What if nearly everything we do in education actually makes a difference? In this episode, we welcome the brilliant John Hattie, a pioneering figure in educational research, to unravel the mysteries behind effective teaching practices. John takes us on a fascinating journey through his career, from his early days in psychometrics and statistics to his groundbreaking work on meta-analysis. His move to New Zealand marked a turning point, leading to the development of "Visible Learning," a transformative approach that has reshaped how we understand educational success. John shares his insightful perspectives on the shift from asking "what works" to "what works best," revealing the hidden stories numbers can tell.
Join us as we explore surprising findings about educational practices, where 95% show positive effects on student learning. John challenges us to rethink common assumptions, such as the impact of class size and teacher subject matter knowledge, and underscores the value of evidence-based approaches. With his candid anecdotes, John highlights how "Visible Learning" unexpectedly gained traction, fostering a global shift towards research-informed teaching methods. This episode illuminates the critical role of listening and the evolving landscape of educational data and theory since John's influential 2008 work.
Listeners can expect to be engaged by discussions on the importance of reflective practices, the role of artificial intelligence in lesson planning, and the dynamic interplay between teaching methods and student outcomes. Together, we examine the necessity for intentional alignment in education, advocating for methods that resonate with content and goals. Our conversation with John is rich with thought-provoking insights, offering a fresh perspective on how education can be reimagined to serve both students and teachers more effectively. As we wrap up, we reflect on the vibrant world of ideas that defines our times and express heartfelt gratitude to John for sharing his wisdom, with hopes of continuing this enlightening dialogue in the future.
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Chris Colley (00:13):
All right.
So here we are, another episodeof ShiftED Podcast, and I have
a real treat for our listenersacross the province, across the
world I am reaching literallyacross the world.
I'm pulling in John Hattie overin Melbourne and he's morning,
I'm day, and hey, we had a greatlittle intro chat and I was
(00:36):
just so excited to have theopportunity to have John on the
podcast to talk about not onlyhis research but where it all
kind of started for him.
So we're going to kind of do alittle a smallish deep dive
within the time that we have.
So, john, thanks so much fortaking some time and joining us.
John Hattie (00:49):
It's a pleasure.
Chris Love talking about thisstuff.
Chris Colley (00:53):
Oh, it's so fascinating.
So before I start, I'd love tojust kind of build a little
foundation on which we can haveour conversation, and I kind of
mentioned that at the beginningof this that you had gotten your
PhD just across our nextprovince over in Ontario from
(01:13):
University of Toronto and youdid your first degree in
statistics.
John Hattie (01:16):
Is that correct?
Psychometrics, yes.
Statistics, yes.
That was the basis.
Chris Colley (01:20):
Right, and what led you to that?
Where did that interest begin?
That you liked numbers andresearching and finding stuff
out?
Where did all that interestbubble up from?
John Hattie (01:30):
Well, I have to give credit to Mr Tomlinson, my
math teacher in my final year ofhigh school, who turned me on
to the subject and made merealize that it was worth doing
and it was fun.
But I also lived in a smallcountry town and the only way I
could get out of that town, as Idiscovered, is they paid you to
be a teacher.
I trained to be a teacher andso I had the chance of.
(01:52):
Another Canadian.
Tom McGuire from Alberta, cameout to New Zealand, where I was
at the time, and he said, yeah,why don't you continue in the
area?
And he put me on to Oise as theplace to go.
And so I went there and had areally exciting, wonderful
experience.
Said, yeah, why don't youcontinue in the area?
And he put me onto Oise as theplace to go.
And so I went there and had areally exciting, wonderful
experience.
Got used to shoveling, snow andskiing and ice hockey and all
(02:12):
the things you're supposed tonot do while you're doing a
student, and my specializationwas in psychometrics and
statistics, so that's where itstarted.
But the funny thing about that,chris, is that and I'm sure
many of your listeners willappreciate this we kind of
tolerate it in faculties ofeducation.
I kind of think, yeah, we needsomeone in that area.
(02:34):
But and so when I first took myfirst job on, everyone told me
that if I was going to besuccessful, I had to study,
ironically, what they werestudying, because it's going to
make the difference whether itbe communication or technology
or curriculum, and it kind ofbemused me that everybody knew
the answer.
It was what they were doing.
(02:56):
And then I went out into schoolsas part of teacher education
and I met many, many teacherswith the same philosophy.
All you need to do, john, iswatch me, because how I teach is
wonderful and I've never metyet I don't know if you have,
chris, I've never met a teacherwho said they're below average
and it didn't make sense because, I'm sorry, I was a kid.
(03:16):
I know teachers varied in termsof their impact on me, and so
it kind of was the bringingtogether, because my whole
career until the last 10 yearshas been in psychometrics, it's
been in measurement, it's notbeen visible learning at all,
and so, about 2009, I decided tofinish all I'd been looking at
(03:39):
on that area of bringingtogether the measurement, to ask
to change the question fromwhat works, because everything
seemed to to what works best andcould we come up with a
relative notion?
And that's kind of where itstarted and it took me about 30,
40 years to collect the data,um, and kind of took over well,
and john, how did that visiblelearning begin for you?
Chris Colley (04:01):
like, what was it?
Was it a conversation you hador was it a part of a study that
you were doing?
John Hattie (04:07):
like, where did the nucleus work begin no, it was a
straight hobby, a side project.
The whole concept of matteranalysis started in 1976, in the
same year that I started mycareer, and so as a measurement
person, I thought the best wayto find out what this new thing
is to do one.
So I did one, then I didanother one, and it was many
(04:27):
years later.
And I remember the moment and Iwas at the University of
Washington in Seattle and I wassitting there thinking maybe if
I did a synthesis ofmeta-analysis, I'd have the data
to change the question, to askabout the relativity of effects.
And that's where it started.
And, as I commented before, inthe first few years the data
were patchy.
There just wasn't enoughmeta-analyses.
(04:48):
I had about 150, which was very, very small.
Now I'm up to almost 3,000.
And so, collecting the data,and then I've just collected the
data, collected the data, andI've had, every now and then
I've gone back and re-looked atit and re-looked at it.
And, as I say, it was only whenI moved to New Zealand in the
year 2000, I thought here's achance to sit down and see if I
can make sense out of this wholething.
(05:10):
And that's where it came.
So it was a very gradual thing.
It was very much a hobby.
It was not part of my day life,but it was fun because of that.
Chris Colley (05:26):
I had no pressure and you cannot believe, chris,
the number of times I got itwrong, right, right.
That's really interesting.
And so, as this hobby evolved,what was the data like?
We talked earlier before wehopped on about how data can
tell these really amazing coolstories, like there's story
behind those numbers.
What were some of those earlystories that really that that
the numbers were showing youthat was what was interesting,
or shocking, or wow.
(05:47):
I never thought of that.
Like, did you have any of thosestories you could tell us?
John Hattie (05:50):
Oh, totally Like.
My whole measurement career hasbeen about the interpretation
of numbers, whereas often datapeople talk about the numbers.
They come up with fancy graphsand pictures and then blame you
if you don't understand them.
I've been quite against that.
So you're right, it was thestory.
What's the story here?
