Engineering Psychology PSY 378S

1
Engineering PsychologyPSY 378S

• University of Toronto
• Spring 2005
• L16 Memory and Training

2
Outline Lecture 1

• Working Memory
• Short-Term vs. Long-Term Memory
• evidence
• Baddeleys Working Memory Model
• Evidence
• WM Codes and Modalities

3
STM versus LTM

• We all know that we can know something, and then
  later forget it
• Often this is labeled short-term vs. long-term
  memory (STM vs. LTM)
• What is experimental evidence for STM/LTM
  distinction?
• Results from serial position experiments
• Give people a list of 20 words, one at a time at
  a certain rate, say 1 every 2 s (Dog, Shovel,
  Run, Ripple, )
• At end of list, ask them to recall as many words
  as they can (free recall)
• We do this again and again, maybe 10 times

4
Serial Position Curve

• Plot P(Recall) vs. serial position (words
  position in list)

Primacy Effect
Recency Effect
P(Recall)
1
20
17
Serial Position
5
Effect of Interference

• Procedure varied a number of different ways
• Participants perform interference task
  (arithmetic) before recalling list
• Recency effect reduced or eliminated (if time
  spent on arithmetic task increased)
• Early part of curve (including primacy effect)
  unaffected

Recency Effect
P(Recall)
Serial Position
6
Effect of Presentation Rate
Primacy Effect

• Using two different presentation rates (1 s 2 s
  per item)--affects primacy only
• Different manipulations affect different parts of
  the curve
• Suggests different mechanisms produce different
  parts of the curve
• Justifies distinction between STM and LTM

P(Recall)
2 s
1 s
Serial Position
STM
LTM
P(Recall)
Serial Position
7
The Modal Model

• Two stores short-term (STM, working memory)
• And long term (LTM)

8
Working Memory(Baddeley, 1986, 1995)

• Working memory is version of activity in STM
• Differs from STM in two ways
• Has a more functional emphasiswhat is STM for?
• Different components in STM

9
Working Memory

• Three components to working memory
• Visuospatial sketchpad--Maintenance and activity
  in visual-spatial domain (e.g., imagery such as
  mental rotation)
• Central executiveControls WM activity assigns
  resources to other WM subsystems
• Phonological storeLanguage-based short-term
  storage and rehearsal (articulatory loop used for
  verbal rehearsal)

Visuospatial sketchpad
Central Executive
Articulatory Loop
Phonological Store
10
Working Memory

• What is evidence for 3 components?
• Interference occurs when two tasks (or task
  components) draw upon same WM subsystem
• Performance degrades relative to situation where
  different WM subsystems involved

11
Working Memory
Visuospatial sketchpad
Task 1
Task 1
Good Time Sharing
INTERFERENCE!
Central Executive
Task 3
Task 2
Phonological Store
12
Working Memory

• An example is the experiment by Brooks (1968)

Task
Verbal
Spatial
Verbal
Response Method
 
Spatial
13
Brooks Experiment
Task
 
 
14
Brooks Experiment Results

• Spatial task (Big F task) better performed with
  verbal responses
• Verbal task (quick brown fox nouns and verbs)
  better performed with spatial responses
• Why? Task and response method draw upon different
  WM components in these cases

15
Implications

• Implications
• The two subsystems of working memory are
  functionally independent susceptible to
  interference from different types of activities
• Tasks should be designed such that disruption
  does not occur

16
Implications (contd)

• Tasks that impose high loads on visuospatial
  sketch pad (e.g., air traffic control) should not
  be performed concurrently with other tasks (or
  task components) that will also use this system
• Use auditory-phonetic system (the phonological
  storearticulatory loop) instead
• On the other hand,
• Tasks involving heavy demands on phonological
  store/artic loop (e.g., editing text, computing
  numbers) will be more disrupted by concurrent
  voice input/output than by visual manual
  interaction (control with a mouse)

17
Kinesthetic WM

• Also evidence for kinesthetic working memory
• Separate from visuospatial (Woodin Heil, 1996)
• Used experienced rowers as participants
• Tapping own body interfered with memory for
  rowing positions, but not positions in 4 x 4
  matrix
• Implications for sports training and performance

Visuospatial sketchpad
Kinesthetic Output Component
Central Executive
Phonological Store
18
Codes and Modalities

