Presentation is loading. Please wait.

Presentation is loading. Please wait.

Tutorial 4: Case Study “Set Phasers on Stun” SY DE 142 – June 7, 2004 Introduction to Human Systems Engineering Waterloo, Ontario, Canada.

Similar presentations

Presentation on theme: "Tutorial 4: Case Study “Set Phasers on Stun” SY DE 142 – June 7, 2004 Introduction to Human Systems Engineering Waterloo, Ontario, Canada."— Presentation transcript:

1 Tutorial 4: Case Study “Set Phasers on Stun” SY DE 142 – June 7, 2004 Introduction to Human Systems Engineering Waterloo, Ontario, Canada

2 Outline  Case Study: “Set Phasers On Stun”  Discussion on “Set Phasers on Stun”  Midterm Overview

3 Set Phasers on Stun Overview  Time: 1986  Place: East Texas Cancer Center, Tyler  Synopsis: A computer glitch turns miracle machine into monster for one cancer patient. Mode error combine with lack of feedback deliver a blast of 25,000 rads down onto the patient.

4 Set Phasers on Stun Interface Design  Draw out the general Human machine system model and redraw it for this case.  What feedback was available to Mary Beth and what was missing?

5 Set Phasers on Stun “ Information Displays” Human = Mary Beth - Interface = Therac Control Panel Machine = Therac World = Patient a: mary beth's command b: control signal c: rays d: patient state e: feedback on Therac state and actions f: feedback on interface state and actions (control signal sent) g: interface information

6 Set Phasers on Stun Feedback  Mary Beth needed to know: the control signal was sent the Therac mode that the Therac had sent out rays patient state. 14 marks: 5 for the draw, 5 for redraw and 4 for feedback

7 Midteram Overview SY DE 142 Midterm: Date: June 14, 2004 Time: 1:30 - 3:30pm Room: DC 1350 Aids Allowed: Text book: Wickens and Set Phasers on Stun Calculator Solutions must be written in pen, not in pencil.

8  Business in Bhopal  Silent Warning  In Search of the Lost Cord  An Act of God  The Wizards of Wall Street  Set Phasers on Stun Case Studies

9  Death on the Job  Bhopal, a Lingering Tragedy  Why Planes Crash  Broken Bus Films

10 Course Material Outline  Accident Analysis and Fault Trees Accident Analysis and Fault Trees  Mappings and Affordances Mappings and Affordances  Gulfs of Execution and Evaluation Gulfs of Execution and Evaluation  Human Action Cycle Human Action Cycle  Information Processing Information Processing  Human Decision Making Human Decision Making  Human Error - Mistakes Human Error - Mistakes  Human Error- slips Human Error- slips  Human machine model Human machine model  Displays Displays  Control Control  Human-Computer Interaction Human-Computer Interaction  Usability Testing Usability Testing  Automation Automation  More details on slides and in book.

11 Accident Analysis and Fault Trees  Linear interactions  Common mode interaction  Nonlinear interactions  Tight vs. Loose coupling  FMECA  Fault Tree Analysis Chronological Show causality Events: action and time (time often implicit) AND/OR gates Last event at the top OR AND

12 Mappings and Affordances  Mapping : relation between action and its result in the world Helps automatic processing when extremely strong between world and required action Two kinds; natural (steering wheel), social/cultural (light switch)  Affordance: perceived and actual properties of things that help to direct users’ actions, should be applied as a design principal “Affordances become visible by establishing mappings, (what it does, how it works)”

13 Gulfs of Execution and Evaluation (and HAC)  Gulfs: Execution: have an intention but can’t figure out action (difference in seq of action & action in the Human Action Cycle) Evaluation: Can’t figure out whether the goal has been achieved

14 GOAL WORLD Act Evaluate Intention Act! Evaluate Gulf of execution! Gulf of evaluation! Perception How is state of the world perceived? Use senses Interpret Sequence of Actions (what should be done) HUMAN ACTION CYCLE Interpret

15 Information Processing “How we Think”  Memory Short term, long term, how to improve, knowledge in head vs. knowledge in world  Perception Feature analysis (bottom-up processing), unitization, top down processing ----design implications  Attention Selective, divided ---- design implications Resource model, Multiple resource model

16 More Information Processing “How we Think”  Situation awareness (SA): being aware of meanings of dynamic changes in the environment 3 stages: Perceive, understand, predict Measuring SA: by SA Global Assessment technique (SAGAT)  Decision making Normative model (methods: multi-attribute utility theory, expected value theory, SEUT) Descriptive model (methods: satisfaction not optimal, heuristics, and biases to create easier ways of thinking)

17 Human Decision Making  Heuristics and Biases in Human decision making (look at updated lecture notes) could happen in any of the following stages: 1. Getting information input (input or cue biases) 2. Generating hypotheses and selection ( 6 biases). 3. Plan generation and action choice (4 biases).  SRK Framework Skill based decisions (automated) Rule Based decisions (procedural) Knowledge based decisions

18 Human Error -- mistake  Mistake: wrong goal and intention but right action Why it happens? Types of mistake mistaken similarity, misjudged probability, rationalizing small events, social pressures/cultural factors and $  Forcing Functions

19 Human Error -- slips  Slip: right goal and intention but wrong action, Mostly occurs with skilled behavior (WHY?) Mode Error: right action in wrong mode (therefore the action becomes WRONG)

20 Information Displays Human-Machine Model  Human machine system model : Elements: user Interface machine World begins with Action : Operator acts on the interface. Interface sends a control signal to the machine. Machine acts on the world.  Feedback: (4 feedbacks) State of world to interface Action of machine to interface Indication of control signal (machine to interface) Information from interface to operator  Any missing item may cause an accident

21 Display contents  should permit evaluation and execution  Display principles: Perceptual (legible, give reference, redundancy, design for distinctive features) Mental model (pictorial, moving part, ecological) Attention (multi-resource, proximity compatibility, information access cost) Memory (predictive aids, knowledge in the world, consistency

22 Display forms  Digital vs. Analog (precision vs. change)  Configural displays Rankine cycle Polar star display  Heads-up  Ecological displays

23 Control  Control vs. display : control is same as display till user interacts with system through display  Very important in design same guidelines as displays.  Laws and principals: Hick-Hyman law for Reaction Time Fitts law for Movement Time  Control Types : zero order (mouse), first order (steering wheel) and second order (thrust of shuttle)

24 Human-Computer Interaction  What your focus is as a designer: User group: who is using your system (novice, infrequent, frequent expert) and what should you know about these users. Interaction styles: how will the user (based on expertise) interact with the system (eg. Menu, form, QA, command language, function keys, direct manipulation, natural language, ….)

25 Usability and user testing Usability Approaches (4)  Cognitive walkthrough  Heuristic evaluation (Neilson’s usability principals)  Performance measurement  Field study Tasks Usability measures (satisfaction, learnability, errors)

26 Automation  When and why use automation  Classes of automation Information acquisition (warnings, filters) Information integration (pattern recognition, expert systems) Action selection (TCAS) Action execution and control (autopilots, cruise control)

27 Automation  Levels of automation  Reliability Issues: complacency (over trust), mistrust, dumb and dutiful effect.  Best form is Human Centered Automation

28 Good luck

Download ppt "Tutorial 4: Case Study “Set Phasers on Stun” SY DE 142 – June 7, 2004 Introduction to Human Systems Engineering Waterloo, Ontario, Canada."

Similar presentations

Ads by Google