And I really did expect to seea normal distribution of effects
(06:15):
with a kind of a mean aroundthe zero effect, and that's just
not true.
95% of things that we do ineducation enhances a kid's
learning.
That shocked me until Irealized that enhancing learning
means just improvement, whereasthere are many teachers
surprisingly, when you use theaverage of all the effects, 50%
(06:38):
to 60% of teachers have astunning effect on kids stunning
effect they raise learning.
More than a year's growth for ayear's input.
That's really impressive.
And so probably what shocked memost of all is that the whole
distribution of effects isincredibly positive, incredibly
above the zero point.
I did not expect that.
(06:58):
Some of the effects like one ofthe earliest ones in fact, the
very, very first meta-analysiswas on class size.
The effect is positive, butit's tiny, and trying to make
sense of why such an obviousinfluence should be so tiny, it
occupied my brain for many years.
The other one teacher subjectmatter knowledge 0.09.
(07:19):
Why is it so low?
And part of my interest overthe years was trying to look at
those low effects, to come upwith a story, why, like I'm a
data person, I accepted theevidence.
The effect size of subjectmatter knowledge is very, very
small.
And then what is the evidence?
And that's what led me to many,many openings, many different
(07:39):
ways of thinking about the world, which has really helped, and
talking to people like LeeShulman about this.
I talked to him about this andtalked to others about the class
size and many of the other ofthose effects that are very,
very small.
And it still surprises me aboutsome of those small ones.
But the other side of theequation, trying to understand
(08:00):
the big picture, like here's theproblem, chris, with 300
million kids, you could getswamped in data.
In fact, I was very, very proudof my final edition of Visible
Learning in 2008.
It was full of data 500 pagesresplendent with graphs that had
three-mode factor analysis.
You name it.
I had it in it and my biggestcritic read it.
(08:22):
My wife and she said and whattwo people in the world have you
written this for?
So I threw it away bestdecision I ever made and said
focus on the story, focus on thestory, and that's what I think
is what really matters in alldata.
Chris Colley (08:39):
Right and visible learning came out, as you
mentioned in what was it 2008,.
Right.
Visible Learning came out, asyou mentioned in what was it
2008,.
Right, yeah.
What was the initial reactionto your analysis and your
research from scholars orresearchers?
What was that first impressiononce you put that book out?
John Hattie (08:57):
Well, it was my 10th book, so I expected the
same as the previous nine.
No one would notice, and a lotof academic publishing is vanity
.
You do it, you're happy, and Iseriously wrote the book to
finish it.
To get all that done, I spent40 years doing it.
I might as well put it together.
I never expected it to take off.
In fact, the week it waspublished, the Times Education
(09:21):
Supplement did a story on itwhich generated a lot of
interest.
Weirdly, in New Zealand, where Iwas living at the time, the
front page of the majornewspaper above the fold had a
feature on it In January, whichhere is the time where all the
parents are thinking about goingto school.
It created a storm and so Irealized that something was
happening here.
But it was a reasonably slowtakeoff.
(09:45):
But it took off and I stilllook back and do not understand
why it took off.
A book like that you've seen itit's not what you call the
easiest novel to read forbedtime reading.
It's sold over a million.
That's weird in our business.
So I wished I had the secret,but obviously it hit at the
(10:06):
right moment.
Chris Colley (10:07):
Well, I think too, a lot of our thoughts started
to think about that informationand bring it into our practice a
little bit more.
What were some of your greatstories that you heard that
people took the information thatyou had gathered and
synthesized and that had successwith it.
(10:27):
In those earlier, like once thebook first came out, those
first couple of years wherepeople were starting to take
that information in, what weresome of the good surprises that
you discovered through the workthat you had put out there?
John Hattie (10:42):
Well, what you said then, Chris, is that 20 years
ago it would be very abnormalfor a principal to go to the
research literature.
That's not true anymore, and Ithink many others people like
Dylan, william and others havebeen popularizing the notion of
using evidence in schools, andthat's really happened.
(11:03):
It would be tough now for anyminister, any school, to not
look at the evidence.
But they're becoming much wiserinterpreters of it, much better
at critiquing it.
And in the early days I had nointerest of working in schools
on a visible learning program.
It was the team I was workingat with the moment at the time
which was developing the NewZealand assessment scheme.
(11:24):
We'd finished the project andthey said could they switch to
have a go at it?
And I said happy to do it.
But two rules.
One is I don't want to beinvolved.
I know that I can go into aschool, I can give a talk, I
think it goes down pretty well,and by the time I've gone out to
the car park nothing happens.
So I don't want to do that.
And the second thing is I wantit scalable.
(11:44):
I don't want it depending onone or two of you, because the
biggest problem in education iswe don't know how to scale.
We're very good at fixingproblems.
We're pretty hopeless atscaling success.
And so we started and we learneda lot.
We learned a lot about what todo, and one of the things we
learned very quickly is don'ttell teachers how to teach,
(12:06):
which is what a lot ofprofessional learning is.
And one of the big themes thatwe developed is not what you do
that matters, it's how you thinkabout what you do that matters.
And the same as you said aboutdata it's not the data that
matters, it's how you thinkabout the data that matters.
And sometimes we focus on thedata and we don't focus on the
person doing the thinking.
And so we've had some prettygood successes on the early days
(12:32):
.
And then we kept refining andrefining.
It got bigger and bigger.
In fact, it got so large thatit's now been taken over by
companies in the US sort ofoversight the thing for the
world.
I retain the role of qualitycontrol.
I get the data.
The other thing that happenedwas I realised that most
professional learning focused onthe teacher.
Not surprising.
(12:54):
I'm going to focus on the kid.
Yes, if the professionallearning doesn't change what the
kid does, then what was thepoint of it and like one of my
fascinations, for instancecoaching, the effect size of
0.48 on teacher practice but theeffect size on kids 0.08.
It doesn't translate to kids,it doesn't keep its weight down.
(13:15):
No, because we stop at theclassroom door and we don't go
inside, and one of my fixationsat the moment is that changing
the conversation about how weteach to how we learn.
Now I'm greedy, chris, I wantboth.
It's not either or it's both,and so I think that's one of the
things I've learned over theyears is how to reinvent the
(13:36):
story so that you're trying toget at those big picture things.
And so, yeah, it grew and grewand grew, and now we work in
many, many tens of thousands ofschools around the world have
implemented, and so it's takenoff.
Chris Colley (13:49):
I love, too, what you just said before, because I
got that quote.
I think it was from a talk youwere giving how we think about
what we do rather than what wedo, what are we going to do,
like today?
No, think of it.
Like that reflective practice Ifind in education sometimes
gets overlooked and I think thatthat's one of the huge parts of
being a teacher is thatreflective practice that we're
(14:09):
always kind of going back tothink about how did that work?
Could I tweak that?
What's your ideas on that?
John Hattie (14:17):
Well, I struggle with the notion of reflective
practice, chris.
I really do, and the analogy Iwant to use is Alice in
Wonderland.
Like Alice didn't look in themirror and see herself.
And most reflective practice isthat you look at what you do
and you reflect on it.
Like Graham Nuttall showed, 80%of what happens in a class you
don't see or hear, so why wouldyou want to reflect in the
(14:39):
mirror?
