EDUC 5090
STUDY GUIDE
EXPERTISE DEVELOPMENT
EDUC 5090 / SG / 01 / VER 1
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EDUC 5090
STUDY GUIDE
EXPERTISE DEVELOPMENT
Dr Greg Yates,
Magill Campus, University of South Australia
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Terminology
In line with international practice, the University of South Australia changed some of its academic
terminology. From 1 January, 2001:

Program replaced course

Course replaced subject

Unit replaced (credit) point
This publication reflects the new terminology.
Textbook
It is assumed you have had access to the following text used in conjunction with EDUC 5080.
Bruning, R H; Schraw, G J ; Norby, M N; and Ronning, R R (2004). Cognitive psychology and
instruction. 4rd edition. Columbus, Ohio: Merrill.
© University of South Australia 2005
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CONTENTS
MODULES AND READINGS
Module
Page
Topic
1
5
Introductory module
2
9
Orientation to the empirical
project
3
15
Reviews of the research
into human expertise
Readings
Sternberg & Ben-Zeev
Ericsson & Lehmann
Ericsson & Charness
Howe, Davidson & Slobada
4
21
Automaticity
Bloom
Csikskentmikaly
Bargh & Chartrand
5
23
Expertise in pedagogy
Berliner
Sternberg & Horvath
26
Appendix 1
32
References
4
5
MODULE 1
INTRODUCTION
Reading
Assumed knowledge: Bruning et al, chapter 8.
Reading notes
As we begin this course, it is assumed that although you are familiar with the major concepts of
information processing psychology. However, a few moments spent by way of revision will be
useful. This is in accord with the principles of reinstatement and schemata activation. This
course, EDUC 5090, is intended as adjunct to, and extension of, the content of EDUC 5080,
and the degree of overlap is intentional.
Firstly, it will help to re-read the pages in the Study Guide from EDUC 5080, in which the
basic concepts of information processing are reviewed within the context of a module used
within Magill undergraduate topics. This was given as Appendix 5 in EDUC 5080 materials,
but as Appendix 1 in this present booklet. This is the same product.
Secondly, we suggest you review the essay by Greg Yates and Margaret Chandler on the role of
prior knowledge in learning, as used within Readings for EDUC 5080, and pay especial
attention to the notions of schemata as handled within that essay.
Thirdly, we suggest that you look at pages in Chapter 8 of Bruning et al., especially the pages
concerned with expertise, pp172ff.
And finally, we suggest you review the case study concerning Mr Powell’s skills, as used in the
study EDUC 5080 materials, by way of attempting to show how cognitive principles apply to
complex human thinking. It will be included here for the same purpose. These materials can all
be considered as valuable reinstatement experiences. But, in addition, we will refer again to this
case study directly within the next module, as you begin to plan your own work. The Mr Powell
material follows:
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EXPERTISE WITHIN REAL-LIFE SITUATIONS
Adapted from the following
The Weekend Australian (2000, 4 November). ‘Bill Powell: after the flames, he sifts through the
mysteries of the ashes’, pages 9-10. [Weekend Magazine]
The newspaper, The Weekend Australian, regularly publishes human interest stories within its
magazine section. In 2000, the columnist Stephen Lacey interviewed Mr Bill Powell who has
served with the New South Wales Fire Service for 33 years. As a chief investigator with the
Fire Investigation Research Unit, he investigates and reports on around 150 fires per year,
gathering evidence for the courts and the state coroner. In short, Mr Powell is an expert within
the field of fire investigation.
The following statements are drawn directly from the published interview.
I always treat a fire as a jigsaw puzzle. I need to know what, how, and why.
We like to go to a hot fire, which means it is still burning. In that way we can interview the first
firefighters on the scene. Experienced firefighters can spot something unusual. If a fire has been
increased by an accelerant, most firefighters can tell. For a start, the fire is very hard to put out.
Secondly, when they put their hoses on it, the fire runs across the top of the water.
Gathering factual information from eyewitnesses is an important part of the job.
We narrow down from the ‘area of origin’—a certain room for example—to the ‘point of
origin’, which might be over in a corner. At this point we’ll excavate debris in that location,
layer by layer, by hand so we don’t disturb the evidence.
When most people see a broken window, they assume it’s been caused by the fire. We look
closer. Maybe we’ll find some clean glass fragments. If they are unsooted, it indicates that the
glass was broken prior to the fire.
This job has made me a suspicious bastard … You’ve got to be.
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Absence of household goods sends me warning lights.
I hate having to record a fire as an undetermined cause … I like to know.
Within the interview, Mr Powell said a good deal more. For example he noted that, in his
experience, arsonists often may remain around their fires and then offer to become
eyewitnesses. They often seem to know more about the fire than would be expected. Many
arsonists actually hurt themselves, but when they go for medical treatment they tend do so as
far from the fire or their homes as they can. They may say it is a burn from a home BBQ
(barbecue).
Now, let us approach this interview from the perspective of cognitive psychology. We ask
‘What is going on within the mind?’. The above listing of statements from the interview is
especially interesting. Note how the investigator tells us that he approaches the problem with an
explicit mental focus. That is, he is suspicious, cautious and highly goal-oriented. He knows
that there has to be a cause, and that he has to proceed with considerable thought and care. That
is, he begins to employ an organised set of strategies. His knowledge of past fires and the
variables that cause them is so extensive that certain recognition processes will be activated
automatically. He knows that there are certain investigative steps to be taken while the fire is
still burning, and so he approaches the firefighters and witnesses with a planned series of
questions. The process of hypothesis testing has to take place, but the first crucial thing is to
gather the information that will eventually allow a specific hypothesis to be supported more
strongly than other possibilities.
Mr Powell does not react impulsively, but takes time to gather evidence. But note how
information gathering is not a random process. Indeed, he has to know what to look out for; that
is, how to identify and protect the evidence. He has to ensure that people do not destroy the
cues needed to arrive at a decision. For example, the disposition of broken glass is highly
important, and there could be any number of additional subtle cues left behind. He knows that
accelerants will leave some form of residue behind. For example, if anyone uses kerosene, it
leaves a smell and unburnt fluid. Mr Powell possesses a wide range of knowledge about how
fires can get started, how they develop, how quickly they spread, and what sequences to expect
as a fire takes hold. Note how such knowledge is actively embodied in schemata such as ‘area
of origin’ and ‘point of origin’. That is, even to use these terms entails a huge level of
knowledge about fire causes and sequences.
Mr Powell’s knowledge will be mentally filed within several different forms. Besides
declarative knowledge about fires, and schemas for such constructs as ‘point of origin’, he will
be able to draw upon case knowledge. Case knowledge involves memories of past events and
specific cases which bear upon the present. For example, he may find that the fire scene is
strangely devoid of furniture. This may cue him to recall a case he visited years ago, or read
about in the past, in which a criminal cleared a house of all valuable objects prior to setting a
building ablaze. Thus, recall of past cases helps by allowing him to perceive similarities
between different events.
Being able to read visual cues to locate areas such as the point of origin is a skill honed over
many years, perhaps a decade or more. To the rest of us a burnt house is a sad scene of
blackened desolation and hopeless loss. To Bill, it presents a clear mental challenge that
enables high-level detective skills to be activated and employed in the service of truth and
justice. Indeed, the newspaper interview touched on the theme of moral indignation; that is,
many fires are the work of people with criminal intent who seek to hurt others, to benefit
directly or cover up previous misdeeds.
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Besides using eyewitness reports and direct observation, the fire investigators proceed to seek
out additional information by procedures such as excavation. Additional data will be called
upon, such as the pattern of burns on any objects including human remains. That is, the
investigator has to take active steps to bring more data into the field, perhaps for a later stage of
analysis. While the scene is still fresh, Mr Powell will take scores of photographs, but even
knowing what to photograph is itself an acquired skill. The need for all this supplementary
evidence gathering will often be guided by the nature of the investigator’s preliminary
hypotheses, but he has to take care not to close off a viable cause too soon. A high level of
inference is demanded. That is, the evidence as it fell is matched to prior knowledge of
previous cases and to technical knowledge of fire sequence events. The specific presenting case
is matched to a more general case of ‘what would occur’ given all available knowledge of
situations and variables which resemble the current one.
And in addition to the tone of moral indignation (that is, the outrage he feels when people use
fire as a means of hurting others), note how Mr Powell, in common with many other experts,
sees the entire issue in terms of remarkably strong personal motivations. That is, his job is not
just to be there and fill out a mechanical report. He actually needs to know what caused the fire.
To not be able to do this would be a cause of intense discomfort. From the viewpoint of the
cognitive psychologist, this need to know is seen as a very powerful source of motivation. We
may surmise that people such as Mr Powell take great pride in their ability to solve complex
problems, and this is what makes his vocation personally rewarding.
Did you notice how we invoked a number of significant technical terms to analyse what occurs
within the mind of the investigator? Let’s look at these:

