programme for international student assessment - pisa organisation for economic cooperation and...
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Programme for Programme for International Student International Student
Assessment - PISAAssessment - PISA
Organisation for Economic Cooperation and Organisation for Economic Cooperation and Development (OECD)Development (OECD)
22 Origins of PISAOrigins of PISA
OECD work on education statistics OECD work on education statistics and indicatorsand indicators major development commenced in major development commenced in
late 1980slate 1980s Network on educational outcomesNetwork on educational outcomes
Council decision in 1997Council decision in 1997
3333
OECD Partner countries (4)
OECD countries (28)
PISA 2000 country participation
4444
OECD Partner countries (11)
OECD countries (30)
PISA 2003 country participation
5555
OECD Partner countries (28)
OECD countries (30)
PISA 2006 country participation
66
Making international comparisons of Making international comparisons of achievement requires decisions achievement requires decisions
about...about...
what to assess,what to assess,
whom to assess.whom to assess.
77Deciding what to assess...Deciding what to assess...
looking back at what they were looking back at what they were expected to have learnedexpected to have learned
OROR
looking ahead to what they can do looking ahead to what they can do with what they have learned.with what they have learned.
For PISA, the OECD countries chose the latter.For PISA, the OECD countries chose the latter.
88PISA assessmentsPISA assessments
Reading literacyReading literacy Using, interpreting and reflecting on written Using, interpreting and reflecting on written
material.material. Mathematical literacyMathematical literacy
Recognising problems that can be solved Recognising problems that can be solved mathematically, representing them mathematically, representing them mathematically, solving them.mathematically, solving them.
Scientific literacyScientific literacy Identifying scientific questions, recognising Identifying scientific questions, recognising
what counts as scientific evidence, using what counts as scientific evidence, using evidence to draw conclusions about the natural evidence to draw conclusions about the natural world.world.
99
Development of the PISA tests
1010 Development of assessments Frameworks by international experts Assessment materials
submitted by countries developed by research consortium screened for cultural bias translated into English & French originals trialled to check items working consistently in all
countries Final tests
items shown in trial to be culturally biased removed best items chosen for final tests
– balanced to reflect framework– range of difficulties– range of item types
1111
Measuring mathematical literacy inPISA 2003
1212 Mathematical literacy in PISAThe real world The mathematical World
A real situation
A model of reality A mathematical model
Mathematical results
Real results
Understanding, structuring and simplifying the situation
Making the problem amenable to mathematical
treatment
Interpreting the mathematical results
Using relevant mathematical tools to solve the problemValidating
the results
1313 Mathematical literacy in PISAMathematical literacy in PISA The capacity to:The capacity to:
identify, understand and engage in mathematics;identify, understand and engage in mathematics; make well-founded judgements about the role that make well-founded judgements about the role that
mathematics plays in an individual’s current and mathematics plays in an individual’s current and future:future:– private lifeprivate life– occupational lifeoccupational life– social life with peers and relativessocial life with peers and relatives– life as a constructive, concerned and reflective citizen.life as a constructive, concerned and reflective citizen.
Seen as depending on…Seen as depending on… mathematical knowledge and skills,mathematical knowledge and skills, ability to think and work mathematically,ability to think and work mathematically, ability to apply the knowledge in a wide variety of ability to apply the knowledge in a wide variety of
contexts.contexts.
1414 Measuring mathematical literacy in Measuring mathematical literacy in PISA 2003PISA 2003
Content Content Space and shapeSpace and shape Change and relationships QuantityChange and relationships Quantity UncertaintyUncertainty
Process skills Process skills Reproduction: use of practised knowledge, routine Reproduction: use of practised knowledge, routine
procedures…procedures… Connections: somewhat familiar but not routine…Connections: somewhat familiar but not routine… Reflection: insight, creativity in choosing mathematical Reflection: insight, creativity in choosing mathematical
concepts…concepts…
1515Deciding whom to assess...
grade-based sample
OR
age-based sample
For PISA, the OECD countries chose the latter, selecting 15-year-olds in school as the population.
