1
Supporting Teacher
Professionalism Insights from TALIS 2013
Prevalence of memorisation
rehearsal, routine exercises, drill and practice and/or repetition
-1.60 -1.40 -1.20 -1.00 -0.80 -0.60 -0.40 -0.20 0.00Switzerland
Poland
Germany
Japan
Korea
France
Sweden
Shanghai-China
Canada
Singapore
United States
Norway
Spain
Netherlands
United Kingdom
0.00 0.20 0.40 0.60 0.80 1.00 1.20
Prevalence of elaborationreasoning, deep learning, intrinsic motivation, critical thinking, creativity, non-routine problems
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.333 Background: TALIS 2013
…representing more than 4 million teachers in over 30 coun-tries and economies…
Over 100 thousand randomly selected lower secondary teach-ers and their school leaders from over 6500 schools
…took an internationally-agreed survey about the working condi-tions and learning environments in their schools…
…responding to questions about their background, their teaching practices, support and development, their relationships with col-leagues and students and the leadership in their schools
Profiles of
teacher profession-alism
• Defined as knowledge that is necessary for teaching• Index includes: formal teacher education, and whether the teacher has
incentives for professional development (e.g. receives time release dur-ing professional hours) and participates in professional development
Knowledge
• Defined as teachers’ decision-making power over aspects related to their work
• Index includes decision making over: teaching content, course offerings, discipline practices, assessment and materials
Autonomy
• Defined as opportunities for the information exchange and support needed to maintain high standards of teaching
• Index includes: participation in induction, mentoring programmes and/or network of teachers, receiving feedback from direct observations
Peer networks
5
55 Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.355 Conceptualising Teacher Professionalism
Por
tuga
lS
pain
Geo
rgia
Chi
leJa
pan
Mex
ico
Fran
ceB
razi
lFi
nlan
dC
ypru
sFl
ande
rs (B
elgi
um)
Nor
way
Abu
Dha
bi (U
nite
d A
rab
Em
irate
s)
Icel
and
Alb
erta
(Can
ada)
Aus
tralia
Den
mar
kIs
rael
Kor
eaM
alay
sia
Italy
Uni
ted
Sta
tes
Rom
ania
Bul
garia
Cro
atia
Cze
ch R
epub
licS
lova
kia
Sha
ngha
i (C
hina
)S
erbi
aLa
tvia
Net
herla
nds
Pol
and
Eng
land
(Uni
ted
Kin
gdom
)N
ew Z
eala
ndS
inga
pore
Est
onia
Rus
sia0
2
4
6
8
10
12
14
NetworksAutonomyKnowledge
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.366 Teacher professionalism index across TALIS systems
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.377
Not everywhere where induction programmes are accessible do teachers use them
Percentage of lower secondary teachers with less than 3 years experience at their school and as a teacher, who are working in schools with the following reported access to formal induction programmes, and their reported participation in such programmes
Icel
and
Finl
and
Geor
gia
Serb
ia
Japa
n
Slov
ak R
epub
lic
Net
herla
nds
Nor
way
Albe
rta
(Can
ada)
Flan
ders
(Bel
gium
)
Aust
ralia
Unite
d St
ates
Croa
tia
Kore
a
Aver
age
Russ
ia
Chile
Israe
l
New
Zea
land
Mal
aysia
Engl
and
(Uni
ted
King
dom
)
Rom
ania
Czec
h Re
publ
ic
Sing
apor
e
Shan
ghai
(Chi
na)
0
10
20
30
40
50
60
70
80
90
100
Access
Participation
%
0 10 20 30 40 50 60 70 800
10
20
30
40
50
60
70
80
Netherlands
Romania
Slovak RepublicBulgaria
Iceland
Georgial
Brazil
England (United Kingdom)
AustraliaAlberta (Canada)
Latvia
PortugalKorea
Average
Shanghai (China)
Spain
Abu Dhabi (United Arab Emirates)
Croatia
Poland
Mexico
Chile Norway
FinlandDenmark Flanders (Belgium)
Sweden
Singapore
Italy
EstoniaIsrael
Russia
United States Japan
SerbiaFrance
Malaysia
Percentage of teachers who report presently having an assigned mentor to support them
Perc
enta
ge o
f tea
cher
s wor
king
in sc
hool
s whe
re th
e pr
inci
pal r
epor
ts t
hat m
ento
ring
prog
ram
mes
are
av
aila
ble
for a
ll te
ache
rs in
the
scho
ol
Czech Re-public
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.388
Not everywhere where principals say mentoring is availabledo teachers have mentors
Por
tuga
lS
pain
Geo
rgia
Chi
leJa
pan
Mex
ico
Fran
ceB
razi
lFi
nlan
dC
ypru
sFl
ande
rs (B
elgi
um)
Nor
way
Abu
Dha
bi (U
nite
d A
rab
Em
irate
s)
Icel
and
Alb
erta
(Can
ada)
Aus
tralia
Den
mar
kIs
rael
Kor
eaM
alay
sia
Italy
Uni
ted
Sta
tes
Rom
ania
Bul
garia
Cro
atia
Cze
ch R
epub
licS
lova
kia
Sha
ngha
i (C
hina
)S
erbi
aLa
tvia
Net
herla
nds
Pol
and
Eng
land
(Uni
ted
Kin
gdom
)N
ew Z
eala
ndS
inga
pore
Est
onia
Rus
sia0
2
4
6
8
10
12
14
NetworksAutonomyKnowledge
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.399 Teacher professionalism index across TALIS systems
Disc
uss
indi
vidu
al s
t...