• Is there correspondence between stimulus modality
  and working memory codes? Yes
• Tasks that demand verbal working memory better
  served by speech displays than by print (if not
  much verbal information to communicate)
• Auditory modality more effective at processing
  language information
• Although possible to employ auditory-spatial
  displays for spatial tasks, usually less
  effective than visual displays
• Auditory modality less effective at processing
  spatial information

19
Codes and Modalities

• Summary

Obligatory Access
20
Longer Communication

• With longer messages, both auditory and visual
  channels are likely to show failures of memory
• But with print, can physically prolong the
  message--makes it more effective for long
  messages
• Might want to code redundantly (use both auditory
  and visual displays) if it does not cause too
  much interference with other tasks

21
Quiz
22
Break
23
Outline Lecture 2

• Properties of Working Memory
• Duration, Capacity
• Items and Chunks
• Expertise
• RI and PI
• Running Memory Task
• Knowledge in the World

24
Duration of Working Memory

• Brown-Peterson paradigm
• Participant presented with auditory sequence of 3
  letters (e.g., XVR)
• Try to remember them while performing interfering
  task (counting backwards by 3s)

25
Duration of Working Memory
26
Duration of Spatial WM

• Loftus et al. (1979)
• Subjects tried to remember air-traffic
  navigational info.
• Moray (1986)
• Subjects were radar controllers trying to recall
  info. that had been displayed on a radar scope.
• Both researchers found same types of forgetting
  functions
• Essentially can clear out spatial WM memory in 18
  s or so
• So, transience occurs both in visuospatial sketch
  pad AND in phonological store

27
Duration Affected by Number of Items

• Curves a and c represent 1 and 5 item (letter)
  sequences
• Faster decay observed with more items

28
WM Explains Word Length Effect

• Component of phonological store is articulatory
  loop
• With more items to be rehearsed, there is longer
  delay between successive rehearsals of each item
• In fact, the length of items--how long the items
  take to say--decreases the capacity of working
  memory--so speed of rehearsal makes a difference

29
Limiting Case

• Limiting case--curve d memory span-- 7 items
  (Millers 7?2)
• Some items cant be recalled even immediately
  after the presentation

30
But What is an Item?

• We talked about an item being a letter
• In absolute judgment task, items were things like
  different line lengths
• Couldnt a word be an item?
• Lets try Brown-Peterson task again--with words
  this time
• DOG CAT BOY
• Pack in more information--three three-letter
  words contains nine letters
• Now we have more information being held

31
Chunking

• Miller addressed this question by proposing the
  concept of chunk
• Chunking is grouping together items based on
  their meaning
• and so a chunk is that group
• e.g., f-b-i could be could be reorganized
  (recoded) as FBI--now we have a chunk
• Working memory capacity is 7 ? 2 chunks of
  information
• New capacity unit for WM
• Chunk can be letter, word,

32
Chunking (contd)

• Components of a chunk need to be semantically
  tied together, typically through assn in LTM
• Chunking can occur at higher levels as
  well--e.g., sentences
• London is the largest city in England (7 words)
• Maybe could associate the words together into a
  meaningful whole--into a superchunk (high level
  chunk chunk of chunks)
• New York is the largest city in the United States
• Toronto is the largest city in Canada, etc.

33
Chunking (contd)

• Should avoid having people perform tasks
  requiring working at 7 ? 2 limit
• To avoid capacity and decay limitations of
  working memory facilitate chunking whenever
  possible
• People with large working memory capacities
  typically have system for chunking numbers or
  letters so that they are meaningful (e.g., dates
  or ages), or by combining them hierarchically to
  form superchunks
• Ss with normal memory spans can get up to 80
  digits or so, using various chunking techniques
• Expertise plays a role herelong-term WM
  (Ericsson Kintsch, 1995)info in LTWM is
  stable, but accessed through temporarily active
  retrieval cues in WM

34
Chess

• Analogous to memory for chess position by masters
  and novices (Chase and Simon, 1973)
• If board position taken from the progression of a
  reasonable game, experts recalled better than
  novices
• If board position random, no difference between
  two groups

35
Pilots and Programmers

• Barnett (1989) found similar results with novice
  and expert pilots for communication exchange in
  air traffic control
• When exchanges flowed in normal sequence, experts
  performed better, but no difference if exchanges
  in random sequence.
• Barfield (1997) Programmers given random lines
  of code no better than novices at remembering,
  but experts better at random chunks or full
  program