What I want you to do is, likeAlice, go onto the other side of
the mirror and see how otherpeople see you.
And this is why things likecollective efficacy are so
powerful but so hard toimplement.
Because so often we've said toteachers Chris, like you're a
teacher, you have the autonomyto teach as you wish, you have
the autonomy to interpret.
When you come and talk to me,you say, oh, but you were there,
(15:05):
you don't understand my kids,you don't understand my teaching
.
We've got all these protectivemechanisms that allow us to look
at that 20% in the mirror.
So, yes, I like the notion ofreflective, but I don't like the
notion that it's been used as amirror kind of notion.
I want others, like in terms ofothers, I want others to come
in your classroom and see theimpact you're having on kids.
(15:25):
I want to talk to the kids.
One of the mistakes I made itwasn't a mistake in one sense,
but it was latter was thatleague table of all those
influences.
So what I was finding in theearly days is teachers were
saying I'm doing this, I'm notdoing these things at the bottom
.
And so that's when we switchedand changed the message to know
thy impact.
It's about your impact.
(15:45):
It begs the question what doyou mean by impact?
It begs the question do thekids understand and like
achievement test scores?
They're the outcomes.
They're not the inputs, they'rethe outcomes.
And so what is the classroomclimate?
Is it safe to make a mistake inthis classroom?
Is it okay to have a sense thatyou feel invited to come and
(16:08):
learn?
Is the concept of what it meansto be successful transparent in
the eyes of the kids?
Do the kids actually see errorsas opportunities, not as
embarrassing?
All these things aboutinterpretation.
That's the kind of reflection Iwant.
So help me here, chris.
I want another word, becausethe minute you say reflective
practice, we say, oh yeah,that's us talking about how we
(16:29):
think.
Chris Colley (16:30):
We get caught up in these, like we have all these
terms right in education allthe time and the hottest one of
the day or the month or the year, and oh, we're going to be
doing this whole language now.
The hottest one of the day orthe month or the year, and oh,
we're going to be doing this, sowhole language now, and I
understand those that it doesbecome a burden on the actual
practice of because it's all inyour head until you actually
look at the kids and the effectthat it's having on your
students.
(16:50):
And I guess I would tweak that.
My reflective is that reflecton how the kids are reacting to
what you are doing, kind ofcoming back to what you quoted
as think about what you're doing.
Rather, you know, like you gotto tweak it a little bit to get
at the meat of change oraffecting success in your
(17:10):
classroom.
John Hattie (17:12):
Like a byline, is when teachers see learning
through the eyes of students.
It's exactly that.
And the word visible learning,like my critics say, it's absurd
because learning is not visible, it's all in the head.
And I'm saying but you missedthe point.
I want to make that in the headmore visible to the kid and to
the teacher.
Not easy, but it's the rightstuff.
Chris Colley (17:32):
That's it Really cool, Like I mean, just this
small chat, John.
Things are starting to sparkalready, and another thing that
you had said was stop talkingand start listening, and I think
, again, that's that same linethat we're kind of, you know,
bouncing around on that.
If we're not listening towhat's going on in our class,
(17:52):
we're just going through themotions.
John Hattie (17:55):
Oh, and we're good at going through the motions.
We're great performers.
Chris, you were a teacher.
We have 20,000 hours ofclassroom transcripts that we've
used.
We know exactly to the decimalpoint, on average, what
percentage of time did you talk,chris?
Chris Colley (18:10):
I tried to talk as little as possible actually.
John Hattie (18:17):
I was a big advocate on getting kids doing
stuff and getting their handsactive.
Chris Colley (18:19):
Do you know what the?
John Hattie (18:20):
average is no 89% Now this is now your point.
How could you possibly hear yourimpact if you're talking 89%?
Now, let me be fair, I'm anacademic.
It's 100%.
Now, my fellow Canadian, lynnSheridan.
I have just finished a book onlearning to listen listen to
(18:41):
learn Because I pointed out toher a couple of years ago I said
isn't it fascinating?
We've got thousands of books onteacher talk, lots of books on
student questions, student talkand voice and agency, but no one
talks about listening.
And I think it's a reallyimportant skill.
I was trained many years ago asa Rogerian counselor, which is
about listening.
(19:01):
It's about demonstrating backto you, chris, that I have not
only heard you, I haveunderstood you.
It doesn't mean to say I agreewith you and I just want to see.
And it's really interestingwhen you ask kids like Pisa
asked 31 million kids, 40% ofthem said the teacher does not
understand how I learn, theteacher does not keep teaching
(19:24):
me till I learn.
And you think this is scary.
Those kids want you tounderstand what they're thinking
because they want to know.
How did you do that, chris?
Like I know, you're a smart guy.
How did you do it?
Now, here's the problem whenyou tell me how you did it.
You edit that.
You went over here, found itwas wrong because you're good at
(19:44):
error management.
You came back, you went oversomewhere else and you finally
got the answer and I say how doyou do it?
And you say, oh, it was obvious.
I went from there.
It's not obvious.
Learning's messy Learning's allover the place and there's a
visible part, right, john, thatyou were talking about.
Chris Colley (19:59):
Like you see it, it's there Exactly.
John Hattie (20:02):
Oh well, like getting a teacher to make a
mistake and talk about itdoesn't happen.
It needs to.
Getting teachers to put up aproblem and say here's a problem
with the wrong answer, how didthe kid get the wrong answer?
Because I can guarantee youthat half the kids in the class
would have got that wrong answerand been told they're wrong.
They want to know how.
Now let me be quick and upfront, because my critics will jump
(20:25):
in here and say learning isalways about something.
They're right, but remember,I'm greedy, I want curriculum
and I want how to think.
So I just think we need a lotmore listening.
Chris Colley (20:36):
I totally agree with you.
So, john, you just had a newbook that came out, the the
sequel.
Right to visible.
Learning the sequel.
What were, what were thebiggest differences between, you
know, the original release tothe sequel, what what's changed
like?
If you could paint that storywith, with the numbers and the
data that you found, um inbetween two, what's the latest
(21:00):
story on how we're doing here?
John Hattie (21:05):
Well, the good news is that not a lot.
The biggest difference was thatin 2008, I had a lot of data
and I was looking for a theory.
In 2023, I have a great theoryand I'm looking for data to
disconfirm it, and so every timea new meta-analysis comes out,
I could be wrong, and that's howscience progresses and that's
(21:27):
what we should be looking at.
And so I think in 2023, I got Ihope I got a lot smarter about
focusing on the story, like, forexample, I took most of the
data out of the book and put iton a free website.
Not only it's reduced the sizeof the book by 500 pages, it
meant that I had to focus on thestory more.
The other difference is that in2023, I had 10 years of data
(21:52):
from implementing it in schools,and so I was able to hopefully
be able to refine the message tobe a lot more direct.
I'm not pretending refine themessage to be a lot more direct.
I'm not pretending it'sstraightforward, but a lot more
direct.
One of my frustrations in 2009is I didn't really understand
the effect of teaching methodsthat well and I didn't focus on
it.
I think it's kind of an irony,chris, that in 2008,.
