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Cognitive Engineering PSYC 530 Introduction to Human Factors and Cognitive Engineering

Cognitive Engineering PSYC 530 Introduction to Human Factors and Cognitive Engineering

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Cognitive Engineering PSYC 530 Introduction to Human Factors and Cognitive Engineering

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  1. CognitiveEngineeringPSYC 530Introduction to Human Factors and Cognitive Engineering Raja Parasuraman

  2. Introduction:History of Human FactorsThe Systems Approach

  3. DATES • Test 1: September 18 (take home) • Test 1 due: September 25 • Test 2: October 23 (in class) • Last date for approval of topic for class presentation and term paper due: November 6. • Class presentations: November 13, 20, and 27. • Last class: December 4 • Term paper due: December 10

  4. Overview • What this course is about • What this course is not about • Course objectives • Topics • History of Human Factors • The Systems Approach

  5. Terms, Terms, Terms……! • Engineering Psychology • Applied-Experimental Psychology • Human Performance Engineering • Human Factors • Ergonomics • Cognitive Ergonomics • Cognitive Engineering

  6. Professional Societies • Applied-Experimental and Engineering Psychology (Division 21, American Psychological Association) • Journal: Journal of Experimental Psychology: Applied • Human Factors and Ergonomics Society (USA) • Journals: Human Factors, Ergonomics in Design, Journal of Cognitive Engineering • Ergonomics Society (UK) • Journal: Ergonomics; Applied Ergonomics • International Ergonomics Association (IEA) • ACM Special Interest Group on Computer-Human Interaction (SIG-CHI) • Journal: CHI Proceedings • IEEE Systems, Man, and Cybernetics Society • Journal: IEEE Transactions on Systems, Man, and Cybernetics, Part A.Systems and Humans

  7. What this course is about • Provides a basic background on the role of human cognitive capabilities and limitations in the design of products, work places, and large systems. • The course emphasizes theories and findings on human performance, rather than the design of systems per se.

  8. What this course is NOT about • A course in cognitive engineering design • A basic course in cognitive psychology

  9. Engineering Psychology vs. Human Factors vs. Experimental Psychology “The aim of engineering psychology is not simply to compare two possible designs for a piece of equipment [which is the role of human factors], but to specify the capacities and limitations of the human [generate an experimental data base] from which the choice of a better design should be directly deducible.” (Poulton, 1966)

  10. Why this Course is Not Human Factors Design Boeing 777 Flight Deck Designing a safe and efficient automated cockpit Successful design may involve the application of human performance principles, but not necessarily their discovery Designing a safe and usable infusion pump

  11. Why this Course is Not Cognitive Psychology Stimulus Response Inferred Information Processing Components “The Machinery of the Mind”

  12. Why this Course is Not Cognitive Neuroscience Stimulus Response “Peering into the Black Box”

  13. Because Minds and Brains are “Situated”—in a Body and Environment with Artifacts and Tools—Hence Cognitive Engineering

  14. Why this Course is Not Cognitive Psychologyor Cognitive Neuroscience Successful cognitive psychology or cognitive neuroscience may involve the discovery of principles, but with no requirement to apply those principles or to ensure that they describe phenomena outside the laboratory

  15. NeuroergonomicsUsing Brain Function to Enhance Human Performance in Complex Systems

  16. Neuro-Ergonomics The scientific study of brain mechanisms and psychological and physical functions of humans in relation to technology, work, and environments

  17. Course Objectives • Understand the major cognitive theories and empirical findings in several domains of human performance • Examine the role of these theories in modern human-machine systems • Understand how human performance theories can improve design and enhance training

  18. Topics • History of human factors and the systems approach • Allocation of function • Signal detection • Vigilance • Attention, perception, and displays • Memory • Decision making • Attention and mental workload • Human performance in automated systems

  19. Resources • Books—General • Wickens and Hollands (2000), Engineering Psychology and Human Performance • Salvendy (1997), Handbook of Human Factors & Ergonomics, 2nd, Edition. • Wickens, Gordon, & Liu (1998), Introduction to Human Factors Engineering. • Matthews et al. (2000), Human Performance • Gawron (2000), Human Performance Measures Handbook • Proctor and Van Zandt (1994) Human Factors in Simple and Complex Systems

  20. Resources • Books—Specific • Vicente (1999), Cognitive Work Analysis • Vicente (2004), The Human Factor • Norman (1999), The Invisible Computer • Parasuraman and Mouloua (1996), Automation and Human Performance • Sheridan (2002), Humans and Automation • Sarter and Amelberti (2000), Cognitive Engineering in the Aviation Domain • Wickens et al. (1998), The Future of Air Traffic Control • Backs and Boucsein (2000), Engineering Psychophysiology • Parasuraman and Rizzo (2007), Neuroergonomics: The Brain at Work