36
Domain Language

• Chunking--resulting in improved memory
  capacity--is a byproduct of domain knowledge
• Everyday English words become specialized terms
  in particular domains
• Hockey terms
• Cycling the puck game up high game down low in
  the slot five hole go to the net offside
  floater dogging it
• Mathematics
• law, proof, derive (derivative), differential,
  integral
• Law
• Trial, witness, suspect, bail, sentence,
• Experts using these terms allows faster
  communicationchunked informationwithin the
  domain

37
English Experts

• Were all fluent in Englishall highly trained,
  experts
• Designers capitalize on language familiarity
• Coding--codes can be developed to facilitate
  chunking
• License plate codes--vanity plates more memorable
  e.g., FUN2GO
• Commercial phone numbers (967-1111)
• TV stations (CITY-TV)
• Radio station codes (1050 CHUM, flow 93.5, Edge
  102)

38
RI and PI

• Information can be lost from working memory
  through active interference from other
  information
• Retroactive Interferenceactivity after material
  to be recalled (MTBR) affects recall of MTBR
• Proactive Interference activity before MTBR
  affects recall of MTBR

39
RI and PI

• Not just a laboratory phenomemon
• Demonstrated in air-traffic control context
  (Loftus et al., 1979)
• PI At least 10 s delay necessary before material
  remembered in previous exchange did not disrupt
  memory for a subsequent exchange
• RI and PI can be reduced if interfering activity
  uses different code than MTBR (e.g., spatial
  activity ok after verbal list) (Haelbig et al.,
  1998)
• WM in action

40
Running Memory Task

• More realistic task (similar to ATC, dispatching)
• 7 ? 2 probably an optimistic figure
• In the running memory task, a sequence of items
  (e.g., letters, numbers) is presented to the
  operator, and the operator has to identify the
  item K items ago

41
Running Memory Task (contd)

• Operator does not know how long the string is
• Operator not expected to remember entire string
• As each item comes in, operator expected to do
  something with it (categorize it, check its
  value, etc.)
• Performance falls off rapidly when K 2
• If asked to recall the last items, memory span
  much less than 7?2

42
Yntema (1963)

• Used running memory task
• Participant kept track of large number of objects
  (aircraft), each varying on multiple attributes
  (altitude, airspeed, location)
• Two key results
• Performance better with few objects and many
  attributes than the reversean integration/chunkin
  g effect
• Performance better if each attribute has its own
  scale
• Hess et al. (1999) Use of consistent spatial
  locations in square grid allowed operator to keep
  track of attributes of multiple objects

43
Running Memory Recommendations

• From Yntema Result 1 Assign each operator to
  monitor all attributes of a few objects
• From Yntema Result 2 Dont code spatial
  variables with same units
• e.g., if code altitude in feet, then code
  distance from airport in miles, not feet
• From Hess et al. result Consistent spatial
  location will improve running memory
• Beyond air-traffic control, results may be
  applicable to other domains where information
  isnt continuously shown (e.g., taxicab
  dispatcher)

44
Putting Memory in the World

• Knowledge is not all in the head--it is partially
  in the world, and in the constraints of the world
  (Norman, Design of Everyday Things)
• Result precise behavior can result from
  imprecise knowledge for four reasons
• Information is in the world
• Precision not required
• Natural constraints are present
• Cultural constraints are present

45
1) Information is in the World
46
Information is in the World

• Information coded in memory need only be precise
  enough to sustain quality of behavior desired
• Whenever information needed to do a task is
  readily available, the need for us to learn it
  diminishes
• Examples
• penny
• hunt-and-peck typists
• I can take you there, but I cant tell you how
  to get there

47
2) Precision not Required

• Dont need all information in head
• Can distinguish quarter from nickel, although may
  not be able to tell you what is on each coin, or
  the words on the coins
• But if you make more precise memory necessary you
  will have a problem

48
When Precision is Required

• Britain one-pound coin--confusable with five
  pence piece
• US Susan B. Anthony one-dollar coin--confusable
  with quarter
• France 10-franc coin confusable with half-franc
  coin
• Descriptions formed to distinguish among the old
  coins were not precise enough to distinguish
  between the new one and one of the old ones 

49
My Red Notebook

• I buy a notebook
• What do I call it?
• Then get another notebook--a blue one
• What do I call my first notebook?
• Then get a small red notebook
• Now what do I call my first notebook?
• Mental representation need only discriminate
  among choices in front of me
• But add another choice and have to change my
  representationmake it more precise