(22:16):
I published a book on visiblelearning and did not have a
chapter on learning.
Ouch, I've made up for that.
Introduce this notion ofintentional alignment, following
John Biggs' work onconstructive alignment.
What makes the difference inteaching is whether you're
focusing on the facts and theknowledge or the problem and the
(22:38):
teaching methods.
Effectiveness differ.
What we often do in education,though, is we say oh, we're a
knowledge-rich curriculum orwe're a problem-based, and we
polarize it, and the problem isthat problem-based learning is
pretty hopeless forknowledge-rich development, and
direct instruction isn't thatvery good for problem posing.
It's when you use it at theright time for the right focus,
(23:03):
and that unraveled and made alot more sense out of the
different teaching methods, andhere's an observation that stuns
me.
When anyone wanting a master'sor a PhD, it's a perfect topic.
When I look at the 400 and odddifferent teaching methods that
Bob Mazzano identified, only one, maybe two.
Only one covers both thecontent and the problem-based,
(23:24):
the jigsaw method.
Why isn't someone inventingteaching methods that
deliberately cover both, likedirect instruction and
reciprocal teaching, like theacronym DIRT?
We're going to do DIRT.
No one does that, and I justthink this is such an obvious
gap in our whole literature.
Getting away from this notionabout this is how I teach to.
Given the content we'reteaching today, this is how we
(23:47):
do it.
I want two assignments oneabout the content, one about the
problem-based.
I want two different activities, I want two different teaching
methods and that's what helped.
So that was a big differencebetween the two books is try to
better understand the teaching.
As you can see, if you compare,the two books spend a lot more
time on the notion of learning.
Like when I ask teachers abouttheir theory of teaching, quite
(24:09):
frankly it's a very rich, longconversation.
When I ask them about theirtheory of learning, it's silence
.
We must have both.
Chris Colley (24:20):
I like that idea.
It brings me to the KennyRogers model that you had coined
.
You know, knowing when, when doyou hold?
When do you fold?
John Hattie (24:32):
Well, thanks, kenny .
We slightly changed his words.
You've got to know when to holdthem.
You've got to know when to playthem.
Again the point you were makingright at the beginning.
People would go away and sayintentional alignment.
What jargon is that?
Kenny Rogers?
Simple, got to know when tohold him.
Got to know when to play him.
Chris Colley (24:50):
I think all great lessons come from songs.
There's so many great songs outthere that have so many great
lessons.
John Hattie (24:55):
Well, you talked about my PhD thesis.
I hope everybody doing a thesishas a song.
My song was Another, andanother one bites the dust Every
page.
And another one bites the dust.
Thanks.
Chris Colley (25:08):
Queen.
So, john, to kind of like bringthings to a close again.
Thanks so much.
This has been so fun.
I've just really enjoyedtalking with you.
We have AI, right, artificialintelligence.
It's the talk of education now.
It's going to transformeverything.
The paranoia, the excitement, Imean it's a plethora of
feelings that we have towardsthis.
(25:29):
What do you?
What do you?
How do you see this artificialintelligence in our system of
education?
Just from you know, aprofessional standpoint.
John Hattie (25:40):
Well, three things.
Firstly is it's the biggestchange in my lifetime.
The second is don'tunderestimate the skills of
schools and education systems toresist using it.
We've resisted usingtelevisions, calculators, social
media, iphones.
We ban them, all that kind ofstuff.
We're very good and when youlook at the 300 meta-analyses on
(26:03):
technology since 1975, theeffect size has been very small.
We're very good at resisting.
But the third thing is the waythrough this.
What I'm trying to do now and Iinvite listeners to think about
this is what are the skills weneed to teach teachers and kids
to use the AI Like?
Take, for example, what I thinkone of the most critical skills
.
We have to learn how to ask theright questions, private
(26:27):
questions.
Now we know teachers ask two to300 questions a day that
require less than three wordanswers.
We know that a class of kidsnot a kid, a class of kids asks
two to three questions at mostper day about their work.
They don't understand.
We are not very good atteaching kids how to ask
questions.
The problem with AI is, if youask it the wrong question, it
(26:49):
gives you an answer.
We have to be smarter about howwe probe.
The second thing is qualitycontrol.
Kids think and teachers tellkids that it's the teacher's
role to do quality control.
It's not.
We need to teach kids when'sgood, good enough.
We need to teach them.
Is it right or wrong?
How do you fact check?
How?
do you triangulate and, I think,focusing on what are these
(27:12):
skills?
We need to teach kids how towork with each other in teams,
to critique and to improve, andso I'm adopting the adage like
take lesson planning.
I don't understand why ateacher ever plans a lesson.
I want the 80-20 rule.
Get AI to write your lesson foryou and then you use 20% of the
time on quality control.
Improve it.
Now, think about that, chris.
(27:33):
99% of lessons a teacherconstructs, administers to the
kids.
It's too late for qualitycontrol.
It's over.
I think AI has incredibleopportunities.
Yeah, it's got massivedownsides.
I know that We've actuallywritten a paper on the downsides
as well as the upsides, but Ialso worry that it's going to be
one of the slowestinterventions and schools are
(27:55):
going to be the last place.
It happens by teachers, not bykids, and we already know kids
are using it, so we see that asa problem, that cheating.
Well, we just said the sameabout TV.
I remember this dates me in the1950s, when we went from a
pencil to a fountain pen.
We weren't allowed to usebarrows because they were going
to kill writing.
Now you've heard all thosestories.
(28:16):
Come on, teachers, let's getsmart.
How do we look at the skills weneed, how do we develop those
skills ourselves, and I justthink it's an incredible
opportunity.
It could dramatically transformand, adopting the line that
many others have taken is AIwill not put a teacher out of a
job.
A teacher using AI will put ateacher out of a job.
Yeah, well said, john, wellsaid.
Chris Colley (28:38):
AI will put a teacher out of a job.
Yeah, well said, john.
Well said Well.
And that idea of developingskills within our students.
I find that we need more ofthat, and AI is this opportunity
for us to start really thinkingabout.
How do we make kids morecritical, how do we make them
look and dig deeper and questionthings, rather than just
accepting what the teacher said.
John Hattie (28:58):
But I also want them to know knowledge, and
that's where AI can be good.
I use it probably every day.
I don't know something.
In fact I've used it twice thismorning.
There's a new tool out thatactually writes the essay for me
, and I've constructed one.
Read it and the first one Ithought ah.
Then I realized I was the fault.
I asked it.
Such a generalized question.
It gave me a generalized answer.
Such a generalized questionthat gave me a generalized
(29:20):
answer.
So hone, hone, focus qualitycontrol.
Chris Colley (29:25):
That's the skill we need to teach our kids, and
I'd even push that into ourpre-service teachers.
Asking good questions should bea course in itself that you
learn, because, I mean, that'swhat one of our jobs.
John Hattie (29:33):
I feel.
Anyways, that's half the course, chris.
The other half of the course isgetting kids to ask good
questions.
Chris Colley (29:39):
Exactly, first you have to understand what makes a
good question and then thatdevelopment can chris, the other
half of the course is gettingkids to ask good questions.
Yes, exactly, first you have tounderstand what makes a good
question and then thatdevelopment can happen and start
to share it.