explicit mental focus

goal-orientation

strategies

knowledge (that is, declarative knowledge and case knowledge)

recall and recognition

prototypical features

automaticity

schemata

information gathering

hypothesis testing

high level of inference

mental challenge, and the need to know
These terms are all basic to the cognitive analysis of mental functioning. Within this course, we
review these and many other terms in more depth, looking at the research basis behind their
usage. Note how they help us to describe the processes the human brain actively uses in order
to solve problems, not just in solving crimes, but in all areas of our psychological functioning,
and especially when the situations in front of us demand effortful thought.
ADDENDUM: We contacted Mr Powell directly, and asked him to read these pages prior to
our citing him in this way. He declared himself amazed and fascinated by what was written, and
we believe these pages were used in training sessions, for the NSW Fire Service.
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MODULE 2
ORIENTATION TO THE EMPIRICAL PROJECT
Orientation session
Unlike other modules, the present one is not structured as a formal reading requirement.
Instead, this time is left open to allow you time to plan your own project. The important task is
to begin planning for your project. As you know, people in this course will complete a unique
personal project. However, our experience is that all students require a level of help and
guidance in order to carry out this exercise successfully and so obtain interesting data.
This project challenges many students, not because it is inherently difficult, but because they
have to proceed very carefully. You have to understand exactly what to do next, and since this
involves some testing with real people, it is crucial to plan the testing stimuli in detail. This is
not an assignment you can undertake at the last moment, and hence it is appropriate to allow
time now to help develop your ideas.
It is important to obtain feedback from your lecturer concerning how viable your plan is in
practice. Our past experience is that student plans change dramatically after receiving feedback,
and in some cases we advise students to change their plans entirely. As a student’s proposal
comes in, we consider it from many perspectives, including whether or not we think it fits
within ethical guidelines. Sometimes we suggest ways to make the project larger, or to test for
other traits, but sometimes the advice will be to make the project smaller and more realistic,
rather that too demanding on yourself and others. It’s really the nature of the data which makes
these projects worthwhile, not how big the project turns out to be in the long run.
Goal.
The central goal is going to be the analysis of what goes on within the mind of an expert as he
or she engages with material within his or her skill domain. The fact that the expert can exhibit
superior levels of performance under certain conditions is our starting point, but we need to try
to find out how and why. That is, why does the expert exhibit such skill, and how does he or
she do it? That is, there is no point simply documenting that an expert does something ‘better’.
We want to document how this can happen.
Within cognitive psychology, we make the assumption that while it is impossible to look
directly into another person’s mind, we are entitled to use behavioural cues to infer mental
processes. That is, we can take measurements of what people are doing and then infer that these
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measurements relate to their thinking and feeling states. For example, we cannot know what
someone is paying attention to, but if we find this person staring at a certain stimulus, then we
infer that that this person is attending to that stimulus. Similarly, if we find that someone (for
example, an expert) takes a long period of time looking at a problem before responding, then
we are likely to infer that they are thinking a good deal about the problem. That is, we base our
inferences upon clear data. Within this project it is crucial to obtain such clear data, and so the
level of inference becomes a known factor.
Measurement
This exercise demands that you devise clear objective measurements. For example, it would not
be satisfactory to note ‘the person began slowly’, or ‘the person seemed to reply quickly’. Both
of these statements fail to make the time dimension explicit; that is, they are not true measures
of what actually occurred. Instead, it could have been expressed: ‘the person stared at the card
for 25 seconds, and then began the work’, or “the person replied less than a second after
hearing the question’. Notice how the time dimension can lend itself well to objective
measures, but with creativity it is possible to report almost any observation within an objective
frame. It is often possible to record the number of times an event occurs. For example, the
number of times a person looks at a stimulus, or for how long, can easily be measured. Or if it
is a learning situation, the number of trials to learn could be measured.
Some measurements can take the form of capacity indexes. Within short-term memory
experiments, for example, the number of items that the mind can retain over a brief period is
readily measured. At times it is possible to measure memory of a central event, as well as
memory for peripheral details. One interesting aspect of expertise is that, at times, an expert’s
memory for peripheral things can be surprisingly low, possibly because his or her attention was
dominated by central events. Obviously we cannot find out such things unless we have been
very careful to set up a detailed test beforehand. This is why considerations of measurement are
so crucial: you can only measure what you have carefully planned and thought about before the
test.
One piece of advice is to develop your test situation, and then trial it upon a novice performer,
rather than run the risk of ‘wasting’ your expert on a faulty test. It is relatively easier to find
novices than experts, and, indeed, we always do recommend in this project that you test the
novice first. This way, the expert’s skills may often be seen to allow performance above an
expected level. Also, if you are unhappy with your first run through the test, then it may be
possible to change it and trial it again before you approach the expert.
Getting people to think aloud
As you devise your tests, try to think of doing several different things. It may be possible to
devise several small-scale tasks which people can work through over the course of an hour.
Some tasks (for example, short-term memory) will take only several minutes. On some tasks
there may be an element of speed, in that you are interested in how quickly someone can finish.
(Although we will suggest that you do not give the impression to people that they are
competing or racing against others). On other tasks, you might ask people to sort objects or
somehow arrange them into categories. On some tasks you might ask them to solve some
structured problems. On other tasks it may be possible to simply ask them what is going on in
their minds as they work on problems. These are called think-aloud protocols.
Asking people to think aloud is one way in which we try to tap into mental processes.
Actually, it is not necessarily an easy or valid method. Many people find trouble actually
reporting on what their mind is doing. The mind can be so mindful in task engagement that
actually talking about what you are doing is remarkably difficult. Your attention is a limited
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resource, and often the words we use to talk about what we are doing simply do not convey
what actually is happening. For example, we may all know how to ride a bicycle, but we have
absolutely no awareness of how we shift our weight to stay upright. Similarly, if you drive a
car, there are thousands of tiny adjustments made by the brain that are never consciously
recorded. It may surprise you to realise, for example, that a car never goes in a straight line. We
are always turning the steering wheel by tiny fractions of a centimetre, but we just do not know
this, and so this skill would never appear within a ‘think aloud’ protocol.
However, there are many contexts in which think-aloud protocols can yield valuable data.
People are often able to point to what they see as significant cues to take into consideration. For
example, an artist may look at a statue and say, ‘Look at the mould marks, so cleverly blended’,
an architect may look at house plans and say ‘The central wall takes the weight of the roof’; or
a mechanic may listen to a car engine and say, ‘Slight timing chain rattle’. In each of these
instances, note how the expert in question draws directly upon knowledge to interpret sensory
data that most of us simply do not notice. We know what these people are thinking because of
the words they use. In each of these three cases, note how the words convey definite domainrelated schemata. A novice may see or hear the same stimulus but not activate the appropriate
schemata.
In practice one can ask someone to think aloud as they perform a task. However, if the task is a
highly mindful one, it may be better not to disturb them as they are working. In many cases you
can ask for a retrospective report. That is, as soon as they have completed a task, you then ask
‘How did you do that?’. Sometimes you may be undecided as whether to ask a person to think
aloud, or to talk about it afterwards. Our normal advice is that if you are unsure, then the
retrospective report is probably the better way to go. But if this is what you are going to do,
then tell the person beforehand; that is, ‘I am going to ask you to solve this problem. Tell me
what you were thinking as you worked on it’. Some people need a bit of help to realise that you
are simply asking them to say what thoughts and judgements they make, and our experience is
that retrospective reports can yield very rich data.
This then brings in another point. When you obtain verbal data, it is critical to record it
faithfully. Often the only real way to do this is to use a cassette tape recorder. This has many
advantages. Using a recorder enables you to adopt a true listening pose. It enables you to gently
reward your participant and encourage more speech. Recordings enable you to measure
timings, such as latency time (time before starting, as a possible index of deep thinking), and
total response time. Recordings also allow you to take simple but effective measures such as
number of words uttered, or number of descriptive adjectives etc. Very often it is possible to
listen to recordings and notice certain aspects that were not obvious at the time of the testing.
Selection of the expert
What or who is an expert? The term does not have a formal definition but obviously must refer
to someone who performs to a very high level of skill within a given domain, That is, one has
to be expert in something. And it is very likely that this skill has virtually no other major
implications for other aspects of his or her life. Acquiring expertise in fixing motor car engines,
for example, does not make you a better writer or mah-jong player.
Very often expertise can be hidden or unparaded. It is possible to work with people for years
without knowing that they are champions in areas such as sports or games, or that they may
spend three hours a day playing chess. Similarly, it is possible for people to maintain an activity
for many years without realising that what they are doing is steadily building up a high level of
expertise. For example, people who work in many fields such as accounting, auditing, real
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estate, medicine, tertiary education, engineering, and computing (and many more) are
increasing their knowledge and skills in their fields virtually all their working lives.
Certainly, there is no automatic linkage between vocational competency and length of service.
But it normally requires around 10 years of development before people acquire high-level
expertise within their profession, and people who are less competent within a field tend not to
carry on. So for our purposes it is possible to view individuals who have accumulated years of
experiences in a field as experts.
Planning the project
At this stage, we would ask that you think about the case study used within the earlier module.
This is the story of the fire investigator, Mr Powell.

