effective policy for teaching, testing, talent and technology
TRANSCRIPT
Effective policy forteaching, testing, talent and technology
Andreas SchleicherDirector for Education and Skills
Trends in science performance (PISA)
2006 2009 2012 2015
OECD
450
470
490
510
530
550
570
OECD average
Stu
de
nt
pe
rfo
rma
nc
e
Trends in science performance (PISA)
450
470
490
510
530
550
570
2006 2009 2012 2015
OECD average
Poverty is not destiny - Science performanceby international deciles of the PISA index of economic, social and cultural status (ESCS)
280
330
380
430
480
530
580
630D
om
inic
an R
ep
ub
lic 4
0A
lge
ria 5
2K
oso
vo
10
Qa
tar
3F
YR
OM
13
Tu
nis
ia 3
9M
on
ten
eg
ro 1
1Jord
an 2
1U
nite
d A
rab
Em
ira
tes 3
Ge
org
ia 1
9L
eb
an
on
27
Indo
nesia
74
Me
xic
o 5
3P
eru
50
Co
sta
Ric
a 3
8B
razil
43
Tu
rke
y 5
9M
old
ova 2
8T
haila
nd
55
Co
lom
bia
43
Ice
lan
d 1
Trin
idad
and
Tob
ago
14
Ro
ma
nia
20
Isra
el 6
Bu
lga
ria
13
Gre
ece
13
Russia
5U
rug
ua
y 3
9C
hile
27
Latv
ia 2
5L
ith
uan
ia 1
2S
lova
k R
ep
ub
lic 8
Italy
15
Norw
ay 1
Sp
ain
31
Hun
ga
ry 1
6C
roa
tia
10
De
nm
ark
3O
EC
D a
vera
ge
12
Sw
ed
en
3M
alta 1
3U
nite
d S
tate
s 1
1M
acao
(C
hin
a)
22
Ire
lan
d 5
Au
str
ia 5
Po
rtug
al 2
8L
uxe
mb
ourg
14
Hon
g K
on
g (
Ch
ina
) 2
6C
zech
Rep
ublic
9P
ola
nd
16
Au
str
alia
4U
nite
d K
ing
do
m 5
Can
ad
a 2
Fra
nce 9
Ko
rea
6N
ew
Zea
land
5S
witze
rlan
d 8
Ne
the
rlan
ds 4
Slo
ve
nia
5B
elg
ium
7F
inla
nd
2E
sto
nia
5V
iet
Nam
76
Ge
rma
ny 7
Jap
an 8
Chin
ese
Ta
ipe
i 1
2B
-S-J
-G (
Chin
a)
52
Sin
ga
pore
11
Score
poin
ts
Bottom decile Second decile Middle decile Ninth decile Top decile
Figure I.6.7
% of students
in the bottom
international
deciles of
ESCS
OECD median student
Students expecting a career in scienceFigure I.3.2
0
5
10
15
20
25
30
35
40
45
50
Do
min
ican
Rep
. 1
2C
osta
Ric
a 1
1Jord
an
6
Un
ite
d A
rab E
m.
11
Me
xic
o
6C
olo
mbia
8Le
ban
on
15
Bra
zil
19
Peru
7Q
ata
r 19
Un
ite
d S
tate
s
13
Ch
ile 1
8T
un
isia
1
9C
anad
a 2
1S
loven
ia 1
6T
urk
ey 6
Austr
alia
1
5U
nite
d K
ing
dom
1
7M
ala
ysia
4
Kazakhsta
n
14
Spain
1
1N
orw
ay
21
Uru
guay 1
7S
ing
apo
re 1
4T
rin
ida
d a
nd T
. 13
Isra
el 2
5C
AB
A (
Arg
.)
