EPHF COMPLETE

Automation definition

use of machines to do human work, control of manufacture, application and extension

4 types of automation

info acquisation, integration, selection, execution

problems with automation

reliability, calibration, sa, confusion, allocation

limits of function allocation

difficult of allocation between automation and human

principles of human-centred automation

mental models, attention, response selection, perception, interaction, organisational

mental models (principle)

define and communicate the purpose of automatio, role of person, simplification

attention (principle)

system to signal its inability to satisfy a given role

response selection (principle)

should avoid accidental activation and deactivation

interaction (principle)

keep humans integrated within workflow loop, flexible automation

perception (principle)

automation should be transparent

organisational (principle)

user should be effectively trained to operate the complex automated system

anthropometry

study of human body dimensions

anthropometry engineering

using human body measurements for design

applications of anthropometric guidelines

workspaces, consumer products

factors of human variability

sex, ethnic groups, nationalities

anthropometric percentile

percentage of population with body dimension of certain size or smaller

factors affecting human variability

age, sex, generational, body postion, occupational, clothing

anthropometric data distribution

represnted as normal distribution

normal percentile number

50th

structural anthropometric data

static measurements of body dimensions

functional anthropometric data

body adopting various working postures

anthropometric design principles

determine user population, body dimensions, percentage of population to accomodate, percentile value, use data sensibly, conduct usability test

mechanics

study of forces and motions produced by their actions

biomechanics

applying mechanis to structure and function of human body

occupational biomechanics

mechanical behaviour of the musculoskeletal system and tissues undergoing physical work

biomechanics types

statics, dynamics

musculoskeletal system

bones, connective tisues, muscles

biomechanical models

mathematical models that treat the mechanical properties of the human body

application of biomechanical models

predict stress levels of specific musculoskeletal components quantitively, identify and avoid hazards

low back problems

most costly and prevalent work related musculoskeletal disorder, accounts for 1/3 claims

cumalative trauma disorders (CTD)

disorders of the soft tissues in upper extremitites such as in fingers, hand, wrist, arms, elbow and shoulderctd

ctd severity

occurs due to repetitive tasks, accounts for more than 50% of all occupational illnesses

2 types of human beahaviour models

probabilistic, deterministic

KLM-GOMS Model

developed to predict completion time for human computer interaction tasks

model validity

does the model behave like a human in some useful way

model fitting

parameters to match human data

task network models

complex tasks, acting in parallel, probabilistic

control theoretic models

linking human to a system with changing state

cross-over model

relates the order of a system to its behaviour

control instability

control errors over time grow larger, leading to loss of control

cognitive architecture models

uses human cognition to predict human behaviour

machine-learned model

uses imitation learning methods to train a large neural network to reproduce human behaviour

Rasmussen’s Skills-Rules-Knowledge Model

knowledge-based decisions

user analyses environment without prior experience

knowledge-based decisions theories

multiattribute utility, expected value

rule-based decisions

familiarity of situations enforces rule followed response

skill-based decisions

triggered by sensory cues, carried out without concious effort

optimal decision making

making the best decision based on criteria

suboptimal decision making

choices that doesn’t result in the best outcome

normative decision making

how decisions should be made

descriptive decision making

how decisions are actually made

bias

ways in which decision making becomes suboptimal

principles of improving decision making

choice architecture, displays, automation, proceduralisation, training

choice architecture

limit number of options

displays

provides fast and unbiased cues

automation

suggest suitable actions

proceeduralisation

methods of forming decisions

training

how to use procedures and tools

situational awareness (SA)

provides perception for decision making

Endsley’s 3 level model

levels of SA

perception, comprehension, projection

perception

observation of environment and its elements

comprehension

meaning and significance of situation

projection

future states and events

SA global assessment technique (SAGAT)

interrupt taks and question probe sa

Situation Present Assessment Method (SPAM)

ask questions during task and measure response time

SA Rating Technique (SART)

subjective rating of situation

perception design priniciples (for improving sa)

make situation changes noticable

comprehension design principles (for improving sa)

organise situation info around goals

projection design principles (for improving sa)

train for sa

selective attention mechanics

brain’s ability to focus on specific tasks whilst being able to tune out external/internal distractions

4 factors of selective attention mechanism

salience, expectancy, value, effort

salience

bottom-up, stimulus driven process that refers to elements that naturally capture your attention

effort

energy required to process stimulus

expectancy/value

top-down, knowledge driven, value effects frequency of response to stimuli

implications of selective attention and perception for design

maximise bottom-up, automaticity, top-down, discriminating features

working memory (WM)

short-term memory, temporary store of info keeps available during use

limits of working memory

capacity, time confusability, similarity

WM implications on design

minimise working memory load, provide visual echoes, placeholders for sequential tasks, exploit chunking, confusability, zeros, negatives

long term memory

storing memory and retriving it later

types of long term memory

semantic, episodic, procedural

4 factors of long term memory mechanism

strength, associations, working memory interaction, forgetting

effect of repetition

forms habits, encourages memory and automatcity

LTM implications for design

encourage regular use, acitve reproduction, standardise, memory aids, design helpful habits, remembered info, correct mental models

visual echoes

visual display of info that minimises the burden on WM

placeholders

feedback provided after each task which require multiple steps

exploiting chunking

reduce info size, create meaningful sequences, letter preference over numbers, seperation

instruction congruence

reduction of WM load through alignment of order of words and actions

redundancy gain

processing info faster and more accurately, by better presentation

semantic

memory for general knowledge

episodic

memory for specific events

procedural

acquisition of recalling tasks through gradual repition and practice

ltm strength

frequency and recency of tasks

ltm associations

linking items to other items

ltm and wm interaction

retrieval of information depends on strength of association

forgetting trends

exponential decay of item strength and association strength

Baddeley’s model of WM

central executive

directs attention, coordinates info to subsystems

visuospatial sketchpad

maintains visual and spatial info

phonological loop

processes audiotory and verbal information