Expertise
How do experts differ from
beginners, and does it do us any
good to know?
1
Questions:
1. What is an expert? What is a genius?
2. Have you ever met either one? If so, what characterized
their capabilities and made them different to yours? [what
are the differences between experts, geniuses, and
“normals”?]
3. What do you think contributes to the development of
expertise? And genius?
4. Is expertise in sport tasks different to that of musicianship,
or management skills, or indeed any other life skill?
5. Can you become a genius? An expert? If so, in what field?
2
Stages of learning
• Cognitive
• Associative
• Autonomous
How much practice
does it take to
progress from one
stage to another?
• Ericsson et al. (1993) – 10 years


Open to debate (age, resources, etc.)
What do we know about reasons for people differing in
their responsiveness to practice?
3
Understanding expertise
• 1. Individual differences

Differing traits among people – data is good, perhaps
conclusions less so?
• 2. Information processing

Different use of environmental information among people
– attunement, invariant features?
• 3. Expert-novice differences

Study experts & non-experts directly, and describe
differences – do we see evidence supporting the above
two items?
4
1. Individual difference approach
• Abilities & their origin



This is pretty important, if we are to critique the idea of
abilities…
The notion of abilities is based mostly on research from
the latter half of the 20th century (e.g. Fleishman &
Quaintance, 1984)
The studies went something like this…
5
1. Individual difference approach
• What is the research supposed to examine?
EG: This graph shows fictional data for the amount of variation
in performance of 4 skills that is explained by each of 3 abilities
other
muscular
endurance
eye-hand
coordination
multi-limb
coordination
Performance Variation

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Cycling
Catching
Chess
Throwing
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1. Individual difference approach
• Take Fleishman (1957) as an example:
• Take a large number of people (200)
• Have them perform a large number of motor tasks (18)



Group the tasks into factors, according to how performance
varies on each task
The idea is to identify as few factors as possible to account for
as much variation in performance on the tasks as possible
We can get an idea of this by looking at the factor table…
7
Factor Matrix (from Fleishman, 1957) – partially reproduced for instructional purposes
Factors
Variable
I
II
III
IV
1. Instrument comprehension
.18
.22
.13
2. Reaction time
.60
-.15
-.03
3. Rate of movement
.43
.19
-.06
4. Pattern comprehension
.12
.66
.07
5. Mechanical principles
.03
.53
.52
6. General principles
.05
.19
.65
7. Speed of identification
.27
.44
.17
8. Visual pursuit
.14
9. Complex coordination trials 1-5
.05
10. Complex coordination trials 12-16
.23
11. Complex coordination trials 49-53
.42
12. Complex coordination trials 60-64
.43
13. Rotary pursuit
.28
14. Plane control
.16
15. Kinesthetic coordination
-.01
16. Unidimensional matching
.14
17. Two-handed matching
.16
18. Discrimination reaction time
.28
.24
.20
V
VI
VII
VIII
IX
The idea is to
name the factors
according to
what types of
task “load” on
them
E.G. These are
.23
.05
the only tasks to
.35
.26
load on factor IV.
.16
.21
The factor was
called
.13
.22
“Mechanical
.12
.20
Experience”
.15
.15
If
.07several tasks
.28 like ball bouncing
and juggling
and catching all
-.16
.28
loaded together, we might use a
.16
.14
label like “eye-hand
.21
.15
coordination
to name the factor
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1. Individual difference approach
• These factors all explained some variation in
performance of a number of motor tasks
• The actual list compiled will depend on the tasks used
to compile it
• The question is, is it worth anything?



Does the existence of correlations indeed suggest hard-wired
abilities?
Can you think of any issues with this?
Are experts born or made? Any relation to genius?
• Worth noting that no general ability diffs are found
between experts & non-experts
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1. Individual difference approach
• Fleischman’s approach

Use a stats procedure examine all the variation in performance across
tasks, and see if you can describe this variation in terms of fewer variables,
known as factors, thus...
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1. Individual difference approach
Two tasks load on factor 2
Three tasks load on factor 2
Factor 1
.6
Task 1
performance
variation
Factor 2
.6
.7
Task 2
performance
variation
.5
Task 3
performance
variation
.8
Task 4
performance
variation
1. Individual difference approach
• But where do these factors come from?

