insights from pisa for schools and local educators

OECD EMPLOYER BRAND

Playbook

1

Insights from PISA for Schools and Lo-cal Educators

Programme for International Student Assessment (PISA)

Alejandro Gomez Palma

Policy Analyst

Organisation for Economic Co-operation and Development (OECD)

Presentation for Local Educators from the USA

1 April 2014

2 PISA in brief

• Over half a million students…– representing 28 million 15-year-olds in 65 countries/economies

… took an internationally agreed 2-hour test…– Goes beyond testing whether students can

reproduce what they were taught…… to assess students’ capacity to extrapolate from what they know

and creatively apply their knowledge in novel situations– Mathematics, reading, science, problem solving, financial literacy– Total of 390 minutes of assessment material

… and responded to questions on…– their personal background, their schools

and their engagement with learning and school• Parents, principals and system leaders provided data on…

– school policies, practices, resources and institutional factors that help explain performance differences .

http://youtu.be/WdE4vISrz2o

3 PISA 2012 in brief

• Key principles– ‘Crowd sourcing’ and collaboration

• PISA draws together leading expertise and institutions from participating countries to develop instruments and methodologies…

… guided by governments on the basis of shared policy interests

– Cross-national relevance and transferability of policy experiences

• Emphasis on validity across cultures, languages and systems• Frameworks built on well-structured conceptual understanding

of academic disciplines and contextual factors

– Triangulation across different stakeholder perspectives• Systematic integration of insights from students, parents,

school principals and system-leaders

– Advanced methods with different grain sizes• A range of methods to adequately measure constructs with different grain sizes to

serve different decision-making needs – e.g. PISA for Schools• Productive feedback to fuel improvement at every level of the system .

Math teaching and learning ≠ math teaching and learning

PISA = reason mathematically and understand, formulate, employand interpret mathematical concepts, facts and procedures (not curriculum-

based but content is important)

4

5

The real world The world of mathematics

A real situation

Mathematical model

Results of the mathematical

procedure

Real results

Understanding the situation, structuring and simplifying it

Transforming the problem to be dealt with mathematics

Interpreting the mathematical results

Employing mathematical tools to solve a problem

Validating the results

PISA = competencies, skills and content = reason mathematically and use mathematical concepts, procedures, facts and tools

A model from reality

6

Climbing Mount Fuji

Mount Fuji is a famous dormant volcano in Japan.

Mount Fuji is only open to the public for climbing from 1 July to 27 August each year. About 200 000 people climb Mount Fuji during this time.

On average, about how many people climb Mount Fuji each day?

A. 340 (answer code: pisa1a)

B. 710 (answer code: pisa1b)

C. 3400 (answer code: pisa1c)

D. 7100 (answer code: pisa1d)

E. 7400 (answer code: pisa1e)

PISA 2012 Sample Question

7

Climbing Mount FujiCorrect Answer: C. 3400

This item belongs to the quantity category. The notion of quantity may be the most pervasive and essential mathematical aspect of engaging with, and functioning in, our world. It incorporates the quantification of attributes of objects, relationships, situations and entities in the world, understanding various representations of those quantifications, and judging interpretations and arguments based on quantity.

SCORING:

Description: Identify an average daily rate given a total number and a specific time period (dates provided)

Mathematical content area:

Quantity

Context: Societal

Process: Formulate

PISA 2012 Sample Question 1

9

Helen the CyclistHelen has just got a new bike. It has a speedometer which sits on the handlebar. The speedometer can tell Helen the distance she travels and her average speed for a trip.

Helen rode 6 km to her aunt’s house. Her speedometer showed that she had averaged 18 km/h for the whole trip.

Which one of the following statements is correct?

A. It took Helen 20 minutes to get to her aunt’s house. (answer code: pisa2a)

B. It took Helen 30 minutes to get to her aunt’s house. (answer code: pisa2b)

C. It took Helen 3 hours to get to her aunt’s house. (answer code: pisa2c)

D. It is not possible to tell how long it took Helen to get to her aunt’s house. (answer code: pisa2d)


10

Correct Answer: A. It took Helen 20 minutes to get to her aunt’s house.

This item belongs to the change and relationships category. This involves understanding fundamental types of change and recognising when they occur in order to use suitable mathematical models to describe and predict change.

