16.422 Human Supervisory Control Function allocation and Task Analysis Massachusetts Institute of Technology
16.422 Human Supervisory Control Function Allocation and Task Analysis
Human Systems Engineering 16.422 sIon” System/Software Reqs User survey. need's analysys, etc Feasiowty assessent Artifact ad Mwe-systemm evalation 户 rbm arce and usab reqs Innovative comeas for aKHE labod'uodgset planmin next versio? release Installation System/Software Preliminary Design Acquisition Cycle Storyboards and dew on statons Puwe如 GNc體 aterials U design stardara's Integration Test Detailed Design an7mo如 Desig tradea and wodoowanalysis Devekbo training M aterials Unit Development Oline help and documen?吉a Define perfom ance ard effect veness criteria Usablity evaluation df prckaypes Planning→ Analysis-丶 Detail design→Test& Evaluation
Human Systems Engineering 16.422 Planning →Analysis → Detail Design → Test & Evaluation
Functions tasks 16.422 Planning Mission Scenario analysis Analysis Function analysis Function Allocation Task Design Test Analysis Eⅴ aluation System Design
Functions & Tasks 16.422 Planning Mission & Scenario Analysis Function Analysis Function Allocation Task Analysis System Design Analysis Design Test & Evaluation
Fitts list 16.422 Attribute Machine Human bee Superior Comparatively slow Power Superior in level in consistency Comparatively weak Out p Consistency Ideal for consistent, repetitive action Unreliable, learning& fatigue a fa actor Information Multi-channel Primarily single channel Capacity Memory Ideal for literal reproduction, access Better for principles& strategies restricted and formal access versatile innovative Reasoning Deductive, tedious to program, fast Inductive, easier to program, slow, Computation& accurate, poor error correction accurate, good error correction Sensing Good at quantitative assessment, Wide ranges, multi-function poor at pattern recognition udgment Ju Perceiving Copes with variation poorly Copes with variation better, susceptible to noise susceptible to noise Hollnagel, 2000 inductive and deductive Induction is usually described as moving from the specific to the general, while deduction begins with the general and ends with the specific, arguments based on experience or observation are best expressed inductively, while arguments based on laws, rules, or other widely accepted principles are best expressed deductively
Fitts’ List 16.422 Attribute Machine Human Speed Superior Comparatively slow Power Output Superior in level in consistency Comparatively weak Consistency Ideal for consistent, repetitive action Unreliable, learning & fatigue a factor Information Capacity Multi-channel Primarily single channel Memory Ideal for literal reproduction, access restricted and formal Better for principles & strategies, access versatile & innovative Reasoning Computation Deductive, tedious to program, fast & accurate, poor error correction Inductive, easier to program, slow, accurate, good error correction Sensing Good at quantitative assessment, poor at pattern recognition Wide ranges, multi-function, judgment Perceiving Copes with variation poorly, susceptible to noise Copes with variation better, susceptible to noise Hollnagel, 2000 inductive and deductive. Induction is usually described as moving from the specific to the general, while deduction begins with the general and ends with the specific; arguments based on experience or observation are best expressed inductively, while arguments based on laws, rules, or other widely accepted principles are best expressed deductively
Some problems with Fitts 16.422 Tasks/functions defined in machine terms. not human-oriented Introduces a bias Laws of human behavior Environmental/ecologic context Learning, fatigue, stress, anxiety generally not incorporated into design picture Task division vs task complement Static vs dynamic allocation Adaptive allocation/automation Function allocation is not binary Bandwidth Trust Machine/computer metaphors
Some problems with Fitts… • Tasks/functions defined in machine terms, not human-oriented – Introduces a bias – “Laws of human behavior” • Environmental/ecologic context • Learning, fatigue, stress, anxiety generally not incorporated into design picture • Task division vs. task complement • Static vs. dynamic allocation – Adaptive allocation/automation – Function allocation is not binary 16.422 • Bandwidth • Trust • Machine/computer metaphors