Understanding & Reducing Human Errors in Complex Systems: Cognitive Modeling & Engineering, Study notes of Psychology

Download Understanding & Reducing Human Errors in Complex Systems: Cognitive Modeling & Engineering and more Study notes Psychology in PDF only on Docsity! Cognitive Modeling, Cognitive Engineering, & Human Error Acknowledgments Michael D. Byrne Bonnie E. John Newell’s 20 Questions Article  Cognitive psychology has reached a point (35 years ago) where continuing to amass a catalogue of phenomena ceases to be very helpful – what we need is a grand theory of cognition. 2 BINARY OPPOSITIONS a. 14. 15. 16. 17. 18. 19. 20. a. 22. 23. 24. Nature versus nurture Peripheral versus central Continuous versus all-or-none learning, Uniprocess versus duoprocess learning (Harlow) Single memory versus dual memory (STM-LTM) (Melton) Massed versus distributed practice Serial versus parallel processing Exhaustive versus self-terminating search Spatial logic versus deep structure Analog versus digital Single code versus multiple codes Contextual versus independent interpretation Trace decay versus interference forgetting Stages versus continuous development Innate versus learned grammars (Chomsky Existence versus non-existence of latent learning Existence versus non-existence of subliminal perception Grammars versus associations for language (reality of grammar] Conscious versus unconscious Channels versus categorizing in auditory perception (Broadbent) Features versus templates Motor versus pure perception in perceptual learning Learning on non-error trials versus learning only on error trials Preattentive versus attentive Fig. 2. A partial list of binary oppositions in psychology. Diagnosis  There is no framework in psychology  alternate explanations crop up ad nauseam for each phenomenon without leading to a grand theory of human cognition  “…the ‘normal’ means of science may not suffice.”  What did he mean by that?  Hint: What was the “slippery eel” problem Newell identified? 6 Potential Remedies  “…the ‘normal’ means of science may not suffice.”  What did he mean by that?  Hint: What was the “slippery eel” problem Newell identified? 7 ACT-R Example  Let’s say you have a large environment with many devices controlling distal equipment  Like, say, a Navy ship  You want to reduce crew requirements  Meaning more distal control  New functionality must be added, new procedures learned by the operators  That is, things change  How do we design human-machine interfaces and procedures to minimize the risk of error and slowdown?  In even the routine procedures 10 ACT-R Example  To understand this, we need to know how people mentally represent routine procedures  Perform experiments to identify factors relevant to human performance  How do people represent the routine tasks that they preform?  How do people represent the space in which they perform those tasks? 11 CAT Triad  Human performance not resultant from any one thing, but from interaction of three:  Cognition  Artifact  Task 12 Card, Moran, & Newell  The computer is man’s most important tool  But at the time, principles governing its design was poorly understood  Use of the computer differs fundamentally from other tools  An applied psychological science needs:  Task Analysis  Calculation  Approximation 15 GOMS  A Framework for Cognitive Engineering  Based on Model Human Processor  Goals: the objective of the task and sub-tasks  Methods: well-learned sequences of subgoals and low-level actions that can accomplish a goal  Operators: low-level actions  Selection Rules: if more than one method applies, specifies when each should be used 16 The Model Human Processor  Three processors  Associated memories  Parameters  Principles of Operation  Quantitative predictions could be made for simple tasks, e.g.,  Speed of animation to create illusion of movement  Position of function keys for most efficient performance  And many more… 17 Human Error  Powerful technologies can have catastrophic consequences  “Be more careful” admonishments don’t work  Systems engineering approach 20 Roots  WWII: Highly trained pilots crashed mechanically-sound aircraft  Big problem  Loss of valuable personnel  Loss of valuable machines 21 Roots  Aircraft disasters really bad for commercial aviation  Airlines developed safety culture  Check lists  Crew Resource Management (CRM)  “Sterile Cockpit Rule”  Aviation’s approaches to safety have largely been successful  Now other industries are adopting their practices  E.G., CRM in the operating room 22 0 © Transporter Power CD Accept Frequency ©) Diagnostic Z C Accept Calibration C Auxiliary Power © Frequency Sample O Scanner On @ Scanner Off O Active Scan @ Lock Signal O Tracker On @ Tracker Off © Modulator @ Fix Frequency Status Elapsed Time 0 0 © Transporter Power CD Accept Frequency ©) Diagnostic Z C Accept Calibration OC Auxiliary Power © Frequency Sample O Scanner On @ Scanner Off O Active Scan @ Lock Signal O Tracker On @ Tracker Off © Modulator @ Fix Frequency Status Elapsed Time 0 0 Transporter Power CDAccept Frequency ©) Diagnostic Z C Accept Calibration C Auxiliary Power © Frequency Sample O Scanner On @ Scanner Off O Active Scan @ Lock Signal O Tracker On @ Tracker Off © Modulator @ Fix Frequency Status Elapsed Time