1616 PISA sampling requirements
Population: all 15-year-olds in school Sample
minimum of 150 schools per country two random samples: schools and replacement
schools if school declines, replacement school is invited stringent requirements set by countries (85% of
selected schools, 80% of selected students within schools)
1717 Key features of PISA 2003 assessment Information collected
each student
– 2 hours on paper-and-pencil tasks (subset of all questions)
– ½ hour for questionnaire on background, learning habits, learning environment, engagement and motivation
school principals
– questionnaire (school demography, learning environment quality)
Sample 275,000 students 41 participating countries
1818
Results from PISA 2003
1919 PISA provides five key benchmarks for the quality of education systems
1. Overall performance of education systems
2. Equity in the distribution of learning opportunities
3. Consistency of performance standards across schools
4. Gender differences
5. Foundations for lifelong learning
2020300 350 400 450 500 550 600
FinlandKorea
NetherlandsJ apan
CanadaBelgium
SwitzerlandAustralia
New ZealandCzech Rep.
I celandDenmark
FranceSwedenAustria
GermanyI reland
Slovak Rep.NorwayPoland
HungarySpainUSA
PortugalI taly
GreeceTurkeyMexico
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 2.5c, p.356.
Mean mathematics scores – selected countries
2121OECD
Level 6
Level 5
Level 4
Level 3
Level 2
Level 1
BelowLevel 1
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 2.5a, p.354.
What students can do in mathematics
15%
21%
22%
18%
10%
4%
11%
2222
0%
20%
40%
60%
80%
100%
Fin
land
Kor
ea
Can
ada
Net
her
land
s
Jap
an
Sw
itze
rlan
d
Bel
gium
Aus
tral
ia
New
Zea
land
Icel
and
Den
mar
k
Cze
ch R
epub
lic
Fra
nce
Sw
eden
Aus
tria
Irel
and
Ger
man
y
Slo
vak
Rep
ublic
Nor
way
Hun
gary
Pola
nd
Spa
in
Uni
ted S
tate
s
Ital
y
Port
ugal
Gre
ece
Percentage of students at each of the proficiency levels on the mathematics
scale
Level 3
Level 1
Below Level 1
Level 6
Level 5
Level 4
Level 2
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 2.5a, p.354.
2323 What students can do in reading
10%
22%
12%
6%
22%
29%
OECD Average
Level 5
Level 4
Level 3
Level 2
Level 1
Below Level 1
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 6.1, p.443.
2424
0%
20%
40%
60%
80%
100%
Fin
land
Kor
ea
Can
ada
Aus
tral
ia
Irel
and
New
Zea
land
Sw
eden
Net
her
land
s
Bel
gium
Sw
itze
rlan
d
Nor
way
Jap
an
Fra
nce
Pola
nd
Den
mar
k
Uni
ted S
tate
s
Ger
man
y
Icel
and
Aus
tria
Cze
ch R
epub
lic
Spa
in
Hun
gary
Port
ugal
Ital
y
Gre
ece
Slo
vak
Rep
ublic
Tur
key
Mex
ico
Percentage of students at each of the proficiency levels in reading
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 6.1, p.443.
2525 Performance in all domains
350
400
450
500
550
600
Hong Kong
FinlandKorea
NetherlandsJ apan
CanadaBelgium
MacaoSwitzerland
AustraliaNew
ZealandCzech Rep.
I celand
DenmarkFrance
SwedenAustria
Germany
I relandSlovak Rep.
NorwayLuxembourg
PolandHungary
SpainUnited
StatesPortugal
I taly
GreeceTurkey
Mexico
Mathematics
350
400
450
500
550
600
350
400
450
500
550
600
Reading
350
400
450
500
550
600
Science Problem Solving
26262626
Securing an equitable distribution of learning opportunities
Measured by the impact students’ and schools’ socio-economic background has on performance – not merely by the distribution
of learning outcomes
2727
-3 -1 1 3-3 -2 -1 0 1 2 3
HighStu
dent
perf
orm
ance
Social background and student performance
AdvantagePISA Index of social backgroundDisadvantage
Low
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Figure 4.8, p.176.