  21. Resources • Journals—Main • Human Factors • Ergonomics • Journal of Experimental Psychology: Applied • CHI Proceedings • HFES Proceedings • Theoretical Issues in Ergonomics Science • Journals—Secondary • International Journal of Aviation Psychology • International Journal of Cognitive Ergonomics • International Journal of Human-Computer Studies • Applied Ergonomics • Applied Cognitive Psychology • Ergonomics in Design • IEEE Transactions on Systems, Man, & Cybernetics: Part A. Systems and Humans

  22. Resources • A Few Web Sites • Human Factors and Ergonomics Society: • ACM Special Interest Group on Computer-Human Interaction: • University of Illinois, Institute of Aviation: • Bad Human Factors Designs:

  23. A final recommendation ……….Please Google with care! It’s a rough, often unreliable, flaky, sometimes downright fraudulent web world out there!

  24. Human Factors: A Brief History

  25. Historical Overview • 1890’s - 1920’s • Time-and-motion studies • Taylor’s “scientific management” • Use time and motion analysis to determine the most efficient method for performing each component task in a job • Link employee compensation to a piece-rate system (to maximize employee work effort) • Select and train employees based on a their skills, intelligence, and personality • Mass production and the assembly line • Industrial safety

  26. The Human in Human Factors: Historical Views 1890-1920: A Cog in the Wheel F. W. Taylor’s Scientific Management Modern Times, by Charlie Chaplin

  27. Historical Overview (contd.) • 1930’s - 1940’s • Selection and training • Industrial Health Research Board (UK); psychology • Army IQ test • Job training methods • The birth of Industrial/Organizational (I/O) Psychology

  28. Historical Overview (contd.) • 1940’s-1950’s • Problems with military systems--even for skilled, well trained, motivated operators • Army: Accidents in using new artillery systems (Broadbent, 1958) • Air Force: Aircraft crashes (Fitts & Jones, 1947) • Royal Air Force (UK): Airborne radar operators missing U-boat contacts (Mackworth, 1950)

  29. Historical Overview (contd.) • 1960’s - 1970’s: NASA and the space program • 1980’s - present: The personal computer revolution • Graphical user interface; mouse (XeroxAppleMicrosoft) • Catastrophic accidents involving poor HF design • Nuclear power (Three Mile Island, Chernobyl) • Aviation (Korean Airlines shooting down, American Airlines Cali accident, etc.) • 2000 - : Diversification: from military and space systems to transportation, robotics, consumer products, aging, health care, home automation, etc.

  30. Key Historical Figures F. W. Taylor, USA 1860s - 1910s Paul Fitts, USA 1950s - 1970s Michael Posner, USA 1970s - present Donald Broadbent UK, 1950s - 1980s

  31. Key Historical Figures (contd) Neville Moray, UK, Canada, USA 1960s - 2000 Tom Sheridan, USA 1970s - present Donald Norman, USA 1980s - present Christopher Wickens, USA 1980s - present

  32. The Systems Approach • Humans are involved in all aspects of technology • Designers • Users (operators) • Maintenance personnel • The successes (and problems) of technology arise not solely from machines (machine failure) or solely from humans (human error), but from the interaction ofhumans and machines (system error)

  33. Human Machine Sensory Cognitive Motor Display Processor Control Interface Human-Machine System Environment

  34. Implications of the Systems Approach • System performance cannot be adequately described by technological factors but requires an analysis of human performance as well. • Need a common language and performance metrics to describe (1) human, (2) machine, and (3) human-machine performance. • Some common metrics: • Cycle time (time and motion) • Bandwidth - Hz (information theory) • Information transmitted - bits (information theory) • Sensitivity (d’) and criterion (ß) (signal detection theory) • These and other approaches should be used to match human and machine capabilities and limitations for efficient and safe system performance

  35. Matching Humans and Machines • I. “Fitting the Machine to the Human”: Display control, and interface design • II. “Fitting the Human to the Machine”: Selection and training Human Machine Sensory Cognitive Motor Display Processor Control Interface

  36. Examples of I: Display, Control and Interface Design • Ego-centered vs. exo-centered displays for spatial navigation • Voice (auditory) vs. data link (visual) for controller-pilot communications • Monitoring for excessive operator workload or fatigue using neuroergonomic measures

  37. Examples of II: Selection and Training • Selecting for high-performance skills (e.g., Navy pilot) • Developing selection tests for new occupations (e.g., checked baggage bomb inspectors) • Training special populations (e.g., older adults in ATM usage, or home automation)

  38. Why Consider Human Factors? • Enhance efficiency (productivity) • Ensure safety • Assure tasks are within human capability • Improve human performance • Gain market acceptance • Reduce costs (economic, legal, social)