John Hattie (29:47):
but they have to have opportunities and, and to
be specific and jargony, it'sprobative questioning.
It's how to probe right a veryspecific kind of question and if
you go and watch in anyclassroom, you'll never see
those questions from thestudents.
Chris Colley (30:02):
I need them.
Very true, you're dropping it'san exciting world we live in a
lot of interesting thoughts,john, for sure I I would love
eventually if we could have youback um I mean I have I've asked
you two questions and thenwe've been chatting, but there's
so much more that we could talkabout and this just been a real
pleasure.
I really, really appreciateyour taking a bit of time out.
(30:27):
Thanks, chris, take care, andwe'll hopefully talk soon.
John, happy 2025.
John Hattie (30:32):
Thank you, Thank you listeners.
All right.
So here we are, another episodeof ShiftED Podcast, and I have
a real treat for our listenersacross the province, across the
world I am reaching literallyacross the world.
I'm pulling in John Hattie overin Melbourne and he's morning,
I'm day, and hey, we had a greatlittle intro chat and I was
(00:36):
just so excited to have theopportunity to have John on the
podcast to talk about not onlyhis research but where it all
kind of started for him.
So we're going to kind of do alittle a smallish deep dive
within the time that we have.
So, john, thanks so much fortaking some time and joining us.
John Hattie (00:49):
It's a pleasure.
Chris Love talking about thisstuff.
Chris Colley (00:53):
Oh, it's so fascinating.
So before I start, I'd love tojust kind of build a little
foundation on which we can haveour conversation, and I kind of
mentioned that at the beginningof this that you had gotten your
PhD just across our nextprovince over in Ontario from
(01:13):
University of Toronto and youdid your first degree in
statistics.
John Hattie (01:16):
Is that correct?
Psychometrics, yes.
Statistics, yes.
That was the basis.
Chris Colley (01:20):
Right, and what led you to that?
Where did that interest begin?
That you liked numbers andresearching and finding stuff
out?
Where did all that interestbubble up from?
John Hattie (01:30):
Well, I have to give credit to Mr Tomlinson, my
math teacher in my final year ofhigh school, who turned me on
to the subject and made merealize that it was worth doing
and it was fun.
But I also lived in a smallcountry town and the only way I
could get out of that town, as Idiscovered, is they paid you to
be a teacher.
I trained to be a teacher andso I had the chance of.
(01:52):
Another Canadian.
Tom McGuire from Alberta, cameout to New Zealand, where I was
at the time, and he said, yeah,why don't you continue in the
area?
And he put me on to Oise as theplace to go.
And so I went there and had areally exciting, wonderful
experience.
Said, yeah, why don't youcontinue in the area?
And he put me onto Oise as theplace to go.
And so I went there and had areally exciting, wonderful
experience.
Got used to shoveling, snow andskiing and ice hockey and all
(02:12):
the things you're supposed tonot do while you're doing a
student, and my specializationwas in psychometrics and
statistics, so that's where itstarted.
But the funny thing about that,chris, is that and I'm sure
many of your listeners willappreciate this we kind of
tolerate it in faculties ofeducation.
I kind of think, yeah, we needsomeone in that area.
(02:34):
But and so when I first took myfirst job on, everyone told me
that if I was going to besuccessful, I had to study,
ironically, what they werestudying, because it's going to
make the difference whether itbe communication or technology
or curriculum, and it kind ofbemused me that everybody knew
the answer.
It was what they were doing.
(02:56):
And then I went out into schoolsas part of teacher education
and I met many, many teacherswith the same philosophy.
All you need to do, john, iswatch me, because how I teach is
wonderful and I've never metyet I don't know if you have,
chris, I've never met a teacherwho said they're below average
and it didn't make sense because, I'm sorry, I was a kid.
(03:16):
I know teachers varied in termsof their impact on me, and so
it kind of was the bringingtogether, because my whole
career until the last 10 yearshas been in psychometrics, it's
been in measurement, it's notbeen visible learning at all,
and so, about 2009, I decided tofinish all I'd been looking at
(03:39):
on that area of bringingtogether the measurement, to ask
to change the question fromwhat works, because everything
seemed to to what works best andcould we come up with a
relative notion?
And that's kind of where itstarted and it took me about 30,
40 years to collect the data,um, and kind of took over well,
and john, how did that visiblelearning begin for you?
Chris Colley (04:01):
like, what was it?
Was it a conversation you hador was it a part of a study that
you were doing?
John Hattie (04:07):
like, where did the nucleus work begin no, it was a
straight hobby, a side project.
The whole concept of matteranalysis started in 1976, in the
same year that I started mycareer, and so as a measurement
person, I thought the best wayto find out what this new thing
is to do one.
So I did one, then I didanother one, and it was many
(04:27):
years later.
And I remember the moment and Iwas at the University of
Washington in Seattle and I wassitting there thinking maybe if
I did a synthesis ofmeta-analysis, I'd have the data
to change the question, to askabout the relativity of effects.
And that's where it started.
And, as I commented before, inthe first few years the data
were patchy.
There just wasn't enoughmeta-analyses.
(04:48):
I had about 150, which was very, very small.
Now I'm up to almost 3,000.
And so, collecting the data,and then I've just collected the
data, collected the data, andI've had, every now and then
I've gone back and re-looked atit and re-looked at it.
And, as I say, it was only whenI moved to New Zealand in the
year 2000, I thought here's achance to sit down and see if I
can make sense out of this wholething.
(05:10):
And that's where it came.
So it was a very gradual thing.
It was very much a hobby.
It was not part of my day life,but it was fun because of that.
Chris Colley (05:26):
I had no pressure and you cannot believe, chris,
the number of times I got itwrong, right, right.
That's really interesting.
And so, as this hobby evolved,what was the data like?
We talked earlier before wehopped on about how data can
tell these really amazing coolstories, like there's story
behind those numbers.
What were some of those earlystories that really that that
the numbers were showing youthat was what was interesting,
or shocking, or wow.
(05:47):
I never thought of that.
Like, did you have any of thosestories you could tell us?
John Hattie (05:50):
Oh, totally Like.
My whole measurement career hasbeen about the interpretation
of numbers, whereas often datapeople talk about the numbers.
They come up with fancy graphsand pictures and then blame you
if you don't understand them.
I've been quite against that.
So you're right, it was thestory.
What's the story here?
And I really did expect to seea normal distribution of effects
(06:15):
with a kind of a mean aroundthe zero effect, and that's just
not true.
95% of things that we do ineducation enhances a kid's
learning.
That shocked me until Irealized that enhancing learning
means just improvement, whereasthere are many teachers
surprisingly, when you use theaverage of all the effects, 50%
(06:38):
to 60% of teachers have astunning effect on kids stunning
effect they raise learning.
More than a year's growth for ayear's input.
That's really impressive.
And so probably what shocked memost of all is that the whole
distribution of effects isincredibly positive, incredibly
above the zero point.
I did not expect that.
(06:58):
Some of the effects like one ofthe earliest ones in fact, the
very, very first meta-analysiswas on class size.
The effect is positive, butit's tiny, and trying to make
sense of why such an obviousinfluence should be so tiny, it
occupied my brain for many years.