How does the fire investigator relate to the assignment for this course?

What if we were able to recruit him as an expert within this current project?

Could we somehow ‘capture’ that which is going on in his head enabling such advanced
planning and inferential processing to occur?
Let us assume that we cannot jump into a car and follow him to a location to observe him first
hand.

Instead, Bill has kindly agreed to sit down with us for up to an hour, and work through
whatever little test or questioning procedure we can devise.

We tell him that this is for a university project in an area of thinking and problem solving,
and we have approached him as we consider him an excellent candidate. It is probably best
not to say that we are testing a novice as well, with a view to direct comparisons. But if he
does ask about this, then we answer truthfully. We try not to make him feel that he is being
tested or evaluated personally.
There could be many ways in which we try to tap into the skills of such a person.

One excellent way could be to use photographs as eliciting stimuli. That is, we might ask
him to respond to a series of photos of real fires. This may mean using the services of
someone who uses photos of fires, such as another investigator, or an insurance agent. If we
are really lucky it may even be possible to find such photos within a textbook in a library.
There may be a recent book on fire cases, or related forensic work within this area, and
useful photos might appear within. These could be used provided our expert has not seen
this book.

Sometimes video sequences can be used. That is, there may be news-type snippets of
burning buildings. That is possible, but our experience has been that video clips are
awkward to handle.

In fact, still photographs, visual diagrams and actual objects to pick up and manipulate
make excellent stimuli, in that experts react well to them. One valuable resource we have
used from time to time are the commercial visual dictionaries. These are books which show
the words implicated in complex visual displays, such as a diagram of a football field, with
all the players’ positions marked and named. The point is that we often strive hard to track
down suitable input material that can serve to activate an expert’s thinking skills.
We can use such visual input material in several ways.

One way is to test straight memory capacity. That is, we deliberately show people too much
data, and ask them to recall it. For example, one past student in this course showed people
video sequences from an aerobics exercise class. He found that a novice aerobic instructor
could reliably recall around 10 steps in a routine, whereas the experienced instructor was
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able to hold 22 steps within her working memory before being overloaded. In this case, the
participants were asked to watch a screen and reproduce what they saw as soon as the video
sequence was switched off. The student found that the aerobics expert’s advantage in
memory extended to steps but not to other short-term memory tasks involving numbers and
words.

In another variation, a past student showed people a series of photos taken from a real golf
course, depicting each of the fairways in sequence. She found that people with low
handicaps (experts) stared at these photos then were able to recall significant details of each
hole when asked to recall an hour later. Her novices had poor recall of the golf fairway, but
strangely enough they had better memories than experts of peripheral things such as ‘What
was the colour of a building in the background on the second hole?’, and ‘Was there a
person standing on the fairway?’. The experts were paying attention to the golf course,
whereas the novices looked at other things within the photos.

In other situations, it may be possible to get people to sort photographs into categories, or
to classify them in certain ways. One remarkably useful method is simply to ask people
what they see in the photos. This is a general approach to find out about the nature of the
schemata activated. Obviously such open-ended assessments have to be handled carefully,
and it would be crucial to ensure that people did not feel under pressure to respond quickly.
Also, we have to decide what sort of feedback we give people in such situations. The
feedback must encourage people to ‘speak their mind’ but should not direct them to focus
on things they would not naturally focus upon, or suggest terms (that is, concepts or
schemata) that would not naturally occur within their thinking.
In one project from the current course, the student asked her people to watch a video of a ballet
sequence, lasting around three minutes, then speak into a tape recorder, just reporting on what
they saw. She used several novices. One novice, who knew little about ballet spoke for about a
minute, saying things such as, ‘Lady in ballet dress twirling across stage. Man follows, taking
big steps’. But in the study was another person who had 30 years of experience in the ballet
world, as performer and teacher. She spent the next 14 minutes describing, analysing and
evaluating what she saw, in the detailed and precise language of the ballet world. What was
striking was the remarkable wealth and depth of knowledge automatically activated by a brief
stimulus. She held this within her working memory then ‘dumped’ it into the tape recorder, thus
unwittingly demonstrating a remarkable ‘mindful’ capacity.
In planning the tasks for analysis, it is important to keep in mind what we actually want the
people to do. We cannot take Mr Powell to a real fire, but we can devise situations which will
draw out some of his skills. We have to devise a set of tasks which will engage his brain, but
which will not be totally rejected by a novice.
Sometimes it is unclear just who a novice should be. In the case of fire investigation, it would
be desirable to try to gain the help of someone who at least deals occasionally with fires. In
Australia, we have thousands of firefighters who volunteer for bush-fire duties with local
authorities, who would make suitable novices. If it is ever unclear who should be experts and
novices, then it is often possible to have several different types of them within the same project.
Remember that these are relative, not absolute terms.
We could, for example, arrange a series of photos in which the task is to find clues that tell us
anything about the cause of the fire. In many tests it is desirable to have some ‘easy’ items and
some ‘hard’ ones. Some photos may be ones that have blatant cues, others may have virtually
no real information in them. We could allow Mr Powell to look at each photo in turn. We
would measure such things as:
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
how long he stares before speaking

how long he speaks for

the number of words he uses

the nature of the schemata he activates

the number of cues he identifies

his use of case knowledge

whether or not he notices other details
Such a task is clearly an artificial laboratory task, but it should allow Mr Powell to demonstrate
some of the very same detective skills he uses within real life. And a novice looking at the same
photos will still be able to make sense of them, but will lack the depth of perception and
knowledge of the expert. In short, our test allows for an expert/novice contrast to emerge, with
a level of analysis being permitted from the carefully collected data.
Problems can emerge when the tasks we devise simply fail to tap into the person’s expertise.
For example, a student within this course recently did a project in which she asked a real-estate
agent to estimate house prices from photographs published within the local paper. The expert
turned out to be relatively inaccurate at doing this, simply because the set task failed to give
him the information he needed to arrive at a decision. That is, in real-life, real-estate agents
simply do not estimate values from looking at photos.
Should we even try to monitor expertise within real-life contexts? Well, it generally does not
work, as it is not possible to achieve a satisfactory level of inference and analysis. We can
observe experts doing things well, often in fast and smooth sequences. But such observations
are merely the starting point for analysis, rather than the analysis itself. In other words, just
documenting the fact that Person A is an expert because they do something well, tells us
nothing about the mental processes that underpin Person A’s skills.
For this reason, we discourage you from thinking in terms of whole-task performances, such as
‘expertise in computing’, ‘expertise in teaching’, or ‘expertise in playing computer games’. In
general, whole-task performances within real-life contexts are unsuited for this project. Often,
they will not allow a genuine level of analysis to emerge. It is not adequate to end up with a
statement that Person A is ‘better at’ Task T than Person B. The one time when real-life events
seem to work well for our purposes is when memory functions are being assessed, but this
needs care as the different people will have different events to recall.
The above discussion is intended to help you to think and plan for your own project. But this
will involve a considerable level of personal decision making and searching for a suitable
person. The normal advice we give is that the project is likely to be driven by the skills of
whatever expert you are able to locate. That is, you need to find an appropriate person, and then
work out exactly what skills he or she might be expected to possess. In many cases you will
need help in devising the tests, and this may have to come from another individual who is
highly familiar with the same skills domain as your expert. For example, if we were to devise a
series of photos for Mr Powell, we would show them to another person who has knowledge of
fire investigation, and note his or her comments.
Also, your lecturer will look at your proposal and will give you feedback as to how the tests
might be adapted to meet the needs of the project.
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MODULE 3
REVIEWS OF RESEARCH INTO HUMAN EXPERTISE
Readings
Reading 1
Sternberg, R J and Ben-Zeev, T (2001). ‘Expertise’. Chapter 13, from Complex Cognition: The
Psychology of Human Thought. New York: Oxford University Press, pp 292- 303
Reading 2
Ericsson, K A and Lehman, A C (1996). ‘Expert and exceptional performance: evidence of
maximal adaptation to task constraints.’ Annual Review of Psychology, volume 47, pages 273305.
Reading 3
Ericsson, K A and Charness, N (1994). ‘Expert performance: Its structure and acquisition.’
American Psychologist, volume 49, pages 725-747.
Reading 4
Howe, M JA, Davidson, JW, and Slobada, JA. (1998). ‘Innate talents: reality or myth’.
Behavioural and Brain Sciences, volume 21, pages 399-407.
Key Points
This module is devoted to some heavy readings concerning the research data associated with
the notion of expertise. Although it may appear a large amount to read, you will find a goodly
level of overlapping content. The two Ericsson papers are major literature reviews which cover
large sweeps of the psychological literature. Please note that a table listing characteristics of
experts is found in the first reading, page 303. This reading ought to prove a helpful overview.
Further, by way of summary, key points are listed here:

The expert–novice paradigm commonly used to study the mental processes that underlie
the emergence of expertise, has also been used to study exceptional performances in a wide
range of human skills and achievements. Areas as diverse as accounting, medical diagnosis,
tennis playing, ballet performances, and many more, have been examined using this
research design, with very profitable findings.

