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presented by: Dr Lisa Wise

Simulations in aviation and medicine: Cognitive and motivational factors influencing use in training. presented by: Dr Lisa Wise Cognitive scientist / educational technologist BASE Study, Defence Science and Technology Organisation

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presented by: Dr Lisa Wise

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  1. Simulations in aviation and medicine: Cognitive and motivational factors influencing use in training presented by: Dr Lisa Wise Cognitive scientist / educational technologist BASE Study, Defence Science and Technology Organisation Honorary Research FellowMUVES Project, The University of Melbourne Prepared by Lisa Wise, Feb 2007

  2. Cross-disciplinary research background • cognitive neuroscience researcher • neural mechanisms of sensory motor integration • neuroethology and multimodal spatial coding • sensory adaptions in different species (predator versus prey) • psychology teaching • perception, cognition, communication • motivation and emotion • skill acquisition • educational technologist specialising in online learning • project management / web database applications Prepared by Lisa Wise, Feb 2007

  3. MUVES Melbourne University Virtual Environments for Simulation • The MUVES research program is grounded in a cognitive science approach to the education and training utility of high fidelity virtual reality simulations and other forms of interactive technology. Underpinning this program of research are core questions about how humans process information and how different types of knowledge is represented. funded by the University of Melbourne Strategic Research Innovation Fund Prepared by Lisa Wise, Feb 2007

  4. BASE Study Balance in the mix of Aircraft and Synthetic Environments for early flight training • The BASE study reviews the psychological and educational basis on which decisions regarding use of synthetic training devices in early pilot training should be made contract research for the Defence Science and Technology Organisation Prepared by Lisa Wise, Feb 2007

  5. Outline • Simulations: What are they? • static versus dynamic models, emulations, synthetic environments, • Simulations: Why use them? • cost reduction, risk mitigation, generating abnormal conditions • Fidelity and level of abstraction • types of fidelity, types of models, purpose of simulation • Mental models and cognitive understanding • novice versus expert, procedural vs conceptual, decision-making • Training continuum • basic vs advanced training, end-point of training, dealing with complexity • Organisational factors • cost-benefit, contractor / vendor / organisational dynamics Prepared by Lisa Wise, Feb 2007

  6. REAL WORLD PROBLEM SPACE Conceptual validation Operational validation datavalidity experimentation analysis &modelling SOFTWARE MODEL CONCEPTUAL MODEL computer programming from Roger Smith Simulation 2000 series Software verification Simulations: What are they • dynamic models (theoretical / empirical) • verification, validation and accreditation of models • emulations, simulations, synthetic environments, VR Prepared by Lisa Wise, Feb 2007

  7. Issues with computer modelling The World as a Process: Simulations in the Natural and Social Sciences (Stephan Hartmann) • “That is the dilemma of using computers in science: People no longer spend that much time thinking about simple treatments but just complicate the model in order to increase its empirical adequacy.” • “We need independent evidence for the terms involved: ‘A simulation is no better than the assumptions build into it.’” • “Every term in the model has to be interpreted thoroughly.” • “There is no understanding of a process without a detailed understanding of the individual contributions to the dynamic model. Curve fitting and adding more and more ad hoc terms simply doesn’t do the job.” Prepared by Lisa Wise, Feb 2007

  8. Issues with computer modelling The World as a Process: Simulations in the Natural and Social Sciences (Stephan Hartmann) • “There is still another (psychological) problem with many realistic simulations which fit all data well. They make us forget that as always in science idealizations and approximations were involved in deriving the model.” • “A serious appraisal of computer simulation has to pay attention to this fact.” Prepared by Lisa Wise, Feb 2007

  9. Virtual reality - answers.com “A computer simulation of a real or imaginary system that enables a user to perform operations on the simulated system and shows the effects in real time” “In scientific and engineering research, virtual environments are used to visually explore whatever physical world phenomenon is under study. Training personnel for work in dangerous environments or with expensive equipment is best done through simulation. Airplane pilots, for example, train in flight simulators. Virtual reality can enable medical personnel to practice new surgical procedures on simulated individuals. As a form of entertainment, virtual reality is a highly engaging way to experience imaginary worlds and to play games. Virtual reality also provides a way to experiment with prototype designs for new products.” Prepared by Lisa Wise, Feb 2007