50
3) Natural Constraints

• Often an objects physical features limit how it
  can be used
• Natural constraints are present and limit the
  range of allowable actions not a random world
• Cant use a shovel to brush teeth
• Cant use a rock to mow the lawn

51
4) Cultural Constraints

• Society has evolved many conventions that govern
  acceptable social behavior
• This lets us know what to do in unfamiliar
  circumstances
• What is appropriate behavior at a party, or in a
  restaurant
• What is the sequence of events in a restaurant?
• If we have to wait for something to happen (like
  the waitress to come and take our order) some of
  us get fidgety

52
Tradeoff between Knowledge in the World and in
the Head

• We need both knowledge in the world and in the
  head
• But in certain situations we choose to rely more
  on one than the other
• Gaining the advantages of knowledge in the world
  means losing the advantages of knowledge in the
  head.

53
Tradeoff Examples

• Can put information in the world
• Provide visual echo for message pilot receives
  from air-traffic control
• Provide the pilot with CDTI (cockpit display of
  traffic info.)
• Stick Post-It notes around my computer display
• Show continuous record of location in a
  hierarchical menu structure
• But causes visual clutter, might disrupt
  performance of pilot or user
• With CDTIs, may increase the visual workload--is
  the increase worth the benefits?
• Memory aids (information in the world) a mixed
  blessing 

54
Knowledge in World vs. in Head
From Norman (1992), Design of Everyday Things
55
Break
56
Quiz 2
57
Part 3

• Score each recalled word as Case, Rhyme, Semantic
  for Y and N answers separately
• Count up the number in each category

Case
Rhyme
Semantic
58

• Case
• BIRDS
• EAGLE
• FLESH
• FROGS
• GOOSE
• GRASS
• LEMON
• OTTER
• PANSY
• PLANT
• SHRUB
• STRAW
• TROUT
• WEEDS
• WHALE
• WHEAT

• Rhyme
• APPLE
• BIRCH
• CEDAR
• GRAIN
• HORSE
• PANDA
• PEACH
• POPPY
• ROBIN
• SEEDS
• SHARK
• SNAIL
• SNAKE
• SUGAR
• WORMS
• ZEBRA

Semantic CORAL CROWS FOXES GRAPE LILAC MAPLE MOOSE
MOUSE OLIVE QUAIL RAVEN REEDS SHEEP THORN TIGER T
ULIP
59
Outline Lecture 3

• Long-Term Memory and Training
• Levels of Processing
• Skill Acquisition
• Training Methods
• Transfer of TrainingMethods
• Negative Transfer

60
Levels of ProcessingCraik Lockhart (1972)

• More deeply you process something, better the
  chance you will remember it
• That is, that you will transfer the info to LTM
  from STM (working memory)
• Deeper approx. equal to more meaningful
• Process view of memory

P(Recall)
Case
Rhyme
Semantic
Level of Processing
61
Levels of Processing Another Take

• Normans taxonomy of memory
• Memory for arbitrary things
• Memory for meaningful relationships
• Memory thru explanation

P(Recall)
Arbitrary
Relationship
Explanation
Level of Processing
62
Memory for Arbitrary Things

• Items to be remembered are arbitrary
• No particular relationship to each other or to
  anything else
• Storage of arbitrary codes (e.g., passwords)
• Requires rote learning, which is difficult, can
  take considerable time and effort
• When problems arise, memorized sequence gives no
  hint as to what has gone wrong
• No suggestion of what you might do to fix problem
  

63
Memory for Meaningful Relationships

• Can relate what we learn to knowledge that we
  already have
• New material can be understood, interpreted,
  integrated, with previously acquired material
• e.g., Mr. Tanakas L/R turn signals on
  handlebars
• Now much easier to interpret and remember
• Although doesnt really explain anything
• Cant be used for future prediction

R
L
64
Memory Thru Explanation

• Material can be derived from some explanatory
  mechanism, e.g., mental model
• Mental model allows you to predict, test
  hypothesis
• Details can be derived when needed, as in
  unexpected situations
• Designers should provide users with appropriate
  models
• If not supplied, people will make them up (e.g.,
  thermostat, impetus model)

65
Long-Term Memory and Training

• The HF practitioner is often faced with the
  problem of developing the most efficient training
  program--greatest level of proficiency per dollar
  invested
• Different forms of training are necessary for
  mastery of declarative vs. procedural knowledge