We can list some of the differences commonly found between experts and novices: for
example, size of perceptual patterns, memory, speed of skill execution, depth of problem
16
representation, time devoted to building problem representation and degree of selfmonitoring.

Expertise involves the coordination of mental processes on three different levels:
1
automation of basic skills
2
conceptual understandings
3
use of domain-specific strategies
Thus, both declarative and procedural knowledge elements are inevitably involved, but
with expertise there is a strong shift towards domain-specific procedural skill. When people
lack expertise, their efforts to solve problems revert back to domain-general strategies.

Ericsson and Lehmann suggest that, in historical terms, there are three views on the nature
on expertise. The first view stresses basic innate capacities. The second view discounts the
innate and stresses the role of experience and training. The third view, generally known as
‘talent’ suggests that individuals begin with natural predispositions which are then
accentuated by experience and other selection factors. Whereas the talent view has
generally been predominant for the past 80 to 100 years, and is (or was) often regarded as
consistent with modern psychology (for example, the mental testing movement), it has not
enjoyed much support from the area of cognitive psychology, which gives more support to
the second view.

Experience and expertise are only poorly related. Indeed, in many fields, years of
experience simply fails to relate to actual measures of professional success. But, in other
fields (for example, medicine, bridge, nursing (see page 276 of the article)) experience
typically does correlate with expertise.

When does experience correlate with expertise? Where a very large number of different
variables have to be taken account of, and the feedback process is uncertain, then
experience and expertise do not seem to correlate. (Note the classic field here is
stockbroking, known for its poor predictions, and where the experts do not outperform the
beginners in the field). But expertise appears to grow with increasing experience in fields
where accurate feedback is available and clearly ‘more correct’ pathways through the
complexity are possible (for example, medicine and indeed even classroom teaching).

Expertise develops perhaps after a decade of consistent application and continuous
learning. The 10-year rule seems to apply in many fields, including elite sports, chess,
ballet, computing, business management and music composition. (Comment: this 10-year
rule still appears to apply even to precociously creative individuals such as Mozart, in that
his early efforts fail to rate as worthy contributions. Precociousness is fascinating, but there
is no evidence that it is linked with true expertise at all in the early stages. There are many
myths associated with precocious development, both in the popular press and even within
the professional literature. Interested readers can be referred to books by Michael Howe
(1990, 1999) which give a cognitive psychology perspective on factors contributing to the
emergence of exceptional abilities. And if you are interested in an authoritative statement
on human creativity from a cognitive and social learning perspective, please see Weisberg
(1993). The topic of creativity is also handled from a knowledge theory perspective in
Bereiter and Scardamalia (1993). Be warned, these reviews will undermine traditional
perspectives on human abilities, effectively demystifying popular views on giftedness and
creativity.

Ericsson and his colleagues have documented the fact that elite performances in many
fields hinge upon a concerted program of training and development as described by the
17
term deliberate practice. Such practice often takes the form of around four hours a day in
semiformal tuition accompanied by extended response opportunities and corrective
feedback. Even areas which do not appear to have professional training programs or
apprenticeships in place (for example, chess) still have definable informal training
procedures which obey principles of deliberate practice.

There is a surprising literature attesting to marked anatomical and physiological change in
the body resulting from accumulating hours of deliberate practice. Together with other
findings (see page 280 of the text), such data undermine the natural talent theory of
expertise. On page 281, Ericsson and Lehmann conclude that the ‘influence of innate,
domain-specific basic capacities (talent) on expert performance is small, possibly even
negligible’. Please note that this is a remarkable conclusion, one that conflicts with a good
deal of past theorising within psychology.

The study of expertise has been advanced considerably by the use of laboratory methods in
which skilled performances can be captured by devices such as computers and video
recorders.