  10. Training aids Prepared by Lisa Wise, Feb 2007

  11. Early Flight Simulators - Link Trainers (1929) Prepared by Lisa Wise, Feb 2007

  12. QANTAS 747 Flight Simulator Prepared by Lisa Wise, Feb 2007

  13. CSIRO Haptic workbench - VR for surgery • The task: one surgeon leading the other through the concepts involved in a surgical procedure • Tools: shared virtual reality model of the anatomy, shared haptic interaction with that model, 3D annotation tools, ancillary shared video of the actual procedure, shared annotatable X-ray display of an actual patient. • Each surgeon had an immersive haptic workbench fitted with camera, small video display and microphone/speaker for audio communication. The audio was also broadcast to the audience. SimTec, T2004 Prepared by Lisa Wise, Feb 2007

  14. Laproscopic surgery • new context for existing surgical skills • actual task requires visualisation via computer screen Prepared by Lisa Wise, Feb 2007

  15. CRM / Scenarios / Missions • David Gaba, an anaesthetist, and his group at Stanford University USA recognised the similarities between pilots and Anaesthetists and adapted the aviation industry's Crew Resource Management training to the field of anaesthesia and named it Anaesthesia Crisis Resource Management (ACRM). Prepared by Lisa Wise, Feb 2007

  16. Simulations: Why use them? • cost reduction • high cost / low availability of real life situation (aircraft availability / air space, operating theatres / patients) • risk mitigation • high risk procedures, emergency situations • generating abnormal conditions • low probability situations • what-ifs • weather / missions / operating conditions Prepared by Lisa Wise, Feb 2007

  17. Fidelity and levels of abstraction • types of fidelity • types of models • purpose of simulation • some examples Prepared by Lisa Wise, Feb 2007

  18. Components of skill acquisition • Cognitive component • nature of skill-to-be-acquired is captured • Perceptual learning component • environmental information is explored such that task-relevant and task-irrelevant cues are identified • Response learning component • specific skill-related behavioural responses are acquired • Mapping - sequencing component • appropriate cues and responses are linked together • Performance component • skilled behaviour is enacted Prepared by Lisa Wise, Feb 2007

  19. Undifferentiated general responsiveness • Perceptual learning and total cognitive process: • Recognition • Production • Image, schema, concept mediation by language Gross selective response to stimulus differences (after E.J.Gibson (1969) Principles of perceptual development, p161) Differentiation of patterns / objects from background Abstraction of distinctive features Abstraction of invariant relationships Progressive differentiation of economical features Detection of higher order structure Formation of representations - Sensorimotor - Imaginal - Conceptual Naming Production Selective factors In Perceptual Learning

  20. Optical illusions “Optical illusion” sounds pejorative, as if exposing a malfunction of the visual system. Rather, I view these phenomena as bringing out particular good adaptations of our visual system to standard viewing situations. These adaptations are “hard-wired” in our brains, and thus under some artificial manipulations can cause inappropriate interpretations of the visual scene. As Purkinje put it: “Illusions of the senses tell us the truth about perception” (cited by Teuber, 1960). Michael Bach http://www.michaelbach.de/ot/ Prepared by Lisa Wise, Feb 2007

  21. Colour afterimage Prepared by Lisa Wise, Feb 2007

  22. Colour afterimage Prepared by Lisa Wise, Feb 2007

  23. Colour afterimage Prepared by Lisa Wise, Feb 2007

  24. Rotating snake - luminance effects Prepared by Lisa Wise, Feb 2007

  25. Mach bands - contrast effects at boundaries Prepared by Lisa Wise, Feb 2007

  26. Necker cube - depth ambiguity Prepared by Lisa Wise, Feb 2007

  27. Illusory motion of illusory contours • The illusory square appears to move from one position to the other. • Two image frames are used to create the illusion of motion. The motion is induced by swapping quickly between the two frames. • The squares themselves are also an illusion, as they have no real boundaries, but are mentally constructed from interpolating between aligned boundaries. Prepared by Lisa Wise, Feb 2007