Abilities research:
 These are psychological traits delivering potential to develop skill
 As such they exist prior to the skills themselves
(note the research has no evidence for this, as
the data is
collected all at one time)
 Hypothetical constructs
 Not parsimonious
 Occam’s Razor is blunted
1. Individual difference approach
• What if....
Factor 1?
Factor 2?
.6
Catching
.7
.6
Hitting a
baseball
.5
Hitting a
shuttlecock
.8
Throwing
1. Individual difference approach
• What if…
Factor 1?
Factor 2?
.6
Catching
1
.7
.6
.8
.5
Hitting a
baseball
Hitting a
shuttlecock
Throwing
2
3
4
Abilities research would say: the people who develop these skills (1
through 4) have the abilities necessary to do so. Note that the data
supports this (is consistent with it)
1. Individual difference approach
• But can we come up with another explanation?
• One that doesn’t rely on abilities?
Something that is directly observable, not some
“hypothetical construct”
What could factor 1 be?
Factor 1?
Factor 2?
.6
Catching
.7
.6
Hitting a
baseball
.5
Hitting a
shuttlecock
.8
Throwing
1. Individual difference approach
• But can we come up with another explanation?
• One that doesn’t rely on abilities?
Again, something that is directly
observable, not some “hypothetical
construct”
Factor 1?
Factor 2?
.6
Catching
.7
.6
What could factor 2 be?
Hitting a
baseball
.5
Hitting a
shuttlecock
.8
Throwing
1. Individual difference approach
• Current conceptions of this issue come up with far
more nuanced explanations for differences in
emerging skill
2. Information processing approach
• 3 stages of processing
perceptual
decision
response
Stimulus
identification
Response
Selection
Response
execution
Clarity, intensity,
familiarity of
stimulus
# of alternatives,
compatibility of
stimulus and
response
Complexity & duration
of movement,
accuracy demands
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2. Information processing approach
• 3 stages of processing



The idea is that experts are quicker at all three than nonexperts
Here the differences are easy to identify
Doesn’t distinguish whether these differences are
necessary conditions for expertise to emerge, or are
merely byproducts of expertise
 Most indications suggest byproduct!
 Also, doesn’t always mean you should teach them
 See “sport vision training”
• Should be domain and task specific (attunement)
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2. Information processing approach
• 3 stages of processing

1. Perceptual differences
 In visual search (what do they attend to)
• – seeing whole arm vs. racket of racket players (Abernethy, 2007)
• Shifting gaze from trunk to racket between preparatory and
execution phases
 In awareness of the game structure (in chess, but then basketball,
rugby, hockey, etc (Allard, Abernethy et al.)
 Basically pick out the cues that matter (e.g. Williams, 2004)
 Cognitive/perceptual machinery changes with experience –
Gibson’s attunement to perceptual invariants
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2. Information processing approach
• 3 stages of processing

2. Decision differences
 General response first (stride) then specific later (swing) ( ~ in
cricket, baseball, and badminton)
 Allows more processing prior to decision, avoids being rushed
 Response selection delayed by increased # decisions, so reduce
decisions - anticipation
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2. Information processing approach
• 3 stages of processing for information

3. Response differences
 Automation
• You aren’t aware of most of the movements you are “expert” at
• What are we to make of this?
• See implicit learning, and memory location and coding
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3. Expert-novice differences approach
• What’s the focus here?

Simply, are there reliable differences between experts and
novices
 Specifically, can we get any hints about coaching or athlete
support from the literature concerning expert-novice differences?
 Talent identification and nurturing programs
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3. Expert-novice differences approach
• “Hardware” & “Software”

Hardware (more resistant to change once established)
 Relatively simple tasks
 Don’t alter much with practice
 Performance seems to be determined by unchanging basic
properties of the nervous system
• See previous comment on visual acuity, depth perception and so on
 E.g. Helsen & Starkes (1999) – found no explained variance in
soccer experts due to “hardware” (simple RT, peripheral RT) (did
find a lot in software components – next...)
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3. Expert-novice differences approach
• “Hardware” & “Software”