Experts clearly use their knowledge to advantage. They typically respond to current
problems using sophisticated search patterns, looking for patterns, using their chunking and
encoding skills, assigning certain acts to automated routines and focusing upon salient
informational cues.
Reading notes
The Sternberg and Ben-Zeev is a useful little review, providing a sensible overview. That is, it
ought to help to read this before moving into the solid research findings as in the other papers.
Now please note how Ericsson and Lehmann’s paper is in the form of the traditional literature
review. The ‘lit review’ is one of the most useful communication vehicles within a profession
where knowledge is being accumulated progressively. A good lit review surveys a massive
amount of recent research within several pages in such a way that the information is highly
meaningful to fellow professionals. To benefit from the lit review, you must already a
reasonable working knowledge of the field of study, and thus the review serves a valuable
updating function. In general, professional lit reviews are not useful to the general public and
are likely to prove unreadable to those who lack appropriate schemata.
At the outset Ericsson and Lehmann invoke the ‘nature/nurture’ debate, albeit in a guise that is
perhaps not immediately obvious. You will also discern that, as the review progresses, they are
less and less impressed with both the innate capacities and the predispositional talent views on
exceptional development. In context, you ought to recognise that talent has become, over the
years, the popular view accepted by both lay and professional sources. This view postulates that
differences in human performance stem from the interaction of inherent predispositions and
learning experiences. Therefore, certain individuals are ‘good at X’ things because (a) they
begin life with a natural flair for Skill X which could be genetically based, and (b) they live
within a world which expects and encourages them to keep doing Skill X.
Talent theory is so widely accepted today that most people would say it has to be ‘obvious’,
‘true’ or even ‘just plain commonsense’. Perhaps most of us do not even realise that talent
theory is just that; that is, a reasonably good theory. We may find evidence for talent theory in
those fields in which the winners have to fit specifiable physical dimensions (for example,
jockeys, basketball players and professional footballers). But once we get beyond a narrow
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range of certain physical sports, there is surprisingly little evidence. Indeed, the more we
advance to the related notions of knowledge theory and expertise development, the more the
theory of inherent talent begins to crumble. Despite being feeling we may have that talent
theory is ‘obviously true’, the actual level of scientific data in its favour is weak. You can read
the evidence for yourself within this paper. Note how Ericsson and Lehmann have little
sympathy for talent theory, although Sternberg and Ben-Zeev appear to be relatively more
sympathetic towards this view (see pp 301- 302).
The other two papers, (a) Ericsson and Charness (1994) and (b) Howe, Davidson, and Sloboda
(1998), also develop the same themes, and provide additional information about the current
state of knowledge in this area. The Ericsson and Charness paper also provides a valuable
historical perspective.
Please realise that the erosion of talent theory does not imply that we are all created genetically
equal, which would be a ludicrous suggestion. But it does imply that we should be very careful
about advancing attributions of human differences in skills to unproven and immeasurable
genetic factors. Even the very term ‘natural talents’ implies the existence of genetically based
differences. We have forgotten the fact that the urge to identify those children with ‘natural
talents’ at an early age stems from the assumption that early skill indicators can be used to
predict the emergence of subsequent expertise which would require the least amount of training
over time.
To put this in a way you have probably never realised, our current beliefs in ‘natural talented
individuals’ stems from economic cost/benefit analyses in which an educational system
employs a group of people to makes judgements as to which individuals can be trained most
effectively with minimal expenditure. Educational systems, the world over, operate by selecting
individuals for subsequent placement. Indeed to get where you are today you progressed
through many selection points.
Seeing poor skill development as lack of expertise
Another fascinating issue related directly to expertise research is that within cognitive
psychology we tend to have little respect for concepts such as reading disabilities, dyslexia or
even learning disabilities in general, which can, by some estimates, affect around 10% of the
population. Such labels tend to be applied to children remaining at early stages in procedural
knowledge development. All too often a learning disability is seen as a “thing” a child is
supposed to possess, a quasi-medical entity that needs treatment. Once you begin to look at
reading and mathematics skills as examples of expertise development, you then begin to
appreciate the level of complexity and automaticity required in acquisition of so-called basic
skills, and you will achieve new insights into the requirements of experiences that can foster
development.
Looking at learning problems as instances of slow expertise development implicates variables
and strategies likely to be overlooked by people using more traditional schemas and paradigms.
In many cases we expect people to learn reasonably quickly. This expectation creates huge
problems without our realising it, in any conscious manner. Within any area in which we are
‘experts’ ourselves we have little sympathy for the novice. A person who is a superb musician
19
herself may have little patience for a struggler. Exposure to such a ‘teacher’ may serve to
convince the student novice that she lacks a basic commodity needed for success.
If you want to turn a person into a learning disabled individual, then one way to do this is to
expose her to a world in which her slowness is taken as evidence of a condition that prevents
success. The lack of success can thus be blamed on the condition. This is not a situation likely
to stimulate motivated effort. Indeed, it’s a situation linked with demoralization and
helplessness. To attribute a child’s lack of computational skill on her lack of ‘talent’ or
‘inability’ in mathematics, is a decidedly unhelpful action if we are expecting this student to
then somehow ‘try harder’. Note how talents can be seen as fixed attributes, or as entities
underlying behaviour (recall Dweck’s research, p 139, in Bruning et al., 2004). This is unlikely
to motivate effort on the part of those who are told they lack such valued and necessary
attributes. Note how such attributional messages can actually be communicated through subtle
means, such as teacher expectations (Eg “You have done quite well for someone who is not
naturally gifted at maths”). Indeed, one of the paradoxes uncovered within Dweck’s research
was the negative impact of praising a child’s abilities directly. To make a person believe their
worth depends on displaying abilities turns out to be a strangely cruel way to treat people,
encouraging them into ego-defensive games. See Dweck’s (2000) book for more on this point,
which is highly counterintuitive.
In responding to an earlier version of these notes, a student objected on the basis that these
comments appeared to imply that somehow ‘learning difficulties’ just do not exist. But the
point really concerns the use of words as explanations, not whether or not certain students
present with unsatisfactory progress in school-related areas. Most educational systems within
the Western world will use diagnostic categories in order to allocate resources with a level of
equity and responsible decision making. Hence, the problem is not to confuse valid descriptive
categories (such as ‘learning difficulty’) with pronouncements about what the individual mind
is or is not capable of doing. Undertaking this university course may thus render you sceptical
about any practices in which labels are used as though they really do anything more than
describe a presenting problem.
Professor Michael Howe’s contribution
The paper from Howe, Davidson and Sloboda was written shortly before Dr Howe died, after a
distinguished career as Professor of Psychology at University of Exeter in England. He was a
brilliant scholar, with his writings having an element of straight ‘common sense’. His books on
the psychology of high abilities and genius stand out as the most remarkable and insightful
statements within the field. Basically, he stood for a knowledge based tradition, ie the idea that
accumulated knowledge and experience will almost always outweigh factors such as native
intellect or IQ in ‘real life’ contexts. His view was that the real mystery behind geniuses was
not so much in the fact that they began with superior intellects (a point of dispute), but that they
were motivated to develop themselves through natural expertise factors over very periods of
time. Perhaps this is overstating a complex position, since biological and genetic factors are
never discounted, but his work certainly made a huge impression upon thinking within
psychology notably across Britain and the United States. His findings in several fields (e.g.
music training, savant research, memory training) gave considerable validity to the notion of
deliberate practice.
20
Internet resource
http://books.nap.edu/html/howpeople1/
Note the existence of the monograph, “How people learn” which was constructed by a group of
distinguished cognitive psychologists, as a commissioned project for the National Research
Council in the United States. The book is published on-line. Notably, there is an excellent
chapter on expertise development (chapter 2), which will overlap directly with material we
cover in this module. The book provides tight little summaries which can be read quickly, and
dips into much contemporary cognitive research in a deliberately non-technical manner. Some
students have reported to us minor problems using the above URL in that the final figure is the
letter l, and not the number 1, which will look the same in many fonts.
21
MODULE 4
AUTOMATICITY
Readings
Reading 5
Bloom, B S (1986). ‘The hands and feet of genius: Automaticity’. Educational Leadership,
volume 43, number 5, pages 70-77.
Reading 6
Csikskentmikalyi, M (1999, October). ‘If we are so rich, why aren’t we happy?’ American
Psychologist, volume 54, number 10, pages 821-827.
Reading 7
Bargh, J A and Chartrand, T L (1999, July). ‘The unbearable automaticity of being’. American
Psychologist, volume 54, number 7, pages 462-479.
Reading notes
The intention of this week’s reading selection is to give you insight into how concepts of
cognitive psychology, especially the notion of automaticity, can have wider applications.
The early reading by Professor Benjamin Bloom represents a clear statement of the standard
position on automaticity as it has been advanced within psychology now for over a hundred
years. Bloom’s data contributes very well to this tradition, and he sees automaticity as the
‘hands and feet of genius’. This paper complements the readings in the previous module in a
straightforward and meaningful way. This is the same Professor Bloom who was famous for the
educational taxonomy developed after WW2. This paper was written toward the end of his life,
and it was based on a key project in which his team sought to identify the key elements that
underscored high achievement in talented young people.
Professor Csikzentmihalyi’s research is also close to expertise research but with a most
interesting twist. He postulates the existence of an altered state of consciousness which he calls
flow. This state of flow is experienced as enjoyment, ecstasy, total immersion and happiness.
But it requires skill, indeed there has to be a balancing of skill against response demands. A
22
common finding is the literature of psychology is that people who are experts within their fields
will often report flow experiences, provided certain conditions are met. This fact has been
known for virtually century, but it is only of late that the term ‘flow’ has been used.