On average, there is a 45 On average, there is a 45 point change in point change in mathematics score for a mathematics score for a one standard deviation one standard deviation change in social change in social backgroundbackground
2828Stu
dent
perf
orm
ance
School performance and schools’ socio-economic background - Sweden
AdvantagePISA Index of social backgroundDisadvantage
Figure 4.13
300
500
700
-3 -2 -1 0 1 2 3
School proportional to size
Student performance and student SES
2929
Low Performance
High performance
Low performance
Low social equity
High performance
Low social equity
High performance
High social equity
Strong impact of social background
Moderate impact of social background
Greece
Russian Federation
Liechtenstein
Korea
Hong Kong- China
Finland
Netherlands
Canada
Macao- ChinaSwitzerland
New Zealand
Belgium
J apan
Australia
I celandCzech Republic
SwedenFrance
Denmark
I relandGermanyAustria
Slovak Republic
LuxembourgPolandHungary
Norway
SpainUnited States Latvia
Portugal I taly
440
460
480
500
520
540
0102030
Low
performance
High social equity
3030
350
400
450
500
550
600
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000
Student performance and spending per student
Mexico
Greece
Portugal Italy
Spain
GermanyAustria
Ireland
United States
Norway
Korea
Czech republic
Slovak republicPoland
Hungary
Finland
NetherlandsCanada Switzerland
IcelandDenmark
FranceSweden
BelgiumAustralia
Japan
R2 = 0.28
Cumulative expenditure (US$)
Perf
orm
an
ce in
math
em
ati
cs
Spending per student is positively associated with average student performance…
…but not a guarantee for high outcomes Australia, Belgium, Canada, the Czech Republic,
Finland, Japan, Korea and the Netherlands do well in terms of “value for money”…
…while some of the big spenders perform below-average
31313131
Ensuring consistent performance standards across schools
Between and within-school variation in performance
3232
0
20
40
60
80
100
120
140
Tur
key
Hun
gary
Jap
an
Bel
gium
Ital
y
Ger
man
y
Aus
tria
Net
herl
ands
Cze
ch R
epub
lic
Kor
ea
Slo
vak
Rep
ublic
Gre
ece
Swit
zerl
and
Luxe
mbou
rg
Port
ugal
Mex
ico
Uni
ted
Sta
tes
Aus
tral
ia
New
Zea
land
Spa
in
Can
ada
Irel
and
Den
mar
k
Pola
nd
Swed
en
Nor
way
Fin
land
Icel
and
Is it all innate ability?Variation in student performance
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 4.1a, p.383.
3333
- 80
- 60
- 40
- 20
0
20
40
60
80
100Tur
key
Hun
gary
Jap
an
Bel
gium
Ital
y
Ger
man
y
Aus
tria
Net
herl
ands
Cze
ch R
epub
lic
Kor
ea
Slo
vak
Rep
ublic
Gre
ece
Swit
zerl
and
Luxe
mbou
rg
Port
ugal
Mex
ico
Uni
ted
Sta
tes
Aus
tral
ia
New
Zea
land
Spa
in
Can
ada
Irel
and
Den
mar
k
Pola
nd
Swed
en
Nor
way
Fin
land
Icel
and
Variation of performance
between schools
Variation of performance within
schools
Is it all innate ability?Variation in student performance in mathematics
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 4.1a, p.383.
34343434
Bridging the gender gap
Performance, attitudes and motivation
3535Gender differences
In reading, girls are far ahead In all countries, girls significantly
outperform boys in reading
In mathematics, boys tend to be somewhat ahead in most countries
… However …
3636
-60 -40 -20 0 20 40
I celandThailandSerbiaLatviaI ndonesiaHong Kong-ChinaNetherlandsAustraliaPolandNorwayUnited StatesSwedenFinlandBelgiumAustriaHungaryJ apanFranceSpainGermanyRussian FederationMexicoCanadaUruguayTunisiaPortugalNew ZealandI relandCzech RepublicTurkeyBrazilDenmarkSwitzerlandLuxembourgI talySlovak RepublicGreeceMacao-ChinaKoreaLiechtenstein
Performance in mathematics
Females perform better
Males perform better
-60 -40 -20 0 20 40Performance in reading
Females perform better
Males perform better
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Tables 2.5c, 6.3, pp.356, 445.