19
Port
ug
al 18
Bulg
aria
2
5Ir
ela
nd
1
3K
osovo
7A
lge
ria
12
Ma
lta
1
1G
reece
12
Ne
w Z
eala
nd 2
4A
lba
nia
2
9E
sto
nia
1
5O
EC
D a
vera
ge 1
9B
elg
ium
1
6C
roa
tia
1
7F
YR
OM
2
0Lithu
ania
2
1Ic
ela
nd
2
2R
ussia
1
9H
KG
(C
hin
a)
2
0R
om
an
ia
20
Ita
ly 1
7A
ustr
ia
23
Mo
ldova
7La
tvia
1
9M
onte
neg
ro 1
8F
rance
21
Lu
xe
mbo
urg
1
8P
ola
nd
13
Ma
ca
o (
Ch
ina
) 10
Ch
ine
se
Taip
ei 2
1S
wede
n 2
1T
ha
iland
2
7V
iet
Nam
1
3S
witzerl
and
2
2K
ore
a
7
Hu
nga
ry 2
2S
lovak R
epub
lic
24
Japa
n 1
8F
inla
nd
24
Geo
rgia
2
7C
zech R
epu
blic
2
2B
-S-J
-G (
Chin
a)
31
Ne
therl
and
s
19
Germ
any 3
3In
don
esia
1
9D
enm
ark
4
8
%Percentage of students who expect to work in science-related professional and technical occupations when they are 30
Science-related technicians and associate professionals
Information and communication technology professionals
Health professionals
Science and engineering professionals
% o
f st
ud
ents
wit
hva
gu
e o
r m
issi
ng
exp
ecta
tio
ns
0
10
20
30
40
50
300 400 500 600 700
Pe
rce
nta
ge
of
stu
de
nts
ex
pe
cti
ng
a
ca
ree
r in
sc
ien
ce
Score points in science
Low enjoyment of science
High enjoyment of science
Students expecting a career in scienceby performance and enjoyment of learning
Figure I.3.17
SingaporeCanadaSloveniaAustralia
United KingdomIreland
Portugal
Chinese TaipeiHong Kong (China)
New ZealandDenmark
JapanEstoniaFinland
Macao (China)Viet Nam
B-S-J-G (China)Korea
GermanyNetherlandsSwitzerland
BelgiumPoland
SwedenLithuaniaCroatiaIcelandGeorgiaMalta
United StatesSpainIsrael
United Arab Emirates
BrazilBulgaria
ChileColombiaCosta Rica
Dominican RepublicJordanKosovo
LebanonMexico
PeruQatar
Trinidad and TobagoTunisiaTurkey
Uruguay
Above-average science performance
Stronger than average beliefs in science
Above-average percentage of students expecting to work in a science-related occupation
Norway
Multip
le o
utc
om
es
8 Looking forward to…Better anticipate the evolution of the demand for 21st century skills and better integrate the world of
work and learning
Leverage the potential of all learners
Find more innovative solutions to what we learn, how we learn, when
we learn and where we learn
Advance from an industrial towards a professional work organisation
Building learning systems that…
The kind of things that are easy to teach are
now easy to automate, digitize or outsource
35
40
45
50
55
60
65
70
1960 1970 1980 1990 2000 2006 2009
Routine manual
Nonroutine manual
Routine cognitive
Nonroutine analytic
Nonroutine interpersonal
Mean task input in percentiles of 1960 task
Robotics
The Auto-auto>1m km,
one minor accident,
occasional human intervention
Augmented Reality
A lot more to come
• 3D printing
• Synthetic biology
• Brain enhancements
• Nanomaterials
• Etc.
Education in the past
Education now
What teachers say and what teachers do
What knowledge, skills and character qualities do
successful teachers require?
96% of teachers: My role as a teacher is to facilitate students own inquiry
What knowledge, skills and character qualities do
successful teachers require?
86%: Students learn best by findings solutions on their own
What knowledge, skills and character qualities do
successful teachers require?