John Bargh and Tanya Chartrand’s paper is not an easy read, but it will leave you thinking.
Within recent years the theory of automaticity has been extended in new directions. Overall, the
data present a disturbing image of human behaviour: That most of our everyday reacting and
decision making is not under conscious control. We certainly harbour perceptions of personal
control, known as ‘acts of will’, but many studies imply that our ability to actually determine
the variables that cause us to react simply are not consciously represented.
There are many spectacular experiments reviewed in this paper. The suggestion is that
automated functioning (that is, procedural knowledge) is more important in actually running
our lives that we had hitherto believed. The basic design in Bargh and Chartrand’s work has
been to establish that human behaviour within many situations is subject to gentle priming
effects. These primes might be presented to people as though they are participating in simple
experiments in areas such as word knowledge. Some, for example, may be primed by having
them locate synonyms for ‘aggression’, but others by finding synonyms for ‘kindness’.
Moments after, they might be left waiting on someone to help them, but that person is on the
phone, and the dilemma is whether or not to interrupt the call. The likelihood of interrupting the
person is possibly doubled by the experience of being primed by the ‘aggression’ words. Such
findings are strange but remarkably robust, and replicated.
You will need to read this paper to appreciate the subtleties behind many of the experiments.
Note the use of neural network theory to explain the findings. Despite the strength of the effects
observed, subjects never report that their behaviour was primed. In essence, behaviour can be
triggered by subtle cues and biasing experiences completely outside of consciousness. This
absence of awareness is actually quite typical in many experiments within the literature of
psychology. That is, people might be induced to give money to a charity after seeing someone
else do this (i.e. referred to as a social modelling influence). But when you ask such people to
say why they gave to charity, not one person ever says “I gave because I saw the model do it”.
In essence, factors such as social models and verbal priming experiences operate very
effectively outside of consciousness, and thus implicate the notion of automaticity.
23
MODULE 5
EXPERTISE IN PEDAGOGY
Readings
Reading 8
Berliner, David C (1986). 'In pursuit of the expert pedagogue' Educational Researcher, volume
15, number 7, pages 5-13.
Reading 9
Sternberg, R J and Horvath, J A (1995). 'A prototype view of expert teaching'. Educational
Researcher, volume 24(6), 9-17.
Reading notes
Some resources relevant to this topic are available at
http://www.k12albemarle.org/CTIP/Paula/advcurric/Texpertise.html
Also, Professor David Berliner, Arizona State University has a wonderfully rich paper
available on http://courses.ed.asu.edu/berliner/readings/expertise.htm
His actual home website, well worth a visit, is http://coe.asu.edu/elps/faculty/berliner.php
As suggested earlier (pp 18-19) it is very often the case that experts within a domain do not
make very good teachers for novices within that same domain. Experts may activate such high
levels of automaticity that they are unable to perceive the problems faced by novices. Experts
can become intolerant of beginners’ ineptness and easily express such frustration in body
language and vocal stress.
The important thing to note is that teaching can itself be seen as a viable domain within which
expertise may be demonstrated. The characteristics of effective teaching have been subject to
research programs stemming back into the 1970, and a good deal of work was carried out using
an experimental design called ‘process-product’, ie searching linkages between teaching
processes and student learning using genuine classroom indices. Process-product linkages were
found to occur, and this tradition has resulted in a rich body of knowledge concerning what it is
that teachers do that assists in student classroom learning. Teacher expertise became one of the
24
spin off topics to emerge out of classic process-product research tradition, and of course
expertise is one of the key topics within cognitive psychology.
Berliner. In 1985 David Berliner was the President of the American Educational Research
Association, and the present paper is the written form of his presidential address, as published
in their house journal in 1986. The actual video of this address is also held by the Magill
Campus Library (but in NTSC). In search of the expert pedagogue is a provocative title, and
you will find that there is much good humour in this paper, especially when the problem of
identifying expert teachers is compared to the procedures used to train and identify experts in
other professions (including cattle judging, farmers, and athletics judges).
Berliner then goes on to outline some of the studies he and his colleagues in Arizona have been
involved with, and ways in which these findings are consistent with the existing data base
within cognitive psychology. Although it stems from 1986, this paper has become the classic
paper in the field, acknowledged by later researchers who have contributed to this important
area.
Sternberg and Horvath. This paper serves as both a short literature review and a synthesis in
which the concept of teacher expertise is aligned with the notion of cognitive prototypes.
Prototype theory is a theory of how the mind acquires new concepts, i.e. by distilling essential
or central features even when there may not be any clear or single nominal representation of
these features. The mind is inclined to build up, or construct, mental prototypes of salient
experiences, in the form of schemata, and then match input experiences against these
prototypes as a check upon the goodness of fit. For example, violin and flute are very different
physically but could both be equally central your mental prototype of musical instruments. The
theory is covered quite well in the opening pages of the current article, but also in the Bruning
et al. textbook.
We are a little ambivalent as to whether or not the use of prototype theory really adds anything
to the analysis of teacher expertise. However, we do see the present paper as valuable in terms
of providing a reasonable literature review.
Some questions for this module are
(a) Berliner cites several reasons to study expertise in teaching. What are they?
(b) Can external agencies, such as parent groups and Good Housekeeping Magazine, be relied
upon to identify expert teachers? At this juncture also note the comments made by Sternberg
and Horvath (pp 11-12) about how people need tacit knowledge to get themselves labelled as
experts. Also remind yourself of the distinction between effective and good teaching in the
Introduction.
(c) Can you summarise the major findings from Berliner's own research (see pp 9-12)
(d) Berliner also says some very interesting things about the nature of complexity in classroom
life, and the mental accomplishments necessary to master such complexity (see pp 12-13). Why
is such achievement not normally recognised? If teaching demands the very highest levels of
cognitive complexity, why is the profession not so honoured by outsiders? What has gone
wrong?
(e) Sternberg and Horvath present an updated literature review, using their own terminology (ie
efficiency, insight, etc). But what actual new findings, beyond ones from Berliner's earlier
paper, did they describe?
25
(f) Sternberg and Horvath suggest that expertise can be seen as a prototype. How useful is this
analysis?
Note: In March 1995, Professor Berliner visited Australia. Amongst his engagements, he gave
an invited seminar on teacher expertise on the Magill Campus. An audio tape was made of this
seminar, and is held by the Magill staff in Educational Psychology. Copies of this tape can be
borrowed and are available on request from Greg Yates.
26
APPENDIX 1: Material as used in undergraduate topics on the Magill Campus
INTRODUCTION TO THE PSYCHOLOGY OF LEARNING
AND BASIC INFORMATION PROCESSING
(This version intended for students in EDUC 1019. October 2004. Dr Greg Yates, UNISA Magill)
How do we learn? What actual process has to occur within the mind? How can we make our
learning more meaningful? What can we do to prevent memory loss? Can the mind ever get
“full up”? Can the mind be trained to learn better or faster? Will my knowledge of psychology
help me to pass university exams? Questions such as these can be addressed in the light of
information covered within this topic.
These pages will provide you with an introductory commentary focussing upon a
specific way of looking at human learning. The perspective adopted by contemporary
psychologists is referred to in general as information processing theory. Your textbook will
take you more deeply into this theory and its educational implications.
We begin this commentary by reviewing several elementary principles of learning.
Some of these will be very familiar to you, but you may never before have appreciated such
principles as formal statements about human learning. In this module, we will quickly review
three topics: Viz, (a) principles of acquisition, (b) principles of memorisation, and (c) principles
of mental overload. Following on from this review we will quickly cover the multi-store theory
of human information processing.
Principles of Acquisition
1. Role of time, effort, and motivation
Human learning is a slow process, typically indexed over months and years rather than
hours or days. The necessary concomitants of the process are (a) time, (b) goal-orientation, (c)
frequent review, and (d) accumulated successful practice. Notions such as “instant expertise”,
superfast learning, speed-reading, and other magic-like programmes are seen as faddish
quackery, and stand in violation of known principles of human learning.
Most humans will appear to learn specific small-scale behaviours, bits of knowledge, or
low-level objectives within only a few minutes. But this impression of quick learning is highly
deceptive for a variety of reasons. Unless the material is very strongly meaningful, it is subject
to very rapid forgetting. Even if it is retained, it may be difficult to retrieve within an appropriate
context. To acquire any level of domain competency will take a bare minimum of 100 hours
practice, and genuine expertise takes perhaps 5 to 10 years of consistent skill development.
2. Concentration span
Adult humans have a natural attention or concentration span, of around 15 to 20
minutes, before significant levels of mind wandering will occur. Well-motivated learners may
then refocus their mental activities back onto a task, but will still need short breaks in order to
avoid overload effects. If you need to teach anyone some new information, then, it is most
helpful to do so within 15 minutes, or else you will “have lost them”. Note how university
lectures may exceed the span by a factor of three, and of course the lecture room violates the
notion that learners should make active responses. Also note how attending to music may
actually harm attention focussing and resultant learning.
3. Spacing effect/ Distributed practice
To try to learn material within a single block of time often turns out to be far less
effective than if the same duration of time was broken into shorter periods spaced over several
days or weeks. This is especially true when learning new skills. For example, if you were to
learn to drive a car, you would benefit far more from 6 sessions of 20 minutes each spaced
over a week, than from a single block session of 2 hours. In most human learning situations,
blocks of 20-30 minutes are most effective in cost-benefit terms. The concept of distributed
practice is also used to refer to the spacing effect.
27
4. Prior knowledge effect
In any one context, the major determinant of knowledge acquisition will be what the
mind already knows. It is far easier to build on existing knowledge (which we call schemata or
schemas) than to learn new material. Input information that cannot be related to one’s existing
knowledge is quickly shed. In sheer power, prior knowledge effects are far stronger than other
variables influencing learning. Prior knowledge effects, for example readily outweigh effects