SCORING:

Description: Calculate time travelled given average speed and distance travelled

Mathematical content area:

Change and relationships

Context: Personal

Process: Employ

Helen the Cyclist


11

Percent of 15-year-olds who scored Level 3 or Above

0

10

20

30

40

50

60

70

80

90

100

Serie

s1

OECD average

United States


410

420

430

440

450

460

470

480

490

500

510

520

530

540

550

560

570

580Mean score

High mathematics performance

Low mathematics performance

… Shanghai-China performs above this line (613)

… 12 countries perform below this line

Average performanceof 15-year-olds in

MathematicsFig I.2.13

US

Massachusetts

Connecticut

Florida

26% of American 15-year-olds do not reach PISA Level 2

(OECD average 23%, Shanghai 4%, Japan 11%, Canada 14%, Some estimate

long-term economic cost to be US$72 trillion )

Socially equitable distribution of learning

opportunities

High mathematics performance

Low mathematics performance

Average performanceof 15-year-olds in

mathematics

Strong socio-economic impact on student

performance

02468101214161820222426

AustraliaAustria

Belgium Canada

Chile

Czech Rep.

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

IcelandIreland

Israel

Italy

Japan

Korea

Luxembourg

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Slovenia

Spain Sweden

Switzerland

Turkey

UK

US

Singapore

Hong Kong-ChinaChinese Taipei

Macao-China

Liechtenstein

Viet Nam

Latvia

Russian Fed.Lithuania

Croatia

SerbiaRomania

Bulgaria United Arab Emirates

KazakhstanThailand

Malaysia

2012Shanghai-China


opportunities


performance

AustraliaAustria

Belgium Canada

Chile

Czech Rep.

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

IcelandIreland

Israel

Italy

Japan

Korea

Luxembourg

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Slovenia

Spain Sweden

Switzerland

Turkey

UK

US

AustraliaAustriaBelgiumCanadaChileCzech Rep.DenmarkEstoniaFinlandFranceGermanyGreeceHungaryIcelandIrelandIsraelItalyJapanKoreaLuxembourgMexicoNetherlandsNew ZealandNorwayPolandPortugalSlovak Rep.SloveniaSpainSwedenSwitzerlandTurkeyUKUS

2012


opportunities


performance

AustraliaAustria

Belgium Canada

Chile

Czech Rep.

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

IcelandIreland

Israel

Italy

Japan

Korea

Luxembourg

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Slovenia

Spain Sweden

Switzerland

Turkey

UK

US


AustraliaAustria

Belgium Canada

Chile

Czech Rep.

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

IcelandIreland

Israel

Italy

Japan

Korea

Luxembourg

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Slovenia

Spain Sweden

Switzerland

Turkey

UK

US


Singapore

Shanghai

Singapore

2003 - 2012 Germany, Turkey and Mexico improved both their mathematics performance and equity levels

AustraliaAustria

Belgium Canada

Chile

Czech Rep.

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

IcelandIreland

Israel

Italy

Japan

Korea

Luxembourg

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Slovenia

Spain Sweden

Switzerland

Turkey

UK

US


Singapore


Germany, Turkey and

Mexico saw significant

improvements in both

math performance and

equity between 2003

and 2012

AustraliaAustria

Belgium Canada

Chile

Czech Rep.

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

IcelandIreland

Israel

Italy

Japan

Korea

Luxembourg

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Slovenia

Spain Sweden

Switzerland

Turkey

UK

US


Singapore


Brazil, Italy, Macao-China, Poland, Portugal,

Russian Federation, Thailand and Tunisia

saw significant improvements in math performance between

2003 and 2012(adding countries with more recent trends results in 25 countries with

improvements in math)

AustraliaAustria

Belgium Canada

Chile

Czech Rep.

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

IcelandIreland

Israel

Italy

Japan

Korea

Luxembourg

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Slovenia

Spain Sweden

Switzerland

Turkey

UK

US


Singapore


Norway, the United States and Switzerland improved equity between 2003 and 2012

Of the 65 countries… …45 improved in at least one subject

22

23

Mathematics, reading and science Israel, Poland, Portugal, Turkey, Brazil, Dubai (UAE), Hong Kong-China, Macao-China, Qatar, Singapore, Tunisia

Mathematics and readingChile, Germany, Mexico, Albania, Montenegro, Serbia, Shanghai-China

Mathematics and scienceItaly, Kazakhstan, Romania

Reading and scienceJapan, Korea, Latvia, Thailand

Mathematics onlyGreece, Bulgaria, Malaysia, United Arab Emirates (ex. Dubai)