The other one teacher subjectmatter knowledge 0.09.
(07:19):
Why is it so low?
And part of my interest overthe years was trying to look at
those low effects, to come upwith a story, why, like I'm a
data person, I accepted theevidence.
The effect size of subjectmatter knowledge is very, very
small.
And then what is the evidence?
And that's what led me to many,many openings, many different
(07:39):
ways of thinking about the world, which has really helped, and
talking to people like LeeShulman about this.
I talked to him about this andtalked to others about the class
size and many of the other ofthose effects that are very,
very small.
And it still surprises me aboutsome of those small ones.
But the other side of theequation, trying to understand
(08:00):
the big picture, like here's theproblem, chris, with 300
million kids, you could getswamped in data.
In fact, I was very, very proudof my final edition of Visible
Learning in 2008.
It was full of data 500 pagesresplendent with graphs that had
three-mode factor analysis.
You name it.
I had it in it and my biggestcritic read it.
(08:22):
My wife and she said and whattwo people in the world have you
written this for?
So I threw it away bestdecision I ever made and said
focus on the story, focus on thestory, and that's what I think
is what really matters in alldata.
Chris Colley (08:39):
Right and visible learning came out, as you
mentioned in what was it 2008,.
Right.
Visible Learning came out, asyou mentioned in what was it
2008,.
Right, yeah.
What was the initial reactionto your analysis and your
research from scholars orresearchers?
What was that first impressiononce you put that book out?
John Hattie (08:57):
Well, it was my 10th book, so I expected the
same as the previous nine.
No one would notice, and a lotof academic publishing is vanity
.
You do it, you're happy, and Iseriously wrote the book to
finish it.
To get all that done, I spent40 years doing it.
I might as well put it together.
I never expected it to take off.
In fact, the week it waspublished, the Times Education
(09:21):
Supplement did a story on itwhich generated a lot of
interest.
Weirdly, in New Zealand, where Iwas living at the time, the
front page of the majornewspaper above the fold had a
feature on it In January, whichhere is the time where all the
parents are thinking about goingto school.
It created a storm and so Irealized that something was
happening here.
But it was a reasonably slowtakeoff.
(09:45):
But it took off and I stilllook back and do not understand
why it took off.
A book like that you've seen itit's not what you call the
easiest novel to read forbedtime reading.
It's sold over a million.
That's weird in our business.
So I wished I had the secret,but obviously it hit at the
(10:06):
right moment.
Chris Colley (10:07):
Well, I think too, a lot of our thoughts started
to think about that informationand bring it into our practice a
little bit more.
What were some of your greatstories that you heard that
people took the information thatyou had gathered and
synthesized and that had successwith it.
(10:27):
In those earlier, like once thebook first came out, those
first couple of years wherepeople were starting to take
that information in, what weresome of the good surprises that
you discovered through the workthat you had put out there?
John Hattie (10:42):
Well, what you said then, Chris, is that 20 years
ago it would be very abnormalfor a principal to go to the
research literature.
That's not true anymore, and Ithink many others people like
Dylan, william and others havebeen popularizing the notion of
using evidence in schools, andthat's really happened.
(11:03):
It would be tough now for anyminister, any school, to not
look at the evidence.
But they're becoming much wiserinterpreters of it, much better
at critiquing it.
And in the early days I had nointerest of working in schools
on a visible learning program.
It was the team I was workingat with the moment at the time
which was developing the NewZealand assessment scheme.
(11:24):
We'd finished the project andthey said could they switch to
have a go at it?
And I said happy to do it.
But two rules.
One is I don't want to beinvolved.
I know that I can go into aschool, I can give a talk, I
think it goes down pretty well,and by the time I've gone out to
the car park nothing happens.
So I don't want to do that.
And the second thing is I wantit scalable.
(11:44):
I don't want it depending onone or two of you, because the
biggest problem in education iswe don't know how to scale.
We're very good at fixingproblems.
We're pretty hopeless atscaling success.
And so we started and we learneda lot.
We learned a lot about what todo, and one of the things we
learned very quickly is don'ttell teachers how to teach,
(12:06):
which is what a lot ofprofessional learning is.
And one of the big themes thatwe developed is not what you do
that matters, it's how you thinkabout what you do that matters.
And the same as you said aboutdata it's not the data that
matters, it's how you thinkabout the data that matters.
And sometimes we focus on thedata and we don't focus on the
person doing the thinking.
And so we've had some prettygood successes on the early days
(12:32):
.
And then we kept refining andrefining.
It got bigger and bigger.
In fact, it got so large thatit's now been taken over by
companies in the US sort ofoversight the thing for the
world.
I retain the role of qualitycontrol.
I get the data.
The other thing that happenedwas I realised that most
professional learning focused onthe teacher.
Not surprising.
(12:54):
I'm going to focus on the kid.
Yes, if the professionallearning doesn't change what the
kid does, then what was thepoint of it and like one of my
fascinations, for instancecoaching, the effect size of
0.48 on teacher practice but theeffect size on kids 0.08.
It doesn't translate to kids,it doesn't keep its weight down.
(13:15):
No, because we stop at theclassroom door and we don't go
inside, and one of my fixationsat the moment is that changing
the conversation about how weteach to how we learn.
Now I'm greedy, chris, I wantboth.
It's not either or it's both,and so I think that's one of the
things I've learned over theyears is how to reinvent the
(13:36):
story so that you're trying toget at those big picture things.
And so, yeah, it grew and grewand grew, and now we work in
many, many tens of thousands ofschools around the world have
implemented, and so it's takenoff.
Chris Colley (13:49):
I love, too, what you just said before, because I
got that quote.
I think it was from a talk youwere giving how we think about
what we do rather than what wedo, what are we going to do,
like today?
No, think of it.
Like that reflective practice Ifind in education sometimes
gets overlooked and I think thatthat's one of the huge parts of
being a teacher is thatreflective practice that we're
(14:09):
always kind of going back tothink about how did that work?
Could I tweak that?
What's your ideas on that?
John Hattie (14:17):
Well, I struggle with the notion of reflective
practice, chris.
I really do, and the analogy Iwant to use is Alice in
Wonderland.
Like Alice didn't look in themirror and see herself.
And most reflective practice isthat you look at what you do
and you reflect on it.
Like Graham Nuttall showed, 80%of what happens in a class you
don't see or hear, so why wouldyou want to reflect in the
(14:39):
mirror?
What I want you to do is, likeAlice, go onto the other side of
the mirror and see how otherpeople see you.
And this is why things likecollective efficacy are so
powerful but so hard toimplement.
Because so often we've said toteachers Chris, like you're a
teacher, you have the autonomyto teach as you wish, you have
the autonomy to interpret.
When you come and talk to me,you say, oh, but you were there,
(15:05):
you don't understand my kids,you don't understand my teaching
.
We've got all these protectivemechanisms that allow us to look
at that 20% in the mirror.
So, yes, I like the notion ofreflective, but I don't like the
notion that it's been used as amirror kind of notion.
I want others, like in terms ofothers, I want others to come
in your classroom and see theimpact you're having on kids.
(15:25):
I want to talk to the kids.