due to IQ or ‘learning styles’ which have only fairly weak effects on learning. When your prior
knowledge is faulty, however, it creates a huge obstacle, an effect called interference, which
we discuss in more depth within the next section on memory effects
5. Principles of information structuring
The mind does not relate well to unstructured data. We find it extremely taxing to learn
random lists or otherwise cope with unrelated materials. We need to find organisation,
structure, and meaning in what we learn. Very often, meaningfulness stems directly from prior
knowledge, but we also benefit enormously from being shown how to group information, how to
find patterns, how to use orderings, or how to schematise and summarise. In teaching
situations, good teachers often provide overviews of what we are to learn, and these are
referred to as advance organisers.
6. The mind responds well to multi-media (ie multi-modality) input
From time to time you will come across people describing ‘visual learners’, or ‘tactile learners’,
or whatever. The basic experimental data, however, indicates that people are far more similar
than they are different in such ‘learning styles’. In fact, we all are visual learners, not just some
of us. Studies reveal that we all learn well when the inputs we receive are multi-modal or via
several different media. That is, the brain is set up, rather beautifully, as a device which
integrates information from different sources, from different inputs, or from different modalities.
Strong learning occurs when words and images are combined. Claims such that ‘some
students learn from words, but others from images’ are incorrect as students learn most
effectively through the contiguity (ie mental associations) of words and images.
Principles of memory retention
1. Recall is hard: recognition is easy
To recognise means to indicate that the material is known, often by signalling in some
coherent way, such as ticking a box on a multiple-choice test. But recall means to produce,
regurgitate, reconstruct, rebuild, etc. Measures of recognition are sensitive in that they may pick
up partial knowledge very easily. Recall measures are far more severe and are typically
insensitive to partial knowledge. Hence, in terms of items “remembered”, a recall test yields
much lower scores. Indeed, part of the art of constructing high quality multiple-choice tests is to
devise items that cannot be answered by simple, direct recognition but which involve deeper
levels of processing.
2. Primacy and recency effects
These two effects are not widely known to lay people. However, they are well
established in the research literature. As a learner, the individual copes inevitably with
sequences of information. The human brain is a type of linear processor, and recall is often
subject to what are called serial position effects. Obviously some information entering the
mind is more important than other information, and this facet will dominate the individual’s
attention. But the sequencing of data also has been shown to influence learning in that the
information that enters the mind first within a sequence is often recalled more readily. This is
called primacy.
The recency effect occurs when the information that enters the mind last has an
advantage in mental processing. For example, you may listen to a lecture and recall the
beginning and end bits, but the middle somehow gets forgotten. Recency effects can be strong
immediately after a learning experience. However, the primacy effect often tends to be stronger
than recency when recall is attempted a period of time after the original experience.
28
3. Meaningfulness determines retention level
It is possible to learn meaningless material. Lists of nonsense words, or columns of
random numbers can be committed to memory. But the retention level for this type of rote
learning is very low, possibly around 20% after a day. Rote acquisition results in rapid
forgetting, and this appears to occur within minutes or hours of the original learning. If such
material is to stay within the head, it must be constantly rehearsed or otherwise some sort of
pattern must be perceived. Various mnemonic devices might be activated to try to aid retention
levels, and these are often useful due to the relative meaninglessness of the input.
4. There are different rates of forgetting over time
The rate of forgetting can depend on the type of original learning. For example, once
mastered, motor actions are typically retained virtually for the life of the individual. A fit senior
citizen might be able to ride a bicycle even after not riding on one for 50 years. Also, the
retention level for words is very high in humans, at least within one’s native language. But
moderate levels of decay over time will occur for most intellectual-type skills, especially if the
skill hinges upon detailed knowledge of specific operations, facts, or arbitrary numbers. The
mind will shed isolated facts very rapidly, and we all have great difficulty holding onto arbitrary
items such as telephone numbers, bank account numbers, etc, even when such things might
be seen as important things to try to recall.
5. Memory is a constructive process.
It is tempting to think of the memory as “play-back video recorder”, but this metaphor is
misleading. Memory is highly constructive in that it hinges upon the brain making sense of
partial cues and imprecise information. Memory is dependent upon the focus of attention at the
time of learning. But what two people focus upon, given the same experience, could be very,
very different. Human beings are notoriously unreliable as eyewitnesses to objective events.
Memory for aspects such as time estimates, vocal emphasis, specific words spoken, causal
sequences, and even actor-action associations can vary dramatically between witnesses.
Interpretations vary in accord with prior expectations and other sense-making strategies.
The act of recall must be seen as a person’s attempt to find meaningful patterns in
what otherwise is unprocessed chaos. Hence, our memories are subject to many different types
of error such as oversimplifications, abbreviations, schematizing, distortions, and intrusions. An
intrusion is where a person recalls some aspect that was not part of the original learning
experience, but which is possible, feasible, likely, or just something that seems to “make
sense”. It should be noted that people generally are not aware when their memory plays such
tricks upon them. We all fall into the trap of believing that our memories correlate perfectly with
reality. Indeed, confidence in memory accuracy has often been shown to be unrelated to actual
objective indices. This has been documented both in laboratory type experiments and
naturalistic studies. Put bluntly, an eyewitness’s confidence level is a flawed predictor of this
person’s actual accuracy level.
At times, memory reports can be biased by factors such as stereotypes, prejudices
and faulty expectations. As intelligent people, and teachers responsible for managing student
welfare, we must be alert to such sources of distortion in what people report. It is important to
realise that human interactions are actually very difficult things to recall accurately.
6. The principle of savings (ie relearning)
Suppose you learnt a foreign language 20 years ago, but appear to have forgotten it
completely. Well, this is unlikely to be the full story. Studies have shown that we can learn
material the second time very rapidly, even when the original learning appears lost and
inaccessible. We know about this principle because of the huge time advantage people have
when they relearn material. In such situations, people are largely unaware of the power of this
effect, and may not realise that substantial savings are being made. All they know is that they
seem to be “picking it up fast”. This effect is quite dramatic when a person visits a country after
not having spoken a specific language there for 20 years and then “picks it up again” within 3 or
4 days of arriving in the country. Often there can be ‘hidden reasons’ why some people learn
quickly, notably when prior knowledge can serve as an unconscious source of memory
savings.
7. Memories are subject to interference.
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Interference refers to natural memory loss due to experiences either before or after the
original experience. For example, if you learn a list of 20 Spanish vocabulary words and then a
list of 20 French words, there is a very strong chance that your recall of the Spanish words is
inhibited by learning the French list . This is called retroactive interference. But similarly, your
recall of the French list is reduced by the fact that you had earlier learnt the Spanish list, and
this form of interference is called proactive interference. These are genuine memory effects,
not merely the result of fatigue or overload.
In school situations these effects can operate in subtle ways. Although we hold that
one’s prior knowledge generally will help learning, there are times when prior knowledge can
become a clear source of proactive interference. For example, within the Science curriculum
words such as “force”, “matter”, “vector”, “ratio”, “space”, and “living” all have technical
definitions that can be very hard for students to assimilate precisely because such words also
have common sense meanings. (Note, this relates to the notion of misconceptions, which are
often discussed in connection with Science teaching)
Principles of handling overload
At times people find themselves in situations where they are overloaded. The efficiency and
organisation of their actions is threatened simply because there is too much going on within the
mind. Overload is implicated in a multitude of human pathologies and miseries, and is one
reason why people at times appear to act against their goals and self-interest. For example,
under provocation and stress, a teacher may strike a student despite being well aware that
such physical gestures are illegal. The explanation for many forms of violence is that the actors
were overloaded. Some basic principles follow.
1. Learning is an unpleasant experience.
This principle may surprise many of you, as the overall results of learning can often
bring high levels of reward and personal satisfaction. But, seriously look at this more closely.
You may find that positive emotions tend to be correlated with (a) planning and goal setting in
the first place, and then with (b) achieving your goals. For the most part the actual learning is
NOT enjoyable, even though it is helpful to tell yourself otherwise. It is enjoyable to have skill,
to display prowess, and to envisage what one can do. That is, it is pleasurable to perform, or
dream about performance benefits. But the actual process of learning (ie the moment when
learning takes place) is far more likely to be stressful and loaded with emotions of uncertainty
which quickly shift into negative feelings.
One factor implicated in this principle is that humans possess a natural tendency
towards overconfidence in being able to learn. That is, we tend to be optimists and believe we
can perform better than we really can in most learning situations. Similarly, we tend to
underestimate the amount of time and practice it takes to master a new skill. Please realise
these natural tendencies are neither “good” nor “bad”, but they should be recognised by all
instructors, teachers, and parents. The overconfidence effect is especially strong before people
receive objective feedback about performances. Feedback may force a person to radically alter
such assessments.
2. Learning places great stress on mental resources
The learner is vulnerable. She has to maintain adaptive composure in the face of often
unpredictable consequences. It is necessary to mobilise high levels of effort and vigilance, and
so be prepared to respond to input experiences in a variety of ways. The learner may not know
how the world is going to react towards an action she has initiated. She may not know of the
appropriate stimuli to pay attention toward. She may not know how to match the intensity of her
response to the immediate input, or how to pull back if she has optimistically overstated her
current capabilities. In short, mental resources are stretched, possibly to a point of non-optimal
processing we refer to as overload.
3. Every person has to develop coping strategies.
We all develop ways of coping with stressful learning contexts. We can do things such