Reading only Estonia, Hungary, Luxembourg, Switzerland, Colombia, Indonesia, Liechtenstein, Peru, Russian Federation, Chinese Taipei

Science onlyIreland

Improvement in mathematics, reading or science

24

Shang

hai-C

hina

Hong

Kong-

China

Viet N

amKor

ea

Liec

hten

stein

Switzer

land

Nethe

rland

s

Belgi

um

Canad

a

Austri

a

New Z

eala

nd

Franc

e

Irela

nd

OECD ave

rage

Slova

k Rep

ublic

Hunga

ryIta

ly

Unite

d Kin

gdom

Lith

uani

a

Unite

d Sta

tes

Sweden

Roman

ia

Serbi

a

Greec

eChi

le

Mal

aysia

Cypru

s5, 6

Costa

Rica

Brazil

Tunisi

aPer

u

Colom

biaQat

ar340

360

380

400

420

440

460

480

500

520

540

560

580

600

Mean score at the country level before adjusting for socio-economic statusMean score at the country level after adjusting for socio economic status

Me

an

ma

the

ma

tic

s s

co

reMathematics performance in a level playing fieldMean mathematics performance after accounting for socio-economic status

Fig II.3.3

25

Shang

hai-C

hina

Mac

ao-C

hina

Singa

pore

Chine

se T

aipe

i

Liec

hten

stein

Estoni

a

Polan

d

Finl

and

Portu

gal

Turk

ey Italy

Latvi

a

Austra

lia

Austri

a

Czech

Rep

ublic

Unite

d Kin

gdom

Fran

ce

Icela

nd

Russia

n Fe

d.

Croat

ia

Sweden

Slova

k Rep

ublic

Serbi

aIsr

ael

Roman

ia

Indo

nesia

Kazak

hsta

n

Brazil

Chile

Mon

tene

gro

Argen

tina

Peru

0

2

4

6

8

10

12

14

16

18

20

%

Percentage of resilient students

More than 10% resilient Between 5%-10% of resilient students Less than 5%

Fig II.2.4

A resilient student is situated in the bottom quarter of the PISA index of economic, social and cultural status (ESCS) in their own country and yetperforms in the top quarter of students among all countries, after accounting for socio-economic status.

Socio-economically disadvantaged students not only score lower in mathematics, they also report lower levels of engagement, drive, motivation and self-beliefs. Resilient students break this link and share many characteristics of advantaged high-achievers.

Comparisons of performance Table I.2.3b

Peru 22 years vs Indonesia 45 years

Qatar 13 years vs Tunisia 35 years

Brazil 42 years vs Kazakhstan 9 years

2003

2007

2011

2015

2019

2023

2027

2031

2035

2039

2043

2047

0

100

200

300

400

500

600

700

800

Catching up to the OECD Average in Mathematics

QatarTunisiaOECD

Mean

Perf

orm

an

ce in

Ma-

them

ati

cs

2006

2009

2012

2015

2018

2021

2024

2027

2030

2033

2036

2039

2042

2045

2048

2051

2054

0

100

200

300

400

500

600

700

800

900Catching up to the OECD Average in

Science

BrazilKaza-khstanOECD

Mean

Perf

orm

an

ce in

Scie

nce

2000

2004

2008

2012

2016

2020

2024

2028

2032

2036

2040

2044

2048

2052

2056

0

100

200

300

400

500

600

700Catching up to the OECD Average in Reading

Peru

Indonesia

OECD

Mean

Perf

orm

an

ce in

Read

ing

26

Stu

dent

perf

orm

ance

AdvantagePISA Index of socio-economic back-ground

Disadvantage

700

-3 -2 -1 0 1 2 3200

493

School performance and socio-economic background: United States27

Student performance and students’ socio-economic background

School performance and schools’ socio-economic background

Private school Public school in rural area Public school in urban area

Student performance and students’ socio-economic background within schoolsSchools with similiar socio-economic backgrounds

28

-3 -2 -1 0 1 2 3200

494

School performance and socio-economic background: Viet Nam

AdvantagePISA Index of socio-economic backgroundDisadvantage

Student performance and students’ socio-economic background

School performance and schools’ socio-economic background

Private school Public school in rural area Public school in urban area

Student performance and students’ socio-economic background within schools

Stu

dent

per

form

ance

700

Pe

ru

Me

xico

Ind

on

esi

a

Co

lom

bia

Tu

rke

y

Un

ited

Sta

tes

Au

stra

lia

Vie

t Na

m

Sh

an

gh

ai-

Ch

ina

Ro

ma

nia

Isra

el

Ch

ine

se T

aip

ei

Ire

lan

d

Tu

nis

ia

Ca

na

da

Ma

cao

-Ch

ina

Lu

xem

bo

urg

Ru

ssia

n F

ed

.

