nm1208: er so first thing i'll say is that er from er beginning of next week 
Monday er these er lectures will be moving into brand spanking new sort of 
flashy lecture theatre er in the new agriculture building and er this is er 
where it is so er approach the front entry in meteorology sort of right down 
there er go outsi-, go round outside left side of meteorology to meet in reach 
the entrance to the new ag-, agriculture building lectures theatres one and two 
are on a lower ground floor use stairs or the lift and there will be no access 
to the new building from the old agriculture right does that make sense to 
everybody cool right er what i'm going to talk about today is expertise and er 
the first thing we need to do before we embark on an investigation of any sort 
of area is to define what we're talking about so that we know that we're 
actually talking about the same sort of thing so what constitutes an expert 
right here's er one example from New Forest Post ninth of March nineteen-ninety-
five er 
front page article driving death off the road young drivers at a Forest School 
have been undergoing psychological tests that can help slash the death toll on 
Britain's roads an expert from namex University has been putting forty-five 
Brockenhurst College students through hazard perception tests this week a 
hazard perception test could well be part of the driving test in two years time 
said Dr namex in nineteen-ninety-five [laughter] never mind er [laughter] so in 
this case this journalist from New Forest Post has labelled me an expert 
because somehow i managed to convince him that i knew marginally more about the 
subject area than he did however what does it say in the dictionary okay it's a 
bog standard er Oxford Dictionary er an expert means being practised skilful 
and well informed and obviously the sort of problem with this definition is how 
exactly practised skilful and well informed do you actually have to be before 
we start calling you an expert and er 
one area where the definition of expertise is vital is within the justice 
system so er expertise can actually be officially er conferred by a judge for 
the purpose of court room testimony and in fact f-, quite a few of my 
colleagues have been called up to court to give evidence as psychologists on 
various sort of different aspects particularly driving dri-, driver fatigue and 
various things to do with driving er and in this case the er definition of 
expertise is usually one on training this is er an official one this is 
actually in your handout okay so er for the purposes of justice the courts 
describe an expert as one who's qualified by training or experience to form a 
definitive opinion in areas of science arts or department of trade in which 
laypersons are not prepared to reach accurate conclusions but the problem with 
this sort of definition is that there is evidence that training and experience 
are poor criterion for judging the quality of an expert something we'll 
explore er later so er moving on to more psychological like definitions 
expertise has been seen as the amount and complexity of knowledge gained 
through experience in a domain okay by the way this er these er definitions are 
in your handout so i think they are yeah they should be in your handout so 
don't need to scribble them down that's all right okay this is good old Eysenck 
and Keane our course textbook and er they stated that expertise means being 
good at specific problems within a specific domain in a lot of domains 
expertise is defined by peer review for example with driving top er police 
officers er top police drivers are often put forward as the model of driving so 
they can perform a range of skills which have been defined by other police 
drivers as being important to good driving like er skid control hazard 
perception vehicle control et cetera and most of the time this may be entirely 
sensible so you can assume that they must know something about what they're 
doing however police drivers have got a job to do and that job involves driving 
as fast as possible from A to B and with some advanced driving courses er which 
are usually run by police drivers er one problem with this is that people are 
often taught to drive like policemen and while this includes skills which have 
been shown to be beneficial to reducing accident involvement like hazard 
perception it can also legitimize practices which are inappropriate for people 
who aren't driving police cars so things like driving fast or making progress 
i'm very bitter about that 'cause i recently failed my motorbike test for 
failing to make progress by driving too slow round roundabouts [laughter] and 
er here's another definition put forward by some psychologists er Ericsson and 
Lehmann nineteen-ninety-six argued that er expertise expert performance 
involves an individual being able to produce a consistent performance on demand 
over a range of tasks that are representative of
of a domain that is expert perf-, er expert performers are those individuals 
who can reliably reproduce their skill their superior skill whenever you ask 