66
Declarative vs. Procedural Knowledge

• Declarative Knowledge--Facts about a domain, we
  can verbalize these, or write them down (e.g.,
  knowledge in typical university course)
• Better off with study and rehearsal
• Levels of Processing (both kinds) important here
• Procedural Knowledge--How to do something, often
  not easily verbalized (e.g., riding bike, driving
  car, skating, using lathe)
• Tell someone everything you know about riding a
  bike, but it wont help much
• Better off with practice and performance

67
Skill Acquisition

• Practice makes perfect
• Most skills continue to improve for weeks,
  months, years
• Can obtain errorless performance in many tasks
  quite quickly
• But two other performance measures continue to
  improve speed (RT), attention or resource
  demand (as measured by performing concurrent
  task)

68
Still Improving After Millionth Cigar
69
3 Stages of Skill Acquisition

• Cognitive stage
• Learner works from written or spoken instructions
• Declarative representation
• Learner rehearses instructions, e.g., driving
  std, press clutch down first
• Associative stage
• Go from declarative rep. to procedural rep.
• Performance becomes more fluid and error free
• Verbalization goes
• Autonomous stage
• Skill becomes more automated and rapid--less
  conscious
• Person loses ability to verbally describe the
  skill
• Performance overlearned
• (Anderson, 1981)

70
Production Rules

• Anderson (1981) talks about production rules
  (if-THEN)
• e.g., if high RPM and in first gear, THEN switch
  to second gear
• Key structure unifying course of skill
  acquisition
• Development of skill in associative stage can be
  decomposed into many component production rules
  (ACT-R model see book)
• Motor program is THEN part of production rule
  its learning in the autonomous stage is the
  fine-tuning of the production rule.
• To get automaticity, stimuli or rules must be
  consistently mapped to a response

71
Guided Training

• Training that allows errors to be made trial
  after trial will become detrimental, b/c errors
  become learned
• Practice makes permanentdont want to practice
  errors
• Guided training ensures that learners
  performance never strays far from what task
  requires
• Two types training wheels, augmented feedback
• Similar to constraints and affordances,
  respectively

72
Training Wheels

• Error prevention often accomplished by guided
  training such as the training wheels idea for
  software (Catrombone Carroll, 1987)
• With training wheels, users prevented from
  straying off beaten pathmaking typical mistakes
  that result in wasted time
• Instead of allowing error to affect system,
  training wheels informs the user about the error,
  then allows user to continue on
• Good evidence to support this approach (in
  computer software context)

73
Augmented Feedback

• Error prevention can also be accomplished by
  using augmented feedback techniques
• Flight training in simulator paint an ideal
  flight path through the sky to the runway
• Learner tracks path to achieve proper landing
  approach-- ingrains correct sequence of
  responding
• Helps to produce rapid learning of skill

74
Problem for Guided Training

• Whats the problem with training wheels/augmented
  feedback?
• Can lead to poor transfer in more realistic
  environment (taking off training wheels)
• Sometimes making errors leads to learning
• Need happy mediumEliminate sources of error that
  change task or waste training time
• But keep those sources of error intrinsic to task
  

75
Adaptive Training

• Some component of the task made simpler to reduce
  initial level of difficulty
• e.g., controlling system without lag first
• Then, as training proceeds, this component
  gradually increases in difficulty until level of
  target task is reached
• e.g., introduce different types of lags

76
Evaluation of Adaptive Training

• Reviews mixed on this technique
• Simplification does make it easier to perform the
  consistent elements of the task
• However, the easy versions of the task may induce
  a response strategy incompatible with one
  necessary to perform the final task
• Time stress is effective in adaptive training,
  however
• increase time stress (speed at which events
  occur) as approach the final task

77
Part-Task Training

• Elements of complex task learned separately
• Two different forms
• Segmentation and fractionization (Wightman
  Lintern, 1985)

78
Segmentation

• Segmentation defines situation where different
  sequential phases of the skill are practiced
  before being integrated
• e.g., playing piano Train up on difficult
  passage, then play easy passage once, then play
  them together
• Research shows this is useful--not wasting time
  on easy stuff--efficient

79
Fractionization

• Practice components of task separately (e.g., LH,
  RH on piano) that you eventually perform
  concurrently
• Merits not clear cutprevents development of
  time-sharing skillsmay be necessary to link and
  co-ordinate the two activities
• If careful in selecting components of tasks that
  can be easily broken off (vs. practiced together)
  fractionization training effective

80
Varied Priority Training

• Shown to be effective (Gopher, Weil, Siegel,
  1989)
• Perform everything together, but attend to one
  component and de-emphasize others
• Integrality of task not destroyed
• Since only small amount of attention paid to
  lower priority component, it does not distract
  from the main component