Gender differences
3737Governance of the school system
In many of the best performing countries Decentralised decision-making is
combined with devices to ensure a fair distribution of substantive educational opportunities
The provision of standards and curricula at national/subnational levels is combined with advanced evaluation systems
Process-oriented assessments and/or centralised final examinations are complemented with individual reports and feed-back mechanisms on student learning progress
3838 Support systems and professional teacher development
In the best performing countries Effective support systems are located at
individual school level or in specialised support institutions
Teacher training schemes are selective The training of pre-school personnel is
closely integrated with the professional development of teachers
Continuing professional development is a constitutive part of the system
Special attention is paid to the professional development of school management personnel
3939 Student approaches to learning
The ability to manage one’s learning is both an important outcome of education and a contributor to student literacy skills at school
Learning strategies, motivation, self-related beliefs, preferred learning styles
Different aspects of students’ learning approaches are closely related
Well-motivated and self-confident students tend to invest in effective learning strategies and this contributes to their literacy skills
Immigrant students tend to be weaker performers… but they do not have weaker characteristics as
learners Boys and girls each have distinctive strengths
and weaknesses as learners Girls stronger in relation to motivation and self-
confidence in reading Boys believing more than girls in their own efficacy
as learners and in their mathematical abilities
4040Thematic Reports
To complement the initial report. In different areas of interest often
based on options parts of the questionnaire
Two of particular interest: Where Immigrant Students Succeed Are Students Ready for a Technology
Rich World
4141 Key Issues Policy attention is shifting from managing and
containing migration inflows to addressing challenges of integration
Schools can play a central role in integration processes Preparation for school-work transitions Overcoming language barriers Transmission of norms and values
PISA provides first-time comparative data on cognitive and non-cognitive learning outcomes of immigrant students… Comparison with native peers Comparison with immigrant student populations
across countries… and thus provides an opportunities to review
policies and practices in this area
4242 The report compares three student populations… Native students are students who were born in the
country of assessment or who had at least one parent born in that country
Second-generation immigrant students are students who were born in the country of assessment, but whose parents were born in another country, i.e. students who have followed their entire school career in the country of assessment
First-generation immigrant students are students who were not born in the country of assessment and whose parents were also born in another country
4343
400
450
500
550
600
Hong
Kong
-China
Nethe
rland
s
Belgi
um
Switz
erland
Cana
da
New Z
ealan
d
Mac
ao-C
hina
Australi
a
Germ
any
Fran
ce
Denmar
k
Swed
en
Austria
Luxe
mbour
g
Norwa
y
United
Sta
tes
Russian Fe
dera
tion
Native students Second- generation students First- generation students
OECD average = 500
Mathematics performance
Native students
Second-generation students
First-generation students
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Figure 2.2a.
Key findings On average across the 17 countries, 15-
year-old first-generation immigrants score in mathematics more than one school year behind their native counterparts
The performance disadvantage varies widely across countries from negligible amounts to…… more than 90 score points in Belgium
and Sweden for first-generation students … more than 90 score points in Belgium
and Germany for second-generation students The performance of immigrant students also
varies in absolute terms… with second-generation immigrants in
Canada outperforming their German counterparts by 111 score points
4444 Unemployment rates by immigration background
0
5
10
15
20
Native- born (2003) Foreign- born (2003)%
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Table 1.4.
4545
Macao- China
Canada
Australia
Hong Kong- China
New Zealand
Russian
Federation
United States
LuxembourgNorway
FranceSweden Austria
Netherlands
Belgium
Germany
Switzerland
Denmark
r = 0.30, p=0.25
460
470
480
490
500
510
520
530
540
550
560
0 20 40 60 80 100
Larger immigrant populations do not imply lower overall performance
Percentage of immigrant students in the country
Ma
the
ma
tic
s p
erf
orm
an
ce
4646
- 60- 40- 20
020406080
100
Russ
ian Fed
erat
ion
United
Sta
tes
Norway
Luxe
mbour
g
Austr
ia
Sweden
Denmar
k
Fran
ce
New Z
ealan
d
Austr
alia
German
y
Belgium
Mac
ao-C
hina
Switzer
land
Cana
da
Hong K
ong-
China
Nethe
r land
s
- 60- 40- 20
020406080
100
Russ
ian Fed
erat
ion
United
Sta
tes
Norway
Luxe
mbour
g
Austr
ia
Sweden
Denmar
k
Fran
ce
New Z
ealan
d
Austr
alia
German
y
Belgium
Mac
ao-C
hina
Switzer
land
Cana
da
Hong K
ong-
China
Nethe
r land
s
Levels5 and 6
Level 4
Level 3
Level 2
Level 1
Below 1
PISA Proficiency
Levels
Percentage of native students
Percentage of first-generation immigrant students
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Figure 2.4a.
Mathematics performance by proficiency levels
In PISA Level 2 demonstrates an essential foundation of mathematics skills
4747 Students’ interest in and enjoyment of mathematics (OECD
average)Native students
Second-generation immigrant students
First-generation immigrant students
I enjoy reading about mathematics.