them to Ericsson and Lehmann argued that though this is quite a narrow 
definition the advantage of this sort of definition is that at last we have an 
opportunity for measuring expertise okay what we're doing here is 
operationalizing expertise so by by definition that means we can start 
measuring it in laboratory experiments the problem with all the previous 
definitions is because they're so nicely woolly and vague it's very hard to 
actually sit down and measure what we mean er by narrowing down the definition 
like this we can actually start measuring it which means we can start doing 
some science on it but as you can imagine evaluating performance is a real 
problem for this field for example what's a laboratory test for whether someone 
is an expert art critic so we could do something like develop a test of 
their knowledge of history of art but would that be a fair test of whether they 
were a good critic or not so there's great difficulty in operi-, operisati-, er 
operationalizing expertise in many domains so and actually measuring expertise 
quantitatively and what we find with our police drivers' peer review is often 
the only measure of success and er Goodyear in nineteen-ninety-seven brought up 
this point with respect to professional psychologists so with professional 
counselling psychologists for example how can we actually measure the quality 
of their work you know is it the number of people they successfully treat in 
the year in a year or something like that and with academic psychologists like 
me is it the number of papers published the number of research contracts i've 
won not the quality of the papers published okay and these are all things that 
you know are actually used to evaluate us in ra-, real life but you know are 
they fair measures okay i mean and 
you can see there's potential problems for that so for example er er we've we 
get although we get judged for teaching on a sort of department wide basis the 
teaching quality isn't actually formally assessed on a person by person basis 
okay apart from we get informal bits of feedback from the sort of sheets you 
fill in but er the actual formal assessment takes place on a department wide 
proc-, er process so at the moment er i actually have no personal s-, incentive 
for my career to sort of bother to sort of do any good teaching my all my 
incentive is based on research because that's what i personally get judged on 
not the teaching okay so there are problems in judging expertise in this sort 
of way so into the science how have people tried to get around these sort of 
problems well first thing they did was to choose a an appropriate domain and 
they chose a domain where expertise is well defined easy to operationalize and 
measurable and that domain was chess okay so now chess was the er 
original domain for studying expert performance and the nice thing about chess 
is that there are clear criterion distinguishing novices from experts basically 
experts will beat novices and it's also a very well defined game set within a 
very rigid framework of rules and this makes it really nice for experimental 
work on the face of it it should be straightforward okay there's no er chance 
involved there's no do-, dice rolling or anything that that and there are a 
finite in theory finite set of moves that can be made at any one time but it's 
the sheer number of these possible moves which is overwhelming so just three 
moves into a chess game gives you more than nine-million distinct board 
positions and er on the face of it this should be an ideal task for a computer 
however attempts to design computers that can match the best chess players 
hasn't proved to be easy so what er computer chess brai-, er programs tend to 
do is search all available options for example a 
a recent one developed by I-B-M and known as Deep Blue considered about ninety-
billion moves per turn at a rate of about nine billion per second okay and this 
is a computer that i think it eventually managed to beat Gary Kasparov but it 
was a close run thing but the point is that people can't do that our brains 
literally can't think at anywhere near that sort of speed so how come the best 
chess players human chess players still manage to beat computers most of the 
time well what are the best chess players doing that the computers and the 
novice chess players aren't doing originally it was assumed that chess experts 
were better as a result of superior intellectual capacity however it's er since 
been shown that expert chess players aren't actually any cleverer than anyone 
else or cleverer than a matched control group i should say so study found that 
their I-Qs are no higher than matched controls so if their mental capacity 
doesn't appear to be any higher 
than normal then presumably it must be their strategies which are superior so 
how has a chess performance been measured er lot of the original work which was 
carried out by de Groot and er what he did was get er two groups of chess 
players the first group were what he called experts and they were top local 