One of the mistakes I made itwasn't a mistake in one sense,
but it was latter was thatleague table of all those
influences.
So what I was finding in theearly days is teachers were
saying I'm doing this, I'm notdoing these things at the bottom
.
And so that's when we switchedand changed the message to know
thy impact.
It's about your impact.
(15:45):
It begs the question what doyou mean by impact?
It begs the question do thekids understand and like
achievement test scores?
They're the outcomes.
They're not the inputs, they'rethe outcomes.
And so what is the classroomclimate?
Is it safe to make a mistake inthis classroom?
Is it okay to have a sense thatyou feel invited to come and
(16:08):
learn?
Is the concept of what it meansto be successful transparent in
the eyes of the kids?
Do the kids actually see errorsas opportunities, not as
embarrassing?
All these things aboutinterpretation.
That's the kind of reflection Iwant.
So help me here, chris.
I want another word, becausethe minute you say reflective
practice, we say, oh yeah,that's us talking about how we
(16:29):
think.
Chris Colley (16:30):
We get caught up in these, like we have all these
terms right in education allthe time and the hottest one of
the day or the month or the year, and oh, we're going to be
doing this whole language now.
The hottest one of the day orthe month or the year, and oh,
we're going to be doing this, sowhole language now, and I
understand those that it doesbecome a burden on the actual
practice of because it's all inyour head until you actually
look at the kids and the effectthat it's having on your
students.
(16:50):
And I guess I would tweak that.
My reflective is that reflecton how the kids are reacting to
what you are doing, kind ofcoming back to what you quoted
as think about what you're doing.
Rather, you know, like you gotto tweak it a little bit to get
at the meat of change oraffecting success in your
(17:10):
classroom.
John Hattie (17:12):
Like a byline, is when teachers see learning
through the eyes of students.
It's exactly that.
And the word visible learning,like my critics say, it's absurd
because learning is not visible, it's all in the head.
And I'm saying but you missedthe point.
I want to make that in the headmore visible to the kid and to
the teacher.
Not easy, but it's the rightstuff.
Chris Colley (17:32):
That's it Really cool, Like I mean, just this
small chat, John.
Things are starting to sparkalready, and another thing that
you had said was stop talkingand start listening, and I think
, again, that's that same linethat we're kind of, you know,
bouncing around on that.
If we're not listening towhat's going on in our class,
(17:52):
we're just going through themotions.
John Hattie (17:55):
Oh, and we're good at going through the motions.
We're great performers.
Chris, you were a teacher.
We have 20,000 hours ofclassroom transcripts that we've
used.
We know exactly to the decimalpoint, on average, what
percentage of time did you talk,chris?
Chris Colley (18:10):
I tried to talk as little as possible actually.
John Hattie (18:17):
I was a big advocate on getting kids doing
stuff and getting their handsactive.
Chris Colley (18:19):
Do you know what the?
John Hattie (18:20):
average is no 89% Now this is now your point.
How could you possibly hear yourimpact if you're talking 89%?
Now, let me be fair, I'm anacademic.
It's 100%.
Now, my fellow Canadian, lynnSheridan.
I have just finished a book onlearning to listen listen to
(18:41):
learn Because I pointed out toher a couple of years ago I said
isn't it fascinating?
We've got thousands of books onteacher talk, lots of books on
student questions, student talkand voice and agency, but no one
talks about listening.
And I think it's a reallyimportant skill.
I was trained many years ago asa Rogerian counselor, which is
about listening.
(19:01):
It's about demonstrating backto you, chris, that I have not
only heard you, I haveunderstood you.
It doesn't mean to say I agreewith you and I just want to see.
And it's really interestingwhen you ask kids like Pisa
asked 31 million kids, 40% ofthem said the teacher does not
understand how I learn, theteacher does not keep teaching
(19:24):
me till I learn.
And you think this is scary.
Those kids want you tounderstand what they're thinking
because they want to know.
How did you do that, chris?
Like I know, you're a smart guy.
How did you do it?
Now, here's the problem whenyou tell me how you did it.
You edit that.
You went over here, found itwas wrong because you're good at
(19:44):
error management.
You came back, you went oversomewhere else and you finally
got the answer and I say how doyou do it?
And you say, oh, it was obvious.
I went from there.
It's not obvious.
Learning's messy Learning's allover the place and there's a
visible part, right, john, thatyou were talking about.
Chris Colley (19:59):
Like you see it, it's there Exactly.
John Hattie (20:02):
Oh well, like getting a teacher to make a
mistake and talk about itdoesn't happen.
It needs to.
Getting teachers to put up aproblem and say here's a problem
with the wrong answer, how didthe kid get the wrong answer?
Because I can guarantee youthat half the kids in the class
would have got that wrong answerand been told they're wrong.
They want to know how.
Now let me be quick and upfront, because my critics will jump
(20:25):
in here and say learning isalways about something.
They're right, but remember,I'm greedy, I want curriculum
and I want how to think.
So I just think we need a lotmore listening.
Chris Colley (20:36):
I totally agree with you.
So, john, you just had a newbook that came out, the the
sequel.
Right to visible.
Learning the sequel.
What were, what were thebiggest differences between, you
know, the original release tothe sequel, what what's changed
like?
If you could paint that storywith, with the numbers and the
data that you found, um inbetween two, what's the latest
(21:00):
story on how we're doing here?
John Hattie (21:05):
Well, the good news is that not a lot.
The biggest difference was thatin 2008, I had a lot of data
and I was looking for a theory.
In 2023, I have a great theoryand I'm looking for data to
disconfirm it, and so every timea new meta-analysis comes out,
I could be wrong, and that's howscience progresses and that's
(21:27):
what we should be looking at.
And so I think in 2023, I got Ihope I got a lot smarter about
focusing on the story, like, forexample, I took most of the
data out of the book and put iton a free website.
Not only it's reduced the sizeof the book by 500 pages, it
meant that I had to focus on thestory more.
The other difference is that in2023, I had 10 years of data
(21:52):
from implementing it in schools,and so I was able to hopefully
be able to refine the message tobe a lot more direct.
I'm not pretending refine themessage to be a lot more direct.
I'm not pretending it'sstraightforward, but a lot more
direct.
One of my frustrations in 2009is I didn't really understand
the effect of teaching methodsthat well and I didn't focus on
it.
I think it's kind of an irony,chris, that in 2008,.
(22:16):
I published a book on visiblelearning and did not have a
chapter on learning.
Ouch, I've made up for that.
Introduce this notion ofintentional alignment, following
John Biggs' work onconstructive alignment.
What makes the difference inteaching is whether you're
focusing on the facts and theknowledge or the problem and the
(22:38):
teaching methods.
Effectiveness differ.
What we often do in education,though, is we say oh, we're a
knowledge-rich curriculum orwe're a problem-based, and we
polarize it, and the problem isthat problem-based learning is
pretty hopeless forknowledge-rich development, and
direct instruction isn't thatvery good for problem posing.
It's when you use it at theright time for the right focus,
(23:03):
and that unraveled and made alot more sense out of the
different teaching methods, andhere's an observation that stuns
me.
When anyone wanting a master'sor a PhD, it's a perfect topic.