Be

lgiu

m

Sw

itze

rla

nd

Ho

ng

Ko

ng

-Ch

ina

Lith

ua

nia

Ka

zakh

sta

n

Cze

ch R

ep

ub

lic

Est

on

ia

Slo

ven

ia

Sin

ga

po

re

Slo

vak

Re

pu

blic

Ko

rea

Se

rbia

No

rwa

y

Fin

lan

d

Alb

an

ia

-2.00

-1.50

-1.00

-0.50

0.00

0.50

Difference between socio-economically disadvantaged and socio-economically advantaged schools

Me

an

ind

ex

dif

fere

nc

eEducational resources are more problematic in disadvantaged schools, also in public schools in most countries

Advantaged and private schools reported better educational resources

Disadvantaged and public schools reported better educational resources

Fig IV.3.829

30H

on

g K

on

g-C

hin

a

Ko

rea

+L

iech

ten

ste

in

Ma

cao

-Ch

ina

+Ja

pa

n

Sw

itze

rla

nd

B

elg

ium

-N

eth

erl

an

ds

-G

erm

an

y

Po

lan

d +

Ca

na

da

-F

inla

nd

-N

ew

Ze

ala

nd

-A

ust

ralia

-A

ust

ria

O

EC

D a

vera

ge

20

03

-F

ran

ce

Cze

ch R

ep

ub

lic -

Lu

xem

bo

urg

Ic

ela

nd

-S

lova

k R

ep

ub

lic

Ire

lan

d

Po

rtu

ga

l +

De

nm

ark

-Ita

ly +

No

rwa

y -

Hu

ng

ary

U

nite

d S

tate

s

Sw

ed

en

-S

pa

in

La

tvia

R

uss

ian

Fe

de

ratio

n

Tu

rke

y

Gre

ece

T

ha

ilan

d

Uru

gu

ay

-T

un

isia

B

razi

l M

exi

co

Ind

on

esi

a 0

10

20

30

40

2012 2003%

Percentage of top performers in mathematics in 2003 and 2012

Fig I.2.23

Across OECD, 13% of students are top performers (Level 5 or 6). They can develop and work with models for complex situations, and work strategically with advanced thinking and reasoning skills

31 Gender differences in reading performance

Jord

an

Bulga

ria

Finla

nd

U.A.E

.

Thaila

nd

Sweden

Greec

e

Norway

Turke

yIsr

ael

Estoni

a

Roman

ia

Russia

n Fed

.

Slova

k Rep

ublic

Italy

Argen

tina

Austri

a

Switzer

land

Urugu

ay

Austra

lia

Chine

se T

aipe

i

Belgi

um

Unite

d Sta

tes

Tunisi

a

Luxe

mbo

urg

Irela

nd

Nethe

rland

s

Costa

Rica

Liec

hten

stein

Shang

hai-C

hina

Korea

Peru

Alban

ia-80

-70

-60

-50

-40

-30

-20

-10

0

Sc

ore

-po

int

dif

fere

nc

e (

bo

ys

-gir

ls)

In all countries and economies girls perform better than boys

Fig I.4.12

The share of immigrant students in OECD countries increased from 9% in 2003 to 12% in 2012…

…while the performance disadvantage of immigrant students shrank by 11 score points during the same period (after accounting for socio-

economic factors)

32

33

Hu

ng

ary

-

Au

stra

lia -

Ma

cao

-Ch

ina

Slo

vak

Re

pu

blic

-

Tu

rke

y

Ne

w Z

ea

lan

d -

Ire

lan

d

Ca

na

da

La

tvia

Ho

ng

Ko

ng

-Ch

ina

Un

ited

Kin

gd

om

Un

ited

Sta

tes

Th

aila

nd

Ru

ssia

n F

ed

era

tion

Cze

ch R

ep

ub

lic

OE

CD

ave

rag

e 2

00

3 -

Lu

xem

bo

urg

Po

rtu

ga

l

No

rwa

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Italy

+

Lie

chte

nst

ein

Gre

ece

Ice

lan

d

Sp

ain

Ge

rma

ny

-

Bra

zil

Ne

the

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s

Sw

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en

Au

stri

a

Be

lgiu

m -

Sw

itze

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nd

-

De

nm

ark

Fra

nce

Me

xico

Fin

lan

d

-40

-20

0

20

40

60

80

100

2012 2003

Sc

ore

po

int

dif

fere

nc

e (

wit

ho

ut-

wit

h im

mig

.)