  28. Hidden figures Prepared by Lisa Wise, Feb 2007

  29. Hidden figures Prepared by Lisa Wise, Feb 2007

  30. Church of Sant'Ignazio di Loyola (17th C) Prepared by Lisa Wise, Feb 2007

  31. Fidelity and immersive capacity • The immersive potential of a synthetic environment is dependent on • the validity of stimulus cues • the willingness of the protagonist to suspend disbelief to the extent of accepting the premises of the simulation and overlooking known limitations of the medium • sufficient domain knowledge available to protagonist from which to construct the illusory or missing aspects of the synthetic environment • Method of illusion generation must not impact detrimentally on learning outcomes required of the training task • calibration by expert does not mean that the correct underlying cues are present for generating responses Prepared by Lisa Wise, Feb 2007

  32. Information processing approach (eg Neisser, 1967) Perceptual processes Decision-making and response selection Response programming and execution Motor learning approach (eg Fitts, 1964, Keele, 1973) 1 Understanding skill requirement (observation, verbal / written instructions) 2 Associative stage (movement refined, errors reduced, verbalisations reduced) 3 Autonomous stage (develop automaticity or reflex) Ecological approach (eg Newell, 1986) task Coordination Control Skill perception Goal-directed behaviour organism constraints environment action (Adapted from Summers, 2004)

  33. Dynamic coordination and control • Coordination strategies align organism with environment to achieve a task • Alignment driven by “search plus selection under constraint” • constraints of task and environment • Tasks and skills • macro level comprising micro level subsystems • Limits of motor coordination • constraints on process (freezing degrees of freedom of movement) • constraints on outcome (constraining goal to tighter and tighter performance criteria) Increasing coordination decreases degrees of freedom on outcome rather than on specifics of how outcome is achieved Prepared by Lisa Wise, Feb 2007

  34. Role of instructor • The role of the instructor or coach is • “to ensure the correct ‘discovery environment’ through the manipulation of task and environmental constraints in an attempt to guide exploration of the dynamics of the perceptuo-motor workspace … if one uses the metaphor of a ‘story’ to conceptualise the skill acquisition process in sport, then the end-state form (the skill) to be acquired by each individual is not proscribed at the outset, but is painstakingly and creatively written ongoingly.” Prepared by Lisa Wise, Feb 2007

  35. Effects of constraints on training • Directed coaching or synthetic training environments with limited dimensionality will only support a very narrow search process • Unbounded workspaces allow unconstrained search which can unrewarding, inefficient and potentially unsafe • Generalised ‘textbook’ approaches provide neatly packaged temporary solutions for immediate performance effects in specific environments • Unique relationships between movement subsystems which influence long term performance transfer to novel situations will not be established in early learning Prepared by Lisa Wise, Feb 2007

  36. Mental models and cognitive understanding • novice versus expert • procedural versus conceptual • decision making Prepared by Lisa Wise, Feb 2007

  37. Simulations in the training continuum • basic versus advanced training • desired end-point of training • dealing with complexity • continuous versus discrete time scales • rate of learning • temporal flow • motivational factors of time pressure Competency-based model versus master-apprentice observational learning model? Prepared by Lisa Wise, Feb 2007

  38. actual performance high rate of learning includes acquisition of new techniques and consolidation of learned techniques TECHNIQUES low rate of learning TIME Rate of learning / Spare cognitive capacity Some parameters: * Rate-of-learning * Technical competence * Spare capacity * cognitive * psychomotor * Sequencing / flow * procedural chunking * Sensory-motor memory Prepared by Lisa Wise, Feb 2007

  39. Organisational factors • cost - benefit … to whom? • contractor > vendor > organisational dynamics • Cross-disciplinary teams often share terminology at the surface level which does not translate to shared understanding at the deep level –the same terminology means different things Prepared by Lisa Wise, Feb 2007

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