74%: Thinking and reasoning is more important than curriculum content
Prevalence of memorisationrehearsal, routine exercises, drill and
practice and/or repetition
-2.00 -1.50 -1.00 -0.50 0.00 0.00 0.50 1.00 1.50 2.00
Switzerland
Poland
Germany
Japan
Korea
France
Sweden
Shanghai-China
Canada
Singapore
United States
Norway
Spain
Netherlands
United Kingdom
Prevalence of elaborationreasoning, deep learning, intrinsic motivation, critical thinking, creativity, non-routine problems
High Low Low High
Learning time and science performanceFigure II.6.23
Finland
Germany Switzerland
Japan Estonia
Sweden
NetherlandsNew Zealand
Macao(China)
Iceland
Hong Kong(China) Chinese Taipei
Uruguay
Singapore
PolandUnited States
Israel
Bulgaria
Korea
Russia Italy
Greece
B-S-J-G (China)
Colombia
Chile
Mexico
Brazil
CostaRica
Turkey
MontenegroPeru
QatarThailand
UnitedArab
Emirates
Tunisia
Dominican Republic
R² = 0.21
300
350
400
450
500
550
600
35 40 45 50 55 60
PIS
A s
cie
nce s
co
re
Total learning time in and outside of school
OECD average
OECD average
OEC
D a
vera
ge
Learning time and science performanceFigure II.6.23
6
7
8
9
10
11
12
13
14
15
16
0
10
20
30
40
50
60
70
Fin
land
Germ
any
Sw
itzerl
and
Japa
nE
sto
nia
Sw
ede
nN
eth
erl
and
sN
ew
Zeala
nd
Austr
alia
Czech R
epu
blic
Ma
ca
o (
Ch
ina
)U
nite
d K
ing
dom
Ca
nad
aB
elg
ium
Fra
nce
No
rwa
yS
loven
iaIc
ela
nd
Lu
xe
mbo
urg
Irela
nd
La
tvia
Ho
ng K
on
g (
Chin
a)
OE
CD
avera
ge
Ch
ine
se
Taip
ei
Austr
iaP
ort
ug
al
Uru
guay
Lithu
ania
Sin
gapo
reD
enm
ark
Hu
nga
ryP
ola
nd
Slo
vak R
epub
licS
pain
Cro
atia
Un
ite
d S
tate
sIs
rael
Bulg
aria
Kore
aR
ussia
Ita
lyG
reece
B-S
-J-G
(C
hin
a)
Co
lom
bia
Ch
ileM
exic
oB
razil
Co
sta
Ric
aT
urk
ey
Mo
nte
neg
roP
eru
Qata
rT
ha
iland
Un
ite
d A
rab E
mira
tes
Tun
isia
Do
min
ican
Rep
ublic
Score
poin
ts in s
cie
nce p
er
hour
of to
tal le
arn
ing t
ime
Hours Intended learning time at school (hours) Study time after school (hours) Score points in science per hour of total learning time
23 Teachers’ skillsNumeracy test scores of tertiary graduates and teachers
Numeracy score215 235 255 275 295 315 335 355 375
SpainPolandEstonia
United StatesCanadaIreland
KoreaEngland (UK)
England/N. Ireland (UK)Denmark
Northern Ireland (UK)France
AustraliaSweden
Czech RepublicAustria
NetherlandsNorway
GermanyFlanders (Belgium)
FinlandJapan
Numeracy score
Numeracy skills of middle half of
college graduates
24 Teachers’ skillsNumeracy test scores of tertiary graduates and teachers
Numeracy score215 235 255 275 295 315 335 355 375
SpainPolandEstonia
United StatesCanadaIreland
KoreaEngland (UK)
England/N. Ireland (UK)Denmark
Northern Ireland (UK)France
AustraliaSweden
Czech RepublicAustria
NetherlandsNorway
GermanyFlanders (Belgium)
FinlandJapan
Numeracy score
Numeracy skills of teachers
25 Professional knowledge and expertise in teaching
Behaviour
Cognition
Content
Character
• Effectiveness is evidenced by teacher
behaviour and student learning outcomes
• Teachers as thoughtful, sentient beings,
characterised by intentions, strategies,
decisions and reflections
• The nature and adequacy of teacher
knowledge of the substance of the
curriculum being taught
• The teachers serve as moral agents,
deploying a moral-pedagogical craft
Teacher knowledge of, and sensitivity to, cultural, social and political contexts and the environments of their students.