club players that's his definition of expert and he compared with an with an 
even better group the grand masters so grand masters are world class chess 
players so his comparison is between one really high level of expertise and a 
still a pretty high level of expertise and what he wanted to find out what is 
the difference between these two groups and what he did was er measure it 
measure er their performance and what they're thinking about with er verbal 
protocols and what verbal protocols are is simply getting people to talk aloud 
when they're doing the task and then transcribing what they're saying and 
trying to analyse it okay so he analysed their performance by 
getting them to talk aloud and he also timed their responses and er he 
presented them with a game position and asked them to think aloud while 
deciding what move to make and he found that people were only considering about 
thirty alternative moves searching at most to a depth of six moves and 
frequently less okay and there's a nice summary of all this sort of stuff in 
Eysenck and Keane so the grand masters didn't consider more moves and they 
didn't search more deeply than the experts but they were neverlethe-, 
nevertheless slightly faster at getting to the right move and they also came to 
their chosen move earlier in their search through possible alternatives and er 
that was supported by the finding that the quality of the chess moves that 
these people were making remained high even when you forcibly reduced their 
search time okay so the the best players er still searching similar number of 
options but they're coming to the right option earlier in their search and in a-
, in 
addition they found that the grand masters er actually came up with better 
moves which was assessed by independent raters and what er de Groot argued here 
is that the chess master doesn't generate moves by a simple search through 
possible alternatives which is exactly what our chess computers are doing to 
generate all possible altern-, alternatives and then go through them one by one 
instead our grand masters are using cued recall from memory okay so as i said 
the depth of search how many moves people are thinking ahead er increases up 
the level of our experts but it doesn't actually increase when people move on 
to be grand masters and de Groot suggests that the difference between these 
experts and these grand masters is that the grand masters have a superior 
knowledge of different board positions and what the best move from each 
position would be okay so the idea is that the expert can recognize the 
position and knows a good move from there and that means you don't 
have to think about all of the irrelevant moves which you know in advance are a 
load of rubbish because you've already you can recognize this pattern from your 
memory so you don't have to do what the computer is doing and go though all of 
the irrelevant s-, er possible moves as well and ma-, that makes it much more 
efficient and it means that you don't have to do do this er ninety-billion 
option search every time you make a move and er de Groot's colleagues found 
further evidence to support this in an experiment that involved chess master 
and expert players' recall of board positions they found that if the position 
was from an actual game than the grand masters 
were significantly better at remembering the position but if the position was 
random so you just pick your chess pieces whack them anywhere on the board 
nothing to do with the game then you found no difference between er the two exp-
, expert groups no difference between the experts and the grand masters okay so 
y-, grand masters only get their advantage if they're trying to memorize an 
actual board position and they argued that tha-, this is because the grand 
masters simply knew more game positions so according to move on to Chase and 
Simon who followed up this work what differentiates expert chess players from 
novice chess players is that experts have stored and 
organized in memory many tens of thousands of different game positions and the 
idea is when they saw sensible game positions they could use the knowledge they 
had in memory to help them remember the various positions as integrated 
organized chunks of information and this is the sort of thing that Chase and 
Simon nineteen-seventy-three were looking at okay if you remember back to er 
about this time last year er and my first year practical on memory chunking 
you'll remember that you could remember the same stimuli better when they were 
sort of chunked into groups that linked in with your own personal knowledge 
basis so remember i presented you with a list of sort of letters when i 
arranged them in one group in in certain groups they made no sense and so 
you're trying to remember each individual letter when i arranged them in other 
groups they actually formed er acronyms sort of common acronyms er so that 
instead of having to remember every single letter you could just remember 
the fewer number of acronyms okay so this is all Miller's stuff on there being 
room for seven plus-or-minus two items in short term memory but the size of 