81
Transfer of Training
82
Transfer of Training

• Can learning a new skill, or a skill in a new
  environment, capitalize on what has been learned
  before?
• e.g.,
• Learning MS Excel then MS Access
• Training in flight simulator before training in
  plane
• Training course before on-the-job training

83
Flight Simulators Do they help?
737-400 FNPT II MCC Source www.frasca.com
84
Transfer of Training

• How do we measure it?
• Control group took 10 hr. to reach criterion
• Transfer group took 8 hr. to reach criterion
• Savings ctrl time - transfer time
• 10 8 2 hours
•   Transfer savings control time
• 2/10 20

85
Transfer Effectiveness Ratio (TER)

• But wait a minute
• Control Group spent 10 hours training,
• Training Group 2 spent 12 hours training, 4 hours
  in simulator, 8 hours in real task
• The Transfer Effectiveness Ratio (TER) expresses
  this relative efficiency
• TER savings training period
•  2/4 .50

86
(No Transcript)
87
Transfer Effectiveness Ratio (TER)

• If TER 1, training for transfer group more
  efficient than for ctrl group (training to
  criterion)
• Your training program is better than training on
  the real systemhighly effective
• If TER ? 0, your training program is worthless
  (actually harmful)
• If 0 worthless, for two reasons
• Training program may be safer
• May be less expensive

88
Training Cost Ratio (TCR)

• Training Cost Ratio (TCR) reflects the cost
  component
• TCR (Training cost in real task environment per
  unit time) ? (Training cost in training program
  per unit time)
• Cheaper the training device, the lower your
  allowable TER can be (everything else held
  constant)
• If TER ? TCR   1, program is cost effective,
  otherwise not
• Even if program not cost effective, important to
  consider safety issues

89
Diminishing Returns

• Diminishing effectiveness of most training
  devices (as measured by TER) with increased
  training time
• i.e., TERs decrease with time in training
• Amount of training at which TER ? TCR 1 is
  point beyond which the training program is no
  longer cost effective

90
Picking the App to Train

• Large TCR indicates potential for simulation
  training
• Importance of relative cost of training program
  vs. training in environment
• Helicopter Deck Landing Simulator
• Developed at DRDC Toronto 

91
Training System Fidelity

• Should training simulators resemble the real
  world as much as possible? NO.
• Why?
• Realistic simulators are expensive--added realism
  may add little to TER, but affects TCR
• e.g., plants in office situation
• If similarity does not achieve complete identity,
  may lead to negative transfer
• e.g., unrealistic motion in flight simulators
  does not help
• If high realism leads to high task complexity,
  may divert attention from critical skill to be
  learned
• e.g., hard to learn to drive a manual
  transmission in big city traffic

92
Capture Important Task Components

• Instead of total fidelity, need to understand
  which components of target task should be
  preserved in training situation or simulator
• Mission, task analyses useful
• e.g., sequence of steps that user has to perform

93
Gibsons Invariants in Simulators

• Evidence for usefulness of including perceptual
  invariants
• e.g., global optical flow in flight simulator
• Optical flow in driving simulator--heading of
  vehicle relative to vanishing point
• Sense of immersion does not require extremely
  high fidelitytask-related invariants are what is
  necessary

94
Types of Transfer

• Positive transferTraining program and target
  task are highly similar
• Zero transferExtreme differences between program
  and task
• Negative transferSimilar in some respects,
  different in others, leading to improper
  expectations  

95
Types of Transfer
Stimulus Elements
Different
Same


Same
Response Elements
0
Different
96
Negative Transfer

• When two situations have similar stimulus
  elements but different response or strategic
  components, transfer will be negative
• This is especially true if new and old response
  are opposites (incompatible)
• Stick position for reverse gear varies across car
  manufacturers
• Task situation (parking, turning vehicle around),
  use of clutch, steering etc. these
  characteristics will remain the same
• But motor response will be opposite (left vs.
  right)

97
Negative Transfer

• Negative transfer can be serious concern for an
  operator who has to switch back and forth between
  two systems
• e.g.,
• Truck driver with two different gear arrangements
• Switching between applications Using keyboard
  shortcuts with s/w that doesnt follow Windows
  conventions
• Mode errors with cellphones, cameras, Unix vi
• Number of aircraft a pilot can fly without going
  through special training

98
End