makes an Expert? 50 What Makes an Expert? Experts are more intelligent? IQ doesn’t distinguish best chess players or most successful artists or scientists (Doll & Mayr 1987) (Taylor 1975) Experts think faster or have larger memory? World class chess experts don’t differ from experts (de Groot 1978) 51 What Makes a Grand Master a Chess Expert? Memory for random chess boards: same for experts and novices Memory for position from actual game: much better for experts than novices [deGroot 1946; Chase & Simon 1973] 52 Schemas (a.k.a chunking) Experts think differently. Have schemas that help them to Recognize and react to common situations through System 1 Encode the world in more abstract terms Solve problems more effectively 53 Don't Make the User Think Let users use (automatic) skills of System 1 rather than (conscious) knowledge-based problem solving of System 2 Key principle What this means: let users think about everything except for interface interactions If user goal is to write a document, want user thinking about what they're writing, not how to use word processor 54 Mental Models Mental Models (a.k.a Conceptual Models) Internal representation in the head of how something works in the real world E.g., changing appropriate knob adjusts temperature in freezer or refrigerator 56 Mental Models Only single temperature sensor. Controls not independent, need to adjust both. (also delayed feedback) 57 External Representations Reduce STM burden Help restructure and reframe problem w/ new abstractions, changing operators Encode information and relationships through use of space Serve as reminders for future goals 58 Designing for Human Actions Humans are Goal-Oriented Goal: Make text flow into empty space 60 Gulfs of Execution and Evaluation 61 Norman’s 7 Stages of Action 1. Goal (form the goal) 2. Plan (the action) 3. Specify (action sequence) 4. Perform (action sequence) 5. Perceive (the state of the world) 6. Interpret (the perception) 7. Compare (outcome w/ goal) 62 Designing for Action Key challenge is designing interactions that help users to accomplish their goals 63 7 Principles of Designing for Action 1. Discoverability 2. Feedback 3. Conceptual Model 4. Affordances 5. Signifiers 6. Mappings 7. Constraints 64 1. Discoverability IT should be possible to determine possible actions and current state of device Which has more discoverable commands: Eclipse or emacs? 65 2. Feedback There should be full and continuous info about the results of actions and the current state 66 3. Conceptual Model Design should project all of the information needed to create an accurate conceptual model. 67 4. Affordances The proper affordances exist to make the desired actions possible. Affordance: Relationship between an object and a user that determines how it can be used. 68 5. Signifiers Signifiers should communicate the affordances of an object, and provide feedback 69 6. Mapping The relationship between controls and their actions should follow intuitive spatial layouts and temporal contiguity. 70 Example - Stove Burners 71 Natural Mapping Best mapping: controls mounted next to item to be controlled Second best mapping - controls as close as possible to item to be controlled Third best mapping - controls arranged in same spatial configuration 72 Consistent Mapping Control consistently leads to same action Facilitates System 1 - taking action always leads to the same effect 73 7. Constraints Provide physical, logical, semantic, cultural constraints to guide actions and ease interpretation 74 Physical constraints Constrain possible operators (e.g., round peg, square whole) Rely on properties of artifact, no training required 75 Lock-Ins Keeps an operation active, preventing someone from prematurely stopping 76 Lock-Outs Prevents an event from occurring 77 Inter-Locks Force actions to take place in the proper sequence 78 Cultural, Semantic, & Logical Constraints Norms, conventions that describe possible actions 79 Example: Faucets Control 2 Variables: temperature, rate of flow Physical Mental Model: water enters through 2 pipes Potential Solutions: Separate controls for hot and cold Control only temp / control only flow On / off One control 80 Example: Faucets Mapping problems: Which controls hot and which cold? How do you change temperature w/ out flow rate? How do you change flow w/out temperature? Which direction increases water flow? 81 Example: faucets Standard conventions: left hot, right cold; counter-clockwise turns it on But Not in England Not always on shower controls Not always for blade controls 82 Norman’s designing for action principles 1. Discoverability - make it possible to determine possible actions and state 2. Feedback - full and continuous feedback about result of action 3. Conceptual Model - design communicates info for conceptual model 4. Affordances - desired affordances exist 5. Signifiers - effective use of signifiers to communicate 6. Mapping - relationship between controls and goals uses good mapping 7. Constraints - physical, logical, semantic, cultural constraints 83