what one of those items is depends on your personal knowle-, knowledge and 
Chase an-, ar-, Simon argued that chess players are chunking the board and the 
more expert you get at chess the bigger more complex your chunks become and er 
chess experts were found to be able to memorize board positions by breaking 
them down into seven or so familiar patterns or units and the difference 
between the novice and expert lay in the amount of information they could hold 
in one chunk so in er one experiment they did people had two chess boards in 
front of them on the first board was an arrangement of pieces and the second 
board was blank and what participants had to do was recreate the position they 
saw on the first board with the pos-, er sorry say that again what participants 
had to do was recreate the position they could see on 
the first board on the second board and what they measured was the number of 
glances that these people had between the two boards and how much they 
remembered in each of these glances okay so they argued that each glance 
between these two boards could be viewed as a chunk and better players could 
rem-, r-, recognize a chunk faster and their chunks were also bigger and er 
work published in nineteen-ninety-six by Gobel and Simon confirms this and er 
they demonstrated that retrieval processes involving recognition of board 
arrangements are actually instrumental in grand master level chess players' 
success compared with er less experienced other players okay so even when the 
grand masters were time constrained so they couldn't engage their looking ahead 
processes their performance isn't much affected okay and they argued this time 
that this suggests that an organized knowledge system is relatively more 
important to experts' performance than even the processes 
involved in predicting future moves okay so the key thing is organization of 
information er organization of knowledge having said that er Holding and 
Reynolds did experiment in nineteen- eighty-two er they reran de Groot's 
experiment using a random board position okay so again chess board and you just 
whack on the pieces at random nothing to do with the game and by comparing 
chess players of different levels on the move they would make from the random 
position they found that the experts produced better moves on even from these 
totally random board positions okay so the idea is here is that er the experts 
couldn't possibly have the board position previously analysed because it was a 
totally random board position er but they inst-, still generated better moves 
on from those random board positions so they argued that er we shouldn't be so 
one-sided about this and there is a important element of chess expertise that 
does involve evaluating board position as well 
as remembering it okay right so half an hour in so er kind of thought er s-, 
skill and learning things this is when your attention should be sort of 
plummeting downhill so i shall attempt to raise it again by doing a quick 
demonstration of one of these experiments if i get you to stick your hand up if 
you've ever been in a chess club [laughter] can i get y-, stick your hand up if 
you've ever played chess before [laughter] bollocks [laughter] right okay could 
you put your hand up if you think you're intermediate chess player y-, sort of 
okayish it's getting tricky i'm going to have to pick at random i think okay 
put your hand up if you've never ever played chess before right out of those 
people who couldn't even name the pieces on a chess board brilliant er cou-, 
could i can i get you to come out right okay and out of the rest of you i need 
to find someone who er okay who who's been playing since they were er a child 
who has played as chess as a child and has played recently as 
well can you stick your hand up [laughter] who's played chess within the last 
four years [laughter] ah brilliant namex
sf1210: oh no 
nm1208: it's all right [laughter] this is undermining okay what i can i get you 
to stand over there and look in that direction okay right 
sf1210: look in which direction 
nm1208: s-, o-, over there just just don't don't look over here okay [laughter] 
and what i'm going to show you i've er what i've designed here is er my acme 
patent overhead chess set [laughter] carefully constructed there okay and 
basically what i'm going to do is er i've got a chess board position from a 
famous game for namex versus namex played this Tuesday [laughter] and er if you 
come and stand here er i'm going to show that for thirty seconds 
nm1208: oh God 
nm1208: and then i'm going to cover it up and then i want you to recreate that 
position on that board as f-, as er fast as you can and you've got about two 
minutes or just tell me y-, when you give up okay [laughter] right and we'll s-,
see okay so you remember in the original experiment this was actually a 
comparison between er expert club 
players and a grand master so we're actually looking at very different levels 
of expertise but we can see whether we can sort of replicate the same sort of 