Software (less resistant to change)
 More complex movements and or visual stimuli to either perform,
recognize or recall (see IP section – differences are everywhere)
 Greatly dependent on practice
 It is these that experts tend to develop
• E.g. recall/recognition of game information (Chase & Simon)
• Squash example (Franks, Khan, et al. 2002)
 As a result of this, it’s in these that research finds the expertnovice differences
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3. Expert-novice differences approach
• Game structure

Experts recognize it far better
 Original research was in chess
 Generalizes pretty well to sport
 You are probably aware of it in driving (novice drivers don’t notice
things like school signs and different road markings as well)
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3. Expert-novice differences approach
• Visual attention and perception

Experts direct visual attention differently
 Abernethy argues that teaching this is not effective (knowing
where to look is no good without knowing what to do)
 But it hasn’t been examined fully
 Some research by Williams (e.g. 2012) is starting to find some
encouraging results (practice both looking and doing)…see next
slide for review article
27
3. Expert-novice differences approach
• Visual attention and perception

Experts direct visual attention differently
28
General “Vision Training” Programs
• http://www.bausch.co.uk/en_UK/consumer/age/sport
vision.aspx
• As a group they seem to suggest those “hardware”
skills can be trained, and that they will result in
improvements in specific sports



But the hardware skills did not distinguish between experts and
novices
And they did not account for variance in expert novice
performances
Basically, any improvements are unlikely to transfer to specific
sports
29
Specific Perceptual Training
• Specificity increases likelihood of success



Training at the more complex visual stimuli encountered in
the real sports scenarios
Abernethy (1997) still skeptical – must train the “doing” as
well as the perceiving
The area suffers from internal validity threats
30
The 10-year rule
• It’s well known, but...


More interesting is how it can be altered through other
variables
Recent growth area in the literature
31
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Current conceptions of the 10 year rule
• Does it hold water?
33
Current conceptions of the 10 year rule
• Massively interactive – talent + experience

But what is talent?
34
Current conceptions of the 10 year rule
• Massively interactive – talent + experience

But what is talent?
35
Current conceptions of the 10 year rule
• Massively interactive – talent + experience


But what is talent?
Current conceptions recognize just about everything you
can imagine as making a difference





Relative age effect – birth timing
Chrissie Wellington - genes
Matthew Syed - street
Asian math ability – culture
Actual devotion to practice
36
Current conceptions of the 10 year rule
• Massively interactive – talent + experience

Relative age effect
37
Current conceptions of the 10 year rule
• Massively interactive – talent + experience

Relative age effect
 Kids in the same year in school will vary in age by as much as a
year
 Older kids will be ahead of the younger, maturationally
 This confers an advantage
• First discovered and examined within school academic performance
• Later found in sport (more persistent and powerful)
38
Current conceptions of the 10 year rule
• Massively interactive – talent + experience

Relative age effect
39
Current conceptions of the 10 year rule
• Massively interactive – talent + experience

Genetics
 Chrissie Wellington - triathlete
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Current conceptions of the 10 year rule
• Massively interactive – talent + experience

Effects of context, and timing…
 Matthew Syed
• Ex #1 table tennis player in UK
• 2 Olympic appearences, three commonwealth titles
• Author of “Bounce”
• See also “Outliers” by Malcolm Gladwell
41
Current conceptions of the 10 year rule
• Massively interactive – talent + experience

Effects of devotion to practice…
 Polgar sisters
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Current conceptions of the 10 year rule
• Massively interactive – talent + experience

Effects of culture – Asian math skill…
 Length of Chinese words for numbers brief
• (4 = si, 7 = qi) So they take less time to say, so Chinese speakers can
retain more numbers in phonological loop
 Way of counting in Chinese different
•
•
•
•
We say eleven, twelve, thirteen fourteen (one in teens, one not)
They say ten-one, ten-two, ten-three (all in teens)
We say fifteen, but then twenty-one (switch in order)
They say ten-five, and two-tens-one (no switch)
 Chinese kids can count to 40 by the age of 4
 US kids can count to 15 by the age of 4
43