as pay attention, work slowly, increase the level of practice, reread the materials, or find a good
teacher. Our coping strategies must apply to two fundamental aspects: (a) increasing our
opportunities to learn, and (b) managing our emotional responses. It is necessary for every
learner to develop a wide range of possible coping methods. Failure to learn coping skills
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renders the learner passive in the face of inevitable overload. Incidentally, it has been found
that there is some level of consistency in the way individuals will tend to respond to quite
different sources of stress.
4. Overload factors can be identified
There is no one single cause of overload, and some people will cope with such stress
better than others. However, at the level of the individual learner, it is possible to specify that
overload can be linked to ANY ONE of the following:
(a) Low levels of prior knowledge.
(b) Deficient use of mental strategies.
(c) Unrealistic expectations (eg overconfidence, or goals set too high, or are immutable).
(d) Poor instruction, inadequate teaching, or failure to engage with learning material.
(e) Unfavourable learning conditions (eg study facilities, presence of distractions, etc).
(f) Assessment apprehension (eg unfair tests, competition, emotional/motivational problems).
Multi-store theory
In this section we introduce the major theory of memory that has held sway over the past 30
years. This theory accounts for many (but not all) of the principles listed above, and is widely
accepted within cognitive psychology today. The theory says that the human memory system
consists of at least three levels of memory, which can loosely be called stores. They are the
iconic store, the short term memory, and long term memory. There has been debate within
academic psychology as to whether these stores should be seen are separate entities, or part
of a single process, but for purposes of this essay we will treat them separately.
1. Iconic Memory
This form of memory is also known as sensory memory, and as ultra-short term
memory. Iconic memory relates to input experiences and perceptions within a sensory
modality. Within the visual system, for example, experiments reveal that a large amount of data
can be stored for around a second. In a laboratory study, for example, you might be asked to
look at a screen where an image appears for one twentieth of a second. Your visual system
takes it in and then has perhaps up to a second to “read” from the image until it fades from your
mind. The auditory system appears to have longer duration sensory images possibly 2 or 3
seconds duration.
2. Short term memory (STM) or working memory (WM)
For our purposes we will regard these two terms as virtually synonymous. However,
many psychologists now avoid the term “short term memory” and prefer “working memory”.
This is to signify that this form of memory represents the amount of space available for current
mental processing. Metaphorically, it is the working area or the workbench of the mind. But it is
a system that has to stay active, lest items drop off the workbench. Indeed, it is a limited
capacity workbench.
The WM system has two basic problems. Firstly, the amount of information it easily
holds is limited to only a few items at a time, and secondly, information is lost quickly from the
system. How much information can be held? Answer: only around four items if they are
unfamiliar ones, but around eight if they are relatively familiar items such as numbers, letters or
simple words. How long does information stay within the system? Answer: somewhere between
five and twenty seconds.
For example, you find a telephone number in the White Pages. But someone speaks to
you in between reading the number and being able to dial. This interaction destroys your
mental rehearsal and your ability to get the number correct is lost after five seconds. And after a
20-second interruption, you may recall not even one of the original numbers. To retain such
information you need to rehearse in order to maintain it within an active buffer. This is called the
articulatory loop. Laboratory studies have shown that humans posses a natural articulatory
loop of one and a half seconds. That is, it is “easy” to retain as much as you can say to yourself
within 1 ½ seconds, and do so indefinitely. The other way to retain information is to transfer it to
long term memory.
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3. Long term memory (LTM)
Metaphorically, this is the archival library store where data are filed for retrieval at a
later time. It is held that this system holds information in permanent storage form. The term
permanent memory is favoured by some writers. Certainly, LTM storage will be affected
dramatically by disease or brain trauma, but this system is not subject to the same decay
processes that beset one’s STM efficiency. In short, the passage of time alone does not dim
this system.
There are still many problems with storage within the LTM. One major issue is that the
system does not possess anything like the FTP download capability of a computer. There is no
human equivalent to transferring information from one’s floppy disk to one’s hard drive. It is
often noted that the major cause of apparent forgetting in humans is actually forgetting to learn
properly in the first place. As we noted earlier, humans tend to be overly confident in their
learning ability, and underestimate the time and effort required to achieve skills.
It is assumed that there are no natural spatial limits on LTM, ie we have yet to come
across any healthy human being whose LTM capacity has reached a top limit. Indeed, the
principle of prior knowledge even suggests the opposite, ie the more knowledge you have the
easier it becomes to learn even more. In the course of aging, the mind may lose often certain
agilities, notably those to do with fast accessing, but the volume of material stored primarily is
not affected.
The major problems of the LTM system hinge around three aspects: Viz, (a) the sheer
difficulty of loading information into the system, (b) the use of efficient encoding strategies
which enable inputs to be fully processed and so interpreted in such a way as to relate to what
the head already knows, and (c) the use of efficient retrieval strategies which enable recovery
of the stored data. Each of these three can involve high levels of conscious effort and thinking,
consistent with what is referred to as the “good information processing” model of human
cognition. Within contemporary psychology we find a large number of concepts used to
describe how the LTM operates. These concepts and their research findings are treated in
depth in chapter 6 of your textbook
4. The nature of learning: The need for strategies
The multi-store theory portraits learning in terms of transfer of information across the
memory banks within the mind. Whereas the sensory store appears to take in a good deal, the
process of attention ensures that only a few items are transferred into the STM. In this sense,
attention operates as a filter keeping a high level of information out of consciousness.
Within the STM information may be held for brief periods, but unless immediately refreshed it
fades quickly, and is lost forever. On the other hand, the learner can use strategies to moves
the data into LTM. This entails some form of active responding in that the mind has to “do
something with this stuff before it disappears”. But what?
The mind could try a bit of CRIME: ie, chunking, rehearsal, imagery, mnemonics,
and elaboration. Chunking is involved whenever the mind groups items together that did not
necessarily come together in direct experience. Chunking can mean to group, sort, organise or
classify. The central idea is that the mind is able to reduce mental load by arranging related
items into a meaningful pattern. These patterns stem from prior knowledge.
Rehearsal means literally to repeat oneself, ie to refresh the data. This can be done subvocally,
within a verbal buffer. When one rehearses aloud it is called recitation. The mind is working on
the theory that repetition will make the memory trace more permanent. When this practice is
applied to data that cannot be linked to existing knowledge we may use the term “rote learning”.
In the early childhood years this strategy generally takes the form basic labelling (ie naming
whatever stimulus is present within immediate view). In later childhood, rehearsals may take
the form of a list that can be quietly repeated to oneself. By adolescence, rehearsal can take
the form of a cumulative rehearsal-fast finish, a much more sophisticated form.
Imagery is another way to respond to an input experience, which is described in depth
in chapter 3. Literally, this means to “picture it” within the mind, a skill that some people report
they use very naturally. We encounter some people, for example who claim that they even
recall telephone numbers not by rehearsing them subvocally, but by imagining what the
numbers actually look like written down. This writer once worked with a person who claimed to
recall telephone numbers by “projecting” the number onto a blank wall.
Mnemonics is really a general word that can be used to refer to any memory device,
but we may tend to use the term more readily to refer to temporary tricks such as ROYGBIV, or
Every Boy Deserves Fruit, or even CRIME. As a student you will know of specific mnemonics
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which relate to problems within your areas of knowledge. Such tricks exist, for example, for
being able to memorise the value of pi, the periodic tables, the positions of planets, the nerves
of the body, etc.
Elaboration means to process information by adding to it in meaningful ways, ie to use
the input information as a trigger for bringing other data into consciousness, and so fusing the
new with the old to create a more durable and accessible memory trace. Let us try to illustrate
this: (a) you have to learn a number, 7812815, and realise that you were born in 1978, in the
month of December, so you “pretend” that it was quarter past 8 in the morning, and (b) you
read the word “Taipan” in the TV programme, and your mind crosses back to when you were in
Queensland and the farmers told you to watch out for deadly snakes hiding in the cane fields.
In both instances your memory for the inputs (the number and the TV programme) is enhanced
simply because you elaborated on them at the moment of initial exposure. Such elaborations
may be either involuntary, or quite deliberately employed as a conscious learning strategy in
which prior knowledge associations are used to advantage. (Note: virtually all the memory
training schemes or books base themselves around the principles of elaboration)
5. Final note
This concludes our introductory tutorial on information processing theory. The story will be
taken up in depth in McInerney and McInerney. Also, you may find it helpful to also consult
other texts that are designed for the undergraduate student. Indeed, any basic textbook within
psychology or educational psychology will have at least one chapter on basic information
processing and cognitive learning theory, and most texts generally have good use of visuals
such as flow diagrams.
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REFERENCES
The following were cited in this Study guide, but are not part of the reading program, and are
not cited within the text or readings used within the current course.
Bereiter, C & Scardamalia, M (1993). Surpassing ourselves. Chicago: Open Court.
Ceci, S & Bruck, M (1995). Jeopardy in the courtroom: a scientific analysis of children’s testimony.
Washington: American Psychological Association.
Dweck, Carol (2000). Self-theories: their role in motivation, personality, and development. Phil, PA:
Psychology Press.
Howe, M J A (1990). The origins of exceptional abilities. Oxford: Blackwell.
Howe, M.J.A. (1999). Genius explained. Cambridge: Cambridge University Press
McInerney, D. M. & McInerney, V. (2002). Educational psychology: Constructing learning, 3rd Edition.
Frenchs Forest, NSW: Prentice Hall.
Seligman, M E P (1990). Learned optimism. New York: Alfred Knopf. (Published within Australia by
Random House).
Weisberg, R W (1993). Creativity: beyond the myth of genius. New York: Freeman.
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