effect so are you ready and here goes for those of you can't see this board 
position this is probably a very boring part of the lecture [laughter] 
[laughter] okay t-, ten seconds twenty seconds thirty seconds okay off you go 
okay and of course we have the additional problem here is that er these pieces 
are really fiddly to move around okay and what we're going to try and do here 
is er score this by just counting the number of pieces that she gets in the 
right place okay if you wanted to do this scientifically of course then er i'd 
actually 
sf1209: guessed the rest 
nm1208: you're guessing the rest okay that's right er i don't think you did too 
badly there okay er right looking my original piece you've got all the one two 
three four five six seven eight nine you get nine points brilliant thanks very 
much indeed [laughter] that's it [laughter] right okay i'll just er quickly 
scramble this er all right 
okay right er and could i have my er chess grand master [laughter] 
sf1210: 
nm1208: okay right do you want to stand here and first i'm going to show you 
this er real chess board position for thirty seconds then i want you to er 
going to cover it up and then you've got about two minutes to reproduce as much 
as you can remember okay 
sf1210: what on this 
nm1208: er yeah well on er yeah that's right yeah okay you're ready 
sf1210: sorry 
nm1208: [laugh] and go [laughter] er er okay that's ten seconds okay twenty-
seven seconds three two one go okay right get you to reproduce it okay so 
according to de Groot someone who has a basic knowledge of chess er should be 
able to er remember slightly more positions if you noticed with the on the on 
the actual sort of stimuli that the de Groot was using er a-, actually no sorry 
this is ch-, er Chase and Simon this is er obviously because they're using much 
more higher level of chess players er the actual chess boards were like much 
further into the game which is wh-, i deliberately chose one where we-, we're 
only we're only 
about sort of think ten moves into the game there or something like that so a 
lot of the pieces are in their original positions but er [laughter] 
sf1210: i've mixed the colours up does it matter 
nm1208: no [laughter] okay in the scientist's conditions then we would care 
about the colours [laughter] and er okay and er also if this is is this is 
proper science of course i'll be testing like fifty people in each group and er 
and also er control for manual dexterity in moving bits of tiny acetate around 
[laughter] 
sf1212: probably better than you did it 
nm1208: 
okay that's cool thanks very much indeed right so right er we have one two 
[laugh] no [laughter] three four five six seven eight nine ten eleven twelve 
twelve er twelve ha [laughter] hurray [laughter] i don't know whether that 
means it's stati-, statistically significant thanks thank you very much you two 
brilliant er okay i'm not but i'm not going to pretend that's science in action 
there [laughter] okay right so there we have chess nicely defined domain but 
the problem is how do we know that other more complicated and sort of every day 
domains er actually involving the same sort of processes in the real world 
problems are seldom as 
well defined as they are in chess so what research is there looking at 
expertise in domains with less rigid rules and in the literature areas commonly 
study studied involve things like chess medicine and computing so many of the 
features that characterize the expert chess players also seem to characterize 
experts in other domains for example the idea of information chunking was found 
to be important in the domain of computer programming computer programming it's 
been suggested that expert programmers have large chunks of code in memory that 
they can rearrange in order to solve a problem so the idea is that expert 
programmers can remember more code than novices and as Chase and Simon then 
showed with chess they can fit more information into one sort of memory chunk 
of code if you like okay as i said er well that was research by Adelson in 
nineteen-eighty-one one way of er analysing difference between experts and 
novices as i said previously is to get people to talk about 
what they're thinking of when their solv-, when they solve a problem and these 
are verbal protocols and er people have done this looking at these sort of 
domains and they've compared they've transcribed the commentaries and compared 
the statements people are making er between the expert and novice groups and 
they've also compared the length of time people have spent on various aspects 
of the problems and also the relationship between these sort of strategies used 
and the solutions reached and it is using that sort of methods that er Glaser 
and Chi nineteen-eighty-eight found that er one difference between experts and 
novices is their different schemas for er solving problems within their own 
domain of expertise okay this bit of er overhead is actually on the handout so 
you don't need to scribble it down okay and so our schema what i mean by a 
schema is a sort of a plan an outline a structure framework a program okay so 