28 35 41
I look forward to my mathematics lessons.
31 40 47
I do mathematics because I enjoy it.
38 43 48
I am interested in the things I learn in mathematics.
52 59 64
Stronger in 9 countries
Effect size 0.16
Stronger in 14 countries
Effect size 0.32
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Figures 4.2 and 4.9.
4949 Are students ready for a technology-rich world?
First internationally comparative data on: The opportunities 15-year-old students
have for using computers at home and at school
How they use computers and their attitudes to them;
The relationship between computer use and performance in key school subjects.
5050
Access to computers at school has increased rapidly between PISA 2000
and PISA 2003…
5151
…but in some countries students still have only limited opportunity to use
computers at school.
5252 Number of computers per student (PISA 2003)
0.0
0.1
0.2
0.3
0.4
Liec
hten
stei
n
Uni
ted
Sta
tes
Aus
tral
ia
Kore
a
Hun
gary
New
Zea
land
Hon
g Ko
ng-C
hina
Aus
tria
Cana
da
Japa
n
Den
mar
k
Luxe
mbo
urg
Icel
and
Nor
way
Sw
itze
rlan
d
Finl
and
Sw
eden
Belg
ium
Net
herl
ands
Ital
yM
acao
-Chi
na
Czec
h Re
publ
ic
Irel
and
Mex
ico
Gre
ece
Spa
in
Ger
man
y
Port
ugal
Slo
vak
Repu
blic
Pola
nd
Latv
ia
Tha
iland
Uru
guay
Indo
nesi
a
Tur
key
Ser
bia
Russ
ian
Fede
rati
on
Braz
il
Tun
isia
Uni
ted
King
dom
1
More than 10 students per computer
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , Figure 2.8, , Figure 2.8, p.27.p.27.
5 or fewer students per computer
1. Response rate too low to ensure comparability.
5353
Access to computers at school is more universal than access to computers at
home, but students report using computers much more frequently at
home.
5454Canada
Iceland
Sweden
Liechtenstein
Australia
Korea
Denmark
Belgium
United States
Germany
Switzerland
Austria
New Zealand
FinlandPortugalI talyCzech RepublicHungary
Slovak Republic
I reland
Poland
Uruguay
Greece
Tunisia
Serbia
Latvia
Mexico
Turkey
Russian Federation
J apan
ThailandUnited Kingdom1
Percentage of students using a computer at least a few times each week
100%
0%
At home
At school
Percentage of students reporting
they use computers “Almost every day”
or “A few times each week”:
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , Figure 3.2, , Figure 3.2, p.37.p.37.
1. Response rate too low to ensure comparability.
5555 What do students use computers to do?
PISA asked students how often they used: The Internet to look up information about people things or
ideas Games on a computer Word processing (e.g. <Microsoft Word® or WordPerfect®>) The Internet to collaborate with a group or team Spreadsheets (e.g. <Lotus 1 2 3® or Microsoft Excel®>) The Internet to download software (including games) Drawing, painting or graphics programs on a computer Educational software such as mathematics programs The computer to help learn school material The Internet to download music The computer for programming A computer for electronic communication (e.g. e-mail or “chat
rooms”) Students could choose from the following answers:
Almost every day, A few times each week, Between once a week and once a month, Less than once a month, Never
5656
Students use computers for a wide range of purposes and not just to play
games…
5757
1. Response rate too low to ensure comparability.
0
20
40
60
80
Canada
Unit
ed S
tate
s
Aust
ralia
Icela
nd
Denm
ark
New
Zeala
nd
Sw
eden
Aust
ria
Belg
ium
Kore
a
Port
ugal
Sw
itzerl
and
OECD
ave
rage
Czech R
epublic
Ita
ly
Germ
any
Mexic
o
Gre
ece
Pola
nd
Hungary
Fin
land
Ire
land
Turk
ey
Slo
vak R
epublic
Japan
Unit
ed K
ingdom
1
The I nternet to look up inf ormation about people, things or ideas.
Games on a computer.
Word processing (e.g. <Word® or WordPerf ect®>)
Students' use of computers (1)
Percentage of students reporting they use the following “Almost every day” or “A few times each week”:
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , ,
Figures 3.3 and 3.4, pp.39 and 41.Figures 3.3 and 3.4, pp.39 and 41.