When I look at the 400 and odddifferent teaching methods that
Bob Mazzano identified, only one, maybe two.
Only one covers both thecontent and the problem-based,
(23:24):
the jigsaw method.
Why isn't someone inventingteaching methods that
deliberately cover both, likedirect instruction and
reciprocal teaching, like theacronym DIRT?
We're going to do DIRT.
No one does that, and I justthink this is such an obvious
gap in our whole literature.
Getting away from this notionabout this is how I teach to.
Given the content we'reteaching today, this is how we
(23:47):
do it.
I want two assignments oneabout the content, one about the
problem-based.
I want two different activities, I want two different teaching
methods and that's what helped.
So that was a big differencebetween the two books is try to
better understand the teaching.
As you can see, if you compare,the two books spend a lot more
time on the notion of learning.
Like when I ask teachers abouttheir theory of teaching, quite
(24:09):
frankly it's a very rich, longconversation.
When I ask them about theirtheory of learning, it's silence
.
We must have both.
Chris Colley (24:20):
I like that idea.
It brings me to the KennyRogers model that you had coined
.
You know, knowing when, when doyou hold?
When do you fold?
John Hattie (24:32):
Well, thanks, kenny .
We slightly changed his words.
You've got to know when to holdthem.
You've got to know when to playthem.
Again the point you were makingright at the beginning.
People would go away and sayintentional alignment.
What jargon is that?
Kenny Rogers?
Simple, got to know when tohold him.
Got to know when to play him.
Chris Colley (24:50):
I think all great lessons come from songs.
There's so many great songs outthere that have so many great
lessons.
John Hattie (24:55):
Well, you talked about my PhD thesis.
I hope everybody doing a thesishas a song.
My song was Another, andanother one bites the dust Every
page.
And another one bites the dust.
Thanks.
Chris Colley (25:08):
Queen.
So, john, to kind of like bringthings to a close again.
Thanks so much.
This has been so fun.
I've just really enjoyedtalking with you.
We have AI, right, artificialintelligence.
It's the talk of education now.
It's going to transformeverything.
The paranoia, the excitement, Imean it's a plethora of
feelings that we have towardsthis.
(25:29):
What do you?
What do you?
How do you see this artificialintelligence in our system of
education?
Just from you know, aprofessional standpoint.
John Hattie (25:40):
Well, three things.
Firstly is it's the biggestchange in my lifetime.
The second is don'tunderestimate the skills of
schools and education systems toresist using it.
We've resisted usingtelevisions, calculators, social
media, iphones.
We ban them, all that kind ofstuff.
We're very good and when youlook at the 300 meta-analyses on
(26:03):
technology since 1975, theeffect size has been very small.
We're very good at resisting.
But the third thing is the waythrough this.
What I'm trying to do now and Iinvite listeners to think about
this is what are the skills weneed to teach teachers and kids
to use the AI Like?
Take, for example, what I thinkone of the most critical skills
.
We have to learn how to ask theright questions, private
(26:27):
questions.
Now we know teachers ask two to300 questions a day that
require less than three wordanswers.
We know that a class of kidsnot a kid, a class of kids asks
two to three questions at mostper day about their work.
They don't understand.
We are not very good atteaching kids how to ask
questions.
The problem with AI is, if youask it the wrong question, it
(26:49):
gives you an answer.
We have to be smarter about howwe probe.
The second thing is qualitycontrol.
Kids think and teachers tellkids that it's the teacher's
role to do quality control.
It's not.
We need to teach kids when'sgood, good enough.
We need to teach them.
Is it right or wrong?
How do you fact check?
How?
do you triangulate and, I think,focusing on what are these
(27:12):
skills?
We need to teach kids how towork with each other in teams,
to critique and to improve, andso I'm adopting the adage like
take lesson planning.
I don't understand why ateacher ever plans a lesson.
I want the 80-20 rule.
Get AI to write your lesson foryou and then you use 20% of the
time on quality control.
Improve it.
Now, think about that, chris.
(27:33):
99% of lessons a teacherconstructs, administers to the
kids.
It's too late for qualitycontrol.
It's over.
I think AI has incredibleopportunities.
Yeah, it's got massivedownsides.
I know that We've actuallywritten a paper on the downsides
as well as the upsides, but Ialso worry that it's going to be
one of the slowestinterventions and schools are
(27:55):
going to be the last place.
It happens by teachers, not bykids, and we already know kids
are using it, so we see that asa problem, that cheating.
Well, we just said the sameabout TV.
I remember this dates me in the1950s, when we went from a
pencil to a fountain pen.
We weren't allowed to usebarrows because they were going
to kill writing.
Now you've heard all thosestories.
(28:16):
Come on, teachers, let's getsmart.
How do we look at the skills weneed, how do we develop those
skills ourselves, and I justthink it's an incredible
opportunity.
It could dramatically transformand, adopting the line that
many others have taken is AIwill not put a teacher out of a
job.
A teacher using AI will put ateacher out of a job.
Yeah, well said, john, wellsaid.
Chris Colley (28:38):
AI will put a teacher out of a job.
Yeah, well said, john.
Well said Well.
And that idea of developingskills within our students.
I find that we need more ofthat, and AI is this opportunity
for us to start really thinkingabout.
How do we make kids morecritical, how do we make them
look and dig deeper and questionthings, rather than just
accepting what the teacher said.
John Hattie (28:58):
But I also want them to know knowledge, and
that's where AI can be good.
I use it probably every day.
I don't know something.
In fact I've used it twice thismorning.
There's a new tool out thatactually writes the essay for me
, and I've constructed one.
Read it and the first one Ithought ah.
Then I realized I was the fault.
I asked it.
Such a generalized question.
It gave me a generalized answer.
Such a generalized questionthat gave me a generalized
(29:20):
answer.
So hone, hone, focus qualitycontrol.
Chris Colley (29:25):
That's the skill we need to teach our kids, and
I'd even push that into ourpre-service teachers.
Asking good questions should bea course in itself that you
learn, because, I mean, that'swhat one of our jobs.
John Hattie (29:33):
I feel.
Anyways, that's half the course, chris.
The other half of the course isgetting kids to ask good
questions.
Chris Colley (29:39):
Exactly, first you have to understand what makes a
good question and then thatdevelopment can chris, the other
half of the course is gettingkids to ask good questions.
Yes, exactly, first you have tounderstand what makes a good
question and then thatdevelopment can happen and start
to share it.
John Hattie (29:47):
but they have to have opportunities and, and to
be specific and jargony, it'sprobative questioning.
It's how to probe right a veryspecific kind of question and if
you go and watch in anyclassroom, you'll never see
those questions from thestudents.
Chris Colley (30:02):
I need them.
Very true, you're dropping it'san exciting world we live in a
lot of interesting thoughts,john, for sure I I would love
eventually if we could have youback um I mean I have I've asked
you two questions and thenwe've been chatting, but there's
so much more that we could talkabout and this just been a real
pleasure.
I really, really appreciateyour taking a bit of time out.
(30:27):
Thanks, chris, take care, andwe'll hopefully talk soon.
John, happy 2025.
John Hattie (30:32):
Thank you, Thank you listeners.
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