in this sort of context think of a schema as a sort 
of cognitive mental plan sort of guide for action okay especially in this case 
some sort of organized framework for solving problems and the schemas of 
experts have been argued to involve large highly intercon-, interrelated units 
of knowledge which are organized according to underlying structural 
similarities amongst these knowledge units okay so our experts large highly 
interconnected units of knowledge and connected together er by underlying 
structural similarities a contrast to that is the novices er the idea is that 
the sort of schemas that novices use in a domain are relatively small 
disconnected bits of information which are organized according to superficial 
similarities not structural similarities and er Glaser and Chi this is er fun-, 
er th-, this bit here is actually from er Steinberg nineteen-ninety-ni wo-, 
nine which i'll put in the er reprint collection er this is the difference 
between novices and experts and schemas it can be noted in how they 
classify different various problems er the idea's that experts and novices also 
describe the essential nature of various problems differently and determine how 
to solve various problems differently okay so three key expert novice 
differences and another thing that er researchers have found is that experts 
tend to spend much more time determining how to represent a problem than 
novices that's research by Lesgold et al nineteen-eighty-eight okay so experts 
spend more time representing the problem but they spent less time implementing 
that solu-, the solution or the strategy for th-, the solution and in contrast 
novices tend to dive into a problem without so much of this er initial analysis 
and hence spent much more time trying to figure out solution to the problem so 
differences between experts and novices in these sort of domains in their 
expenditure of time could be viewed in terms of the focus and the direction of 
their problem solving experts 
spend more time figuring out what they already know about the problem and how 
the information given in a problem maps on to what they already know and the 
idea is once the expert finds a previously existing strategy for solving the 
problem they can just put it down out of memory and implement it without too 
much bother okay and another way to describe that is that experts are working 
forward from the given information to find their unknown information okay okay 
so they're going from what do i know to what do i need to find out implementing 
the correct sequence of steps based on strategies they've retrieved from their 
schemas in long term memory okay in contrast to this the novices tend to work 
backwards so what they tend to do is generate a set of alternative solutions to 
start with and then trying to work out which one would be the best one to 
proceed with okay so little time is spent trying to represent the problem 
initially and er to illustrate this difference between forward 
processing and backwards processing here is an example that's in Steinberg 
imagine that we have an expert doctor and a totally green er novice n-, medical 
student and they're both presented with a patient who has a series of symptoms 
first of all what does the novice do well he's not sure exactly what to make of 
the symptoms and so what he does is goes and orders a whole long series of 
expensive er medical tests to be done in the hope that once he's got the full 
information in front of him full symptomatic information he may be able to then 
go ahead and make his diagnosis and he realizes that this illness could be any 
number of a wide range of things and he works backwards to try and sort 
eliminate them and work out exactly which one it is our more experienced doctor 
on the other hand is far more likely to recognize the initial set of symptoms 
he's being presented with as being as fitting a diagnostic pattern or one of a 
small number of patterns that she holds in her 
long term memory she's therefore worked forward from these initial symptoms to 
a much smaller set of possible illnesses and therefore she only needs a very 
small number of highly targeted tests to choose the correct diagnosis from 
among the limited number of possibilities that she's generated okay er okay a 
word of warning with that though is that obviously that's a that's a simple way 
of describing it and as you can imagine in real life get's much more fiddly 
than that okay those are sort of very sort of gross it's a very gross 
generalization on how people operate 'cause obviously as i described at the 
beginning it depends on how you define your expert and how you define your 
novice okay and er another thing to bear in mind is what a w-, first of all 
well wh-, d-, w-, how do we define our expertise and also how people in the 
study have chosen to measure that expertise and this actually makes the whole 
area of expertise quite tricky and when you're actually 
looking at research in this area you should bear that sort of thing in mind 
okay because despite the example i've just given you er what you actually find 