Shar
e re
sour
ces
Team
con
fere
nces
Colla
bora
te fo
r com
m...
Team
teac
hing
Colla
bora
tive
PD
Join
t act
iviti
es
Clas
sroo
m o
bser
vatio
ns
0
10
20
30
40
50
60
70
80
90
100Average Shanghai (China)
Perc
enta
ge o
f te
ache
rs
Professional collaboration
Percentage of lower secondary teachers who report doing the following activities at least once per month
Teacher co-operation10
Exchange and co-ordination
Eng
land
(UK
)
Latv
ia
Mal
aysi
a
Est
onia
Sin
gapo
re
Net
herla
nds
Sha
ngha
i (C
hina
)
Rus
sia
Slo
vak
Rep
ublic
New
Zea
land
Cze
ch R
epub
lic
Bra
zil
Abu
Dha
bi (U
AE
)
Japa
n
Chi
le
Mex
ico
Cro
atia
Uni
ted
Sta
tes
Ave
rage
Rom
ania
Aus
tralia
Geo
rgia
Nor
way
Isra
el
Alb
erta
(Can
ada)
Pol
and
Spa
in
Ser
bia
Icel
and
Kor
ea
Por
tuga
l
Flan
ders
(Bel
gium
)
Italy
Sw
eden
Bul
garia
Den
mar
k
Fran
ce
Finl
and
0
10
20
30
40
50
60
70
80
90
100
School Management Principals Other teachers
Perc
enta
ge o
f tea
cher
sMean mathematics performance, by school location,
after accounting for socio-economic status Fig II.3.31111
Teachers feedback : direct classroom observations
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.31
212 Models of teacher professionalism
High Peer Networks/Low AutonomyHigh AutonomyKnowledge EmphasisBalanced Domains/
High ProfessionalismBalanced Domains/
Low Professionalism
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.31
313 Models of teacher professionalism
High Peer Net-works/
Low AutonomyHigh Autonomy Knowledge Emphasis
Balanced Domains/High Professional-
ism
Balanced Domains/Low Professional-
ism
Impact of teacher
professionalism
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.31
515 Relationship between teacher professionalism and learning
Relationship between PISA 2012 mathematics scores and teacher professionalism index (system-level)
5.0 6.0 7.0 8.0 9.0 10.0 11.0350
400
450
500
550
600
650
Dubai (UAE)
AustraliaFlanders (Belgium)
Bulgaria
Brazil
Alberta (Canada)
Chile
Shaghai (China)
Czech RepublicDenmarkEngland (UK)
Spain
EstoniaFinland
France
Croatia
Iceland
Israel
Italy
Japan
Korea
Latvia
MexicoMalaysia
Netherlands
NorwayNew Zealand
Poland
Portugal
Romania
Russian Federation
Singapore
Serbia
Slovak RepublicSweden
Teacher professionalism index
PISA
mat
hem
atics
scor
e
R = 0.298
Status of the profession
Teachers’ perception of the extent to which teach-ing is valued as a profes-
sion
Satisfaction with the pro-
fession
Teachers’ re-port on the extent to
which teach-ers are happy with their de-cision to be-
come a teacher.
Satisfaction with work en-
vironment
Teachers’ re-port on the extent to
which teach-ers are happy with their cur-rent schools.