Students without an immigrant background perform better

Students with an immigrant background perform better

Change between 2003 and 2012 in immigrant students' mathematics

performance – before accounting for students’ socio-economic statusFig II.3.5

Japa

n

Luxe

mbo

urg

Czech

Rep

ublic

Korea

Thaila

nd

Denm

ark

Italy

Mac

ao-C

hina

Belgi

um

Portu

gal

Spain

Switzer

land

Unite

d Sta

tes

Slova

k Rep

ublic

Russia

n Fed

erat

ion

Irela

nd

Austra

lia

Sweden

Franc

e

Germ

any

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

Change between 2003 and 2012 in disciplinary climate in schools

Me

an

ind

ex

ch

an

ge

In most countries and economies, the disciplinary climate in schools improved between 2003 and 2012

Disciplinary climate declined

Disciplinary climateimproved

Fig IV.5.13

35 Motivation to learn mathematics

Percentage of students who reported "agree" or "strongly agree" with the following statements:

I enjoy reading about mathematics

I look forward to my mathematics lessons

I do mathematics because I enjoy it

I am interested in the things I learn in mathematics

0 10 20 30 40 50 60 70

United States Shanghai-China

%

Fig III.3.9

36

-0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20300

350

400

450

500

550

600

650

481.366786279212

517.501096817955

561.241096454551

391.459888954175

499.749902827587

452.973426858907

409.291567937716

493.934230896316

520.545521676786518.750335282979

394.329333356314

471.131460759248

490.571021411359

481.644744006327489.845098037208

513.525055819928

478.823277433358

505.540743249801

498.95788231768

559.824796201498

494.98467432064426.737491293011

536.406918234208

447.984414978954 478.260635903011

477.044455015488504.150766311124

466.48143014931

518.078519433354

501.497460196644438.738259877415

385.595556395556

422.632355405519

538.134494733918

U.A.E.

514.745238582901522.971758192682

484.319297801971

388.431709907139

375.114451681749

500.026756625414

431.798408505078

368.102547127357

406.999866988793

530.931003950397

409.626613284347

387.824629620249

492.795697239492

501.127422390953

376.4483986347

573.468314296641

487.063181343903

489.373070348755

376.488601072821

420.512967619054

413.281466667708

534.96508297892

553.766659143613

448.859130247604

Russian Fed.

444.554242787643

511.338207501182

485.321181012553

612.675536305453

f(x) = 138.160916953927 x + 477.587612682211R² = 0.368631715648504

Mean index of mathematics self-efficacy

Me

an

ma

the

ma

tic

s p

erf

orm

an

ce

OE

CD

av

era

ge

Countries where students have stronger beliefsin their abilities perform better in mathematics

Fig III.4.5

Schools with more autonomy perform better than schools with less autonomy in systems with more accountability arrangements

Less school autonomy

More school autonomy

464

466

468

470

472

474

476

478

School data not public

School data public

Score points

School autonomy for curriculum and assessment x system's level of posting achievement data publicly

Fig IV.1.1637

Less school autonomy

More school autonomy

455

460

465

470

475

480

485

No mathematics standards

Central mathematics standards

Schools with more autonomy perform better than schools with less autonomy in systems with more accountability arrangements

Score points

School autonomy for curriculum and assessment x System's extent of implementing a standardised policy

Fig IV.1.16

39

Attract• Attract the best students to the teaching

profession (Examples: Brazil, Korea, Israel, United Kingdom)

• Create incentives to encourage experienced teachers to work in disadvantaged schools (Examples: Brazil, Estonia, Shanghai)

Train• Provide quality training that combines

acquiring knowledge and skills (Examples: Finland, Japan, Turkey)

• Prepare teachers to address specific problems of students, assess and use appropriate remedial methods (E-xamples: Germany, Poland, Canada)

Accompany• Provide mentoring programs for young

teachers (Examples: Germany, Singapore)• Give young teachers the opportunity early in

their career to return to university and improve their skills (Examples: Finland, Germany)

Retain• Develop continuous professional deve-

lopment, which is as important, if not more than initial training (Examples: Brazil, Canada, Mexico, Singapore)

• Provide career advancement opportu-nities (Examples: Quebec, Portugal)