with doctors is that for most cases you don't actually get that much difference 
between novice and expert doctors so it's been found that diagnostic 
performance doesn't actually seem to improve much beyond the first year of 
residency for typical diagnostic cases okay and er there are some small 
differences between doctors with different lengths of experience for everyday 
agn-, diagnosis er though it has been shown there are tend to be much bigger 
differences as soon as you start moving on to more difficult cases okay and 
Boshuizen and Schmidt nineteen-ninety-two found that the expert doctors seem to 
have easier access to higher level structured diagnostic information whereas 
the medical students tended to have to go through this sort of cumbersome 
biomedical reasoning to get to their solutions okay but say we've got to be 
very careful that we don't overgeneralize here because it matters what we're 
actually calling a novice doctor here and what we're calling an expert doctor 
and how we're measuring their expertise another example of a skilled domain 
where the problem may not be as well defined as we would like is physics and er 
it's covered by a lot of research by Chi et al and they tested er expert and 
novice physicists on a range of physics problems 
and they found that the novices tend to use the surface features of the problem 
while the experts er encode far more deeply er in this domain experts solved 
problems four times faster than novices though they spent longer analysing the 
problems and Chi et al argued that these differences between novices and 
experts were as a result of differences in strategy and er knowledge so like 
with the chess the experts who use their superior knowledge of previous 
problems er but er is found that the experts not only had a greater quantity of 
knowledge 
they also organized that knowledge better and er experts also tend to exhibit 
superior memory on unexpected recall tasks possibly as a result of their deeper 
encoding of the problem okay and more research by Larkin et al where they took 
people with equivalent knowledge in solving physics problems but who differed 
on their level differed on their level of expertise and they found that when we 
actually controlled for the amount of knowledge people knew the er the experts 
still showed a superior performance okay so it's not th-, the am-, not just the 
amount of knowledge it's how you structure that knowledge which is important 
and then they described it as pattern based retrieval from memory and like 
medicine er they found that experts tended to use a forward working strategy 
whereas the novices tended to use a backwards working strategy and also this er 
expertise was found to be very domain suspic-, specific so being an expert 
physicist doesn't make you good at anything 
else whatsoever okay and this may reflect the finding that i talked about 
earlier where basic differences like things like I-Q er have surprisingly 
little bearing on expert performance okay er running out of time so i'm going 
to pop on to some people who've tried to summarize this sort of research okay 
er summarizing this sort of research is a problem 'cause as i said before we 
have to be very careful that first of all we know what definition of expert and 
novice we're using secondly we've got to be very careful about exactly how 
we're measuring expertise and the third thing we've got to watch out is that we 
don't overgeneralize from our results okay so it could be that er we say ah 
this is a novi-, this is an expert and the expert can do this this and this but 
then we discover that's only true of experts er solving maths problems and it 
has no bearing on experts er doing chess and things like that so you've got to 
bear all of these sort of these those three things in mind when you're 
analysing this research but er Glaser and Chi again have come come up with er a 
list of things they 
argued were common between different domains of expertise and these are all 
things that we've met previously in the lecture okay so they argued that er 
experts excel mainly in their own domains experts perceive large meaningful 
patterns in domains experts tend to be faster at solving problems experts have 
superior short and long term memory experts see and represent problems in their 
domain at a deeper level than novices and experts spend more time analysing 
problems qualitatively and something we haven't talked about is experts have 
very strong self-monitoring skills okay and you'll see that similar pattern 
reflected in another example i've put in your handout er by Green and Gilhooly 
who tried to do the same thing and came up with five maxims okay right so we've 
looked at the differences between novices and experts one point we haven't 
addressed is how people become experts in the first place so how do you become 
skilful at something how can a-, someone anyone become an expert at something 
or does er can anyone become an expert at something or does genetics play an 
important role and those are the issues we'll be looking at next week i'll see 
you then