Self-efficacy
Teachers’ perception of their capabil-
ities (e.g. controlling disruptive behaviour,
use a variety of assess-
ment strategies,
etc.).
16
1616 Mean mathematics performance, by school location,
after accounting for socio-economic status Fig II.3.31616 Policy-relevant teacher outcomes
0
10
20
30
40
50
60
70
Overall professionalism = 1 Overall professionalism = 5Overall professionalism = 10
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.31
717 Teacher professionalism index and teacher outcomes
The relationship between overall teacher professionalism and teacher outcomes
Perceptions of teachers’ status
Satisfaction with the profession
Satisfaction with the work environment
Teachers’ self-efficacy
Predicted percentile
0
10
20
30
40
50
60
70
80
Knowledge = 0Knowledge = 5
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.31
818 Knowledge base index and teacher outcomes
The relationship between knowledge base and teacher outcomes
Perceptions of teachers’ status
Satisfaction with the profession
Satisfaction with the work environment
Teachers’ self-efficacy
Predicted percentile
0
10
20
30
40
50
60
70
80
Networks = 0Networks = 5
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.31
919 Peer networks index and teacher outcomes
The relationship between peer networks and teacher outcomes
Perceptions of teachers’ status
Satisfaction with the profession
Satisfaction with the work environment
Teachers’ self-efficacy
Predicted percentile
0
10
20
30
40
50
60
70
80
Autonomy = 0Autonomy = 5
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.32
020 Autonomy index and teacher outcomes
The relationship between autonomy and teacher outcomes
Perceptions of teachers’ status
Satisfaction with the profession
Satisfaction with the work environment
Teachers’ self-efficacy
Predicted percentile
Fran
ce
Net
herla
nds
Est
onia
Geo
rgia
Nor
way
Slo
vaki
a
Por
tuga
l
Sw
eden
Japa
n
Alb
erta
(Can
ada)
Italy
Chi
le
Cro
atia
Den
mar
k
Icel
and
Abu
Dha
bi (U
.A.E
.)
Flan
ders
(Bel
gium
)
Sin
gapo
re
Rom
ania
Bra
zil
Ser
bia
Latv
ia
Bul
garia
Isra
el
New
Zea
land
Aus
tralia
Cze
ch R
epub
lic
Finl
and
Spa
in
Mex
ico
Rus
sia
Pol
and
Kor
ea
Sha
ngha
i (C
hina
)
Eng
land
(U.K
.)
Mal
aysi
a0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.32
121 Country differences: Self efficacy
Relationship between overall teacher professionalism and teachers’ self efficacy
Coefficient size
Geo
rgia
Icel
and
Fran
ce
Latv
ia
Slo
vaki
a
Rom
ania
Italy
Japa
n
Finl
and
Nor
way
Est
onia
Bra
zil
Spa
in
Por
tuga
l
Ser
bia
Rus
sia
Sw
eden
Flan
ders
(Bel
gium
)
Den
mar
k
Mal
aysi
a
Mex
ico
Alb
erta
(Can
ada)
Cze
ch R
epub
lic
Cro
atia
Kor
ea
Chi
le
Net
herla
nds
Isra
el
Bul
garia
Pol
and
New
Zea
land
Abu
Dha
bi (U
.A.E
.)
Sin
gapo
re
Aus
tralia
Eng
land
(U.K
.)