Games – 53% on average
Internet research –
55% on average
Word processing –
48% on average
5858
… a minority of students frequently use educational software on computers…
5959
1. Response rate too low to ensure comparability.
0
20
40
60
80
Port
ugal
Uru
guay
Denm
ark
Mex
ico
Ita
ly
Tunis
ia
Icela
nd
Thailand
Unit
ed S
tate
s
Aust
ralia
Turk
ey
Slo
vak R
epublic
Aust
ria
Hungary
New
Zeala
nd
OE
CD
ave
rage
Canada
Serb
ia
Germ
any
Czech R
epub
lic
Pola
nd
Latv
ia
Belg
ium
Sw
eden
Gre
ece
Russ
ian F
edera
tion
Lie
chte
nst
ein
Sw
itzerl
and
Kore
a
Fin
land
Ire
land
Japan
Unit
ed K
ingdom
1
Educational sof tware such as mathematics programs
The computer to help learn school material
Students' use of computers (2)
Percentage of students reporting they use the following “Almost every day” or “A few times each week”:
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , ,
Figure 3.4, p.41.Figure 3.4, p.41.
To learn school material - 30% on
average
Educational software - 13%
on average
6060
In general, students are confident in performing routine and Internet tasks
on computers.
6161 Routine tasks on a computer – percentage of students who are confident (OECD
average)
Open a file 90 7
Play computer games 90 7
Start a computer game 86 10
Save a computer document or file 88 8
Delete a computer document or file 88 8
Draw pictures using a mouse 85 10
Print a computer document or file 86 9
Scroll a document up and down a screen 87 8
Create/edit a document 80 13
Move files from one place to another on a computer 76 17
Copy a file from a floppy disk 75 16
I can do this…
By myself
With help
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , Table 3.9, , Table 3.9, p.110.p.110.
6262 Internet tasks on a computer – percentage of students who are confident (OECD
average)I can do this…
By myself
With help
At least 90% of students report confidence in these tasks in Australia, Canada, Iceland, Korea, New Zealand, Sweden and the United States.
Get onto the Internet 88 7
Write and send e-mails 79 12
Copy or download files from the Internet 70 19
Download music from the Internet 66 21
Attach a file to an e-mail message 58 24
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , Table 3.11, , Table 3.11, p.112.p.112.
6363
In general, 15-year-old boys report higher confidence than girls do in
performing computing tasks and these differences are particularly apparent for
the more demanding computing tasks...
6464 High-level tasks on a computer – percentage of students who are confident to perform
these tasks by themselves or with help (OECD average)
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , Table 3.14, , Table 3.14, p.115.p.115.
Boys Girls
Use software to find and get rid of computer viruses 79 54
Create a multi-media presentation (with sound, pictures, video) 77 62
Create a computer program (e.g. in Logo, Pascal, Basic) 63 48
Construct a Web page 71 61
Create a presentation (e.g. using <Microsoft® PowerPoint® > 79 70
Use a spreadsheet to plot a graph 79 70
Use a database to produce a list of addresses 85 79
6565
Students who are established computer users perform better than students with limited computing experience.
6666
0
20
40
60
80
100
120
140
Swit
zerl
and
Bel
gium
Icel
and
Uni
ted S
tate
s
Ger
man
y
New
Zea
land
Aus
tria
Den
mar
k
Ital
y
Kor
ea
Hun
gary
Swed
en
Mex
ico
Aus
tral
ia
Pola
nd
Port
ugal
Cze
ch R
epub
lic
Slo
vak
Rep
ublic
Tur
key
Jap
an
Can
ada
Gre
ece
Fin
land
Irel
and
between students who reported using computers less than one year and those using computers more than five years
between students who reported using computers less than one year and those using computers three to five years
between students who reported using computers less than one year and those using computers one to three years
… and diminishes somewhat when socio-economic background factors are taken into account
6767
If more experience counts, more frequent use does not necessarily
Looking at a wide range of students’ use of computers, moderate users
perform better than students who are either not using computers/using them
rarely or are using computers very often…
6868
Mathematics performance
475
500
525
Bottom
quarter
Second
quarter
Third
quarter
Top
quarter
Reading performance
475
500
525
Bottom
quarter
Second
quarter
Third
quarter
Top
quarterStudents reporting a moderate use of computers to perform a
range of tasks
Frequency of use of computer to perform a wide range of tasks and student
performance
Source: OECD (2005) Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell usAre students ready for a technology-rich