Summary of insights regarding teachers from countries with high per-formance and equity in PISA:

Provides information on the competencies, knowledge, skills and engagement of students, and the learning environment at the school comparable to PISA scales

Tool in support of research and the benchmarking efforts for improvement

Can be used by schools, networks of schools and districts

…To support local improvement

OECD Test for Schools (based on PISA)Uses of the assessment tool

Is not…

• A mandated standardised test

• Intended to influence – in of itself – everyday teaching practices

• An alternative to national, regional PISA participation

• Intended to align completely with the content and curricular standards of a specific country, although there is overlap

• A tool for “rankings” or “league tables”

OECD Test for Schools (based on PISA)Uses of the assessment tool

OECD Test for Schools (based on PISA)What does the actual assessment look like?

Experience for students similar to that of the main PISA tests: ~ 3.25 hours (with breaks and student questionnaire)

Three areas (domains) equally represented (over 90 minutes of assessment items)

Student sample size per school (target): 75 (some schools tested over 100 students)

Contextual information questionnaires for students and school authorities

Paper and pencil for first phase…

Content of school reports provided

I. Introduction: Understanding your school’s results

II. What students at Your School Know and Can Do in Reading, Mathematics and Science

III. Student Engagement and the Learning Environment at Your School

IV. Your School Compared with Similar Schools in Your Country

V. Your School’s Results in an International Context

Annexes School nameSchool DistrictStateUnited States

How your school compares internationallyOECD Test for SchoolsPilot Trial 2012

OECD Test for Schools (based on PISA)Overview of school reports

School-specific results provided

Performance on PISA scales

Relative performance based on background of students (socio-economic status - ESCS)

Learning environment at school

OECD Test for Schools (based on PISA)Overview of school reports

• Teacher-student relations

• Disciplinary climate in English and Mathematics lessons

• Student confidence and attitudes towards mathematics and science

http://youtu.be/tnhLrGM81eI?t=1m58s



Per

form

ance

on

PIS

A s

cale

OECD Test for Schools (based on PISA)Overview of results (from the pilot)

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Schools in theUnited States

Schools in theShanghai-China

Schools in Mexico

PISA 2009 Results

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North Star Academy

Pilot Results

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Reading

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Woodson HS

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BASIS Scottsdale

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Langley High School

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Oakton High School

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BASIS Tucson

OECD Test for Schools (based on PISA)Overview of results (from the pilot)

What does the same mean mean?

Brazil

United States

United Kingdom

Poland

Japan

Korea

Shanghai-China

Oakton High School

0%20%40%60%80%100%

Brazil

Mexico

United States

OECD average

United Kingdom

Germany

Poland

Singapore

Japan

Canada

Korea

Finland

Shanghai-China

Langley High school

Oakton High School

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543 and 543

Reading

Level 1 and be`low Level 2 Level 3 Level 4 Level 5 Level 6

OECD Test for SchoolsSchool Reports

Disciplinary climate and reading performancce


Disciplinary climate and reading performancce



Disciplinary climate and mathematics lessons

Quality of teacher-student relations

http://youtu.be/1MzGhxJ5HOg?t=3m17s



Performance and teacher-student relations

Motivation of students to learn science

Self-belief of students in science

Instrumental motivation and self-efficacy of students and performance at your school

OECD Test for SchoolsSchool Reports

http://pearsonfoundation.org/oecd/china.html

Performance needs to be considered not in absolute terms but in terms of equity and relative effectiveness of schools

International benchmarking supported by the assessment is a process – the “real work” begins after receiving the results…

Performance should also be considered in the context of the quality of the learning environment at schools

Importance of peer-to-peer learning opportunities –– and the opportunity to share good practices to help identify “what works”

OECD Test for Schools (based on PISA)What now? Current cycle of testing in the USA

America Achieves – key partners in the USA

EdLeader21 – key partners in the USA

CTB/McGraw-Hill – currently accredited service provider

Spain has finished pilot in four official languages (224 schools)

In UK: England, Wales and Norther Ireland

International Learning Network – Australia….

OECD Test for Schools (based on PISA)Availability in the United States and Internationally

OECD EMPLOYER BRAND

Playbook

58

PISA Insights for Schools and Local Educators

Thank you very much

www.pisa.oecd.org • All national and international

publications

• The complete micro-level database

• Documents and Presentations of PISA for Development

http://www.pisa.oecd.org/

insights from pisa for schools and local educators

Technology