Sha
ngha
i (C
hina
)0.00
0.05
0.10
0.15
0.20
0.25
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.32
222 Country differences: Work environment
Relationship between overall teacher professionalism and teachers’ satisfaction with work environment
Coefficient size
Teacher profes-sionalism and
equity
24
2424 Mean mathematics performance, by school location,
after accounting for socio-economic status Fig II.3.32424 Conceptualising high-needs schools
School Low needs Medium needs High needs
Percentage of stu-dents in high needs
group (second-language learners, students with special needs
and students that are so-
cio-economically disadvantaged)
Less than 11% of students
11 to 30% of stu-dents
Greater than 30% of students
25
2525 Mean mathematics performance, by school location,
after accounting for socio-economic status Fig II.3.32525 Socio-economically disadvantaged schools Teacher professionalism support gap and the percentage of schools that fall into the high socio-economi-cally disadvantaged category
-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5
0
10
20
30
40
50
60
70
Australia
Flanders (Beligum) Alberta (Canada)
Chile
Czech RepublicDenmark
Estonia
Finland
France
Iceland
Israel Italy
Japan
Korea
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
England (UK)
Brazil
Bulgaria
Croatia
Georgia
Latvia
Malaysia
Romania
Russian Federation
Serbia
Shanghai (China)
Singapore
Dubai (UAE))
Teacher professionalism support gap - economically disadvantaged
High
conc
entr
ation
- ec
onom
ically
disa
dvan
tage
d
2727 Mean mathematics performance, by school location,
after accounting for socio-economic status Fig II.3.32727
Knowledge domain in high and low socio-economi-cally disadvantaged schools and teacher job satisfac-tion
Nor
way
Abu
Dha
bi (U
AE
)
Isra
el
Net
herla
nds
Eng
land
(UK
)
Bel
gium
(Fla
nder
s)
Alb
erta
(Can
ada)
Italy
Aus
tralia
Ser
bia
Cro
atia
Sha
ngha
i (C
hina
)
Spa
in
Sin
gapo
re
Pol
and
Mal
aysi
a
Slo
vak
Rep
ublic
Mex
ico
Chi
le
Est
onia
Bra
zil
New
Zea
land
Rom
ania
Latv
ia
Por
tuga
l
Fran
ce
Geo
rgia
Japa
n
Sw
eden
Kor
ea
Bul
garia
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
LowHigh
Association between satisfaction with current working environment and knowledge domain for each country sepa-rated by a high and low socio-economically disadvantaged concentration level.
Unst
anda
rdise
d co
efficie
nts
2828 Mean mathematics performance, by school location,
after accounting for socio-economic status Fig II.3.32828
Peer networks domain in high and low socio-economically disadvantaged schools and teacher job satisfaction
Bul
garia
Aus
tralia
Net
herla
nds
Abu
Dha
bi (U
AE
)
Eng
land
(UK
)
New
Zea
land
Ser
bia
Sin
gapo
re
Est
onia
Cro
atia
Chi
le
Sw
eden
Sha
ngha
i (C
hina
)
Nor
way
Bel
gium
(Fla
nder
s)
Mex
ico
Slo
vak
Rep
ublic
Bra
zil
Alb
erta
(Can
ada)
Pol
and
Por
tuga
l
Mal
aysi
a
Italy
Spa
in
Fran
ce
Kor
ea
Latv
ia
Rom
ania
Isra
el
Japa
n
Geo
rgia
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
LowHigh
Association between satisfaction with current working environment and peer networks domain for each country separated by a high and low socio-economically disadvantaged concentration level.
Unst
anda
rdise
d co
efficie
nts
29
2929 Mean mathematics performance, by school location,
after accounting for socio-economic status Fig II.3.32929 Equity in teacher professionalism support
Most Equitable Mixed Equity Least EquitableEngland (United Kingdom) Abu Dhabi (United Arab Emirates) CroatiaKorea Australia EstoniaLatvia Flanders (Belgium) IsraelSpain Brazil MalaysiaSweden Bulgaria Netherlands
Alberta (Canada) PolandChile PortugalCzech Republic SerbiaDenmark Slovak RepublicFinlandFranceGeorgiaIcelandItalyJapanMexicoNew ZealandNorwayRomaniaThe Russian FederationShanghai (China)Singapore
Conclusions
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.33
131 The importance of teacher professionalism
Teachers in schools that adopt more practices re-lated to improving teacher professionalism (espe-cially teachers’ knowledge base and peer net-works) feel:• more satisfied,• more capable (i.e. have higher feelings of self-ef -
ficacy),• that teaching professions has a higher status in
the society.
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.33
232 How can systems support teacher professionalism?
Policies supporting teacher professionalism should con-sider:• requiring teachers to participate in pre-service
formal teacher education programmes that ex-pose teachers to pedagogy and provide opportunit-ies to practice teaching;
• expanding induction and mentoring programs; • supporting teachers in conducting classroom-based
individual or collaborative research;• encouraging teachers’ participation in networks of
other teachers for information exchange.
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.33
333 How can systems support teacher professionalism?
TALIS is a partnership
between
an international research consor-
tiumOECD
Governments in 34 countries
European Commission
Teachers’ unions
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.334
• The report has been prepared by:
Elizabeth Buck-ner
(FHI 360)
Christine Harris-Van Keuren
(Education Policy Insti-tute)
Carina Omoeva(FHI 360)
Under the oversight of OECD Secretariat
William Smith(RESULTS Educational
Fund)
Charles Gale(FHI 360)
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