External forces
exerting pressure and
influence inward on
an occupation
Internal motivation and
efforts of the members
of the profession itself
26 Professionalism
Professionalism is the level of autonomy and internal regulation exercised by members of an
occupation in providing services to society
Policy levers to teacher professionalism
Knowledge base for teaching (initial education and incentives for professional development)
Autonomy: Teachers’ decision-making power over their work (teaching content, course offerings, discipline practices)
Peer networks: Opportunities for exchange and support needed to maintain high standards of teaching (participation in induction,
mentoring, networks, feedback from direct observations)
Teacher
professionalism
Teacher professionalism
Knowledge base for teaching (initial education and incentives for professional development)
Autonomy: Teachers’ decision-making power over their work (teaching content, course offerings, discipline practices)
Peer networks: Opportunities for exchange and support needed to maintain high standards of teaching (participation in induction,
mentoring, networks, feedback from direct observations)
High Peer Networks/Low Autonomy
High Autonomy Knowledge Emphasis
Balanced Domains/High Professionalism
Balanced Domains/Low Professionalism
Teacher professionalism
0
1
2
3
4
5
6
7
8
9
10S
pain
Ja
pa
n
Fra
nce
Bra
zil
Fin
land
Fla
nd
ers
No
rwa
y
Alb
ert
a (
Ca
na
da
)
Au
str
alia
De
nm
ark
Isra
el
Ko
rea
Un
ite
d S
tate
s
Cze
ch R
epu
blic
Sh
an
gh
ai (C
hin
a)
Latv
ia
Ne
the
rla
nd
s
Po
land
En
gla
nd
Ne
w Z
ea
land
Sin
ga
po
re
Esto
nia
Networks Autonomy Knowledge
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.33030 TALIS Teacher professionalism index
0
10
20
30
40
50
60
70
80
90
100D
iscu
ss indiv
idual
students
Share
reso
urc
es
Team
confe
rence
s
Colla
bora
te for
com
mon
standard
s
Team
teach
ing
Colla
bora
tive
PD
Join
t act
ivitie
s
Cla
ssro
om
obse
rvations
Perc
enta
ge o
f te
ach
ers
Average Shanghai (China)
Professional collaboration
Percentage of lower secondary teachers who report doing the following activities at least once per month
Teacher co-operation
Informal exchange
Teachers Self-Efficacy and Professional Collaboration
11.40
11.60
11.80
12.00
12.20
12.40
12.60
12.80
13.00
13.20
13.40
Never
Once
a y
ear
or
less
2-4
tim
es
a y
ear
5-1
0 t
imes
a y
ear
1-3
tim
es
a m
onth
Once
a w
eek o
r m
ore
Teach
er
self-e
ffic
acy
(le
vel)
Teach jointly as a team in the same class
Observe other teachers’ classes and provide feedback
Engage in joint activities across different classes
Take part in collaborative professional learning
Less frequently
Morefrequently
Technology can amplify innovative teaching
• As tools for inquiry-
based pedagogies
with learners as
active participants
• Make it faster
and more granular
• Collaborative platforms
for teachers to share and
enrich teaching materials
• Well beyond textbooks, in
multiple formats, with little
time and space constraints
Expand
access to
content
Collaboration
for
knowledge
creation
Support
new
pedagogies
Feedback
450
460
470
480
490
500
510
520
-2 -1 0 1 2
Sco
repoin
tsTechnology in schools and digital skills still don’t square
Source: Figure 6.5
Relationship between students’ skills in reading and computer use at school (average across OECD countries)
OECDaverage
Digital readingskills of 15-year-olds
Intensive technology useNo technology use
Routine cognitive skills Conceptual understanding, complex ways of thinking, ways of working
Some students learn at high levels All students need to learn at high levelsStudent inclusion
Curriculum, instruction and assessment
Standardisation and compliance High-level professional knowledge workersTeacher quality
‘Tayloristic’, hierarchical Flat, collegialWork organisation
Primarily to authorities Primarily to peers and stakeholdersAccountability
What it all meansThe old bureaucratic system The modern enabling system
3838Lessons f
rom
hig
h p
erf
orm
ers
38
38 Thank you
Find out more about our work at www.oecd.org/edu– All publications
– The complete micro-level database
Email: [email protected]
Twitter: SchleicherOECD
and remember:
Without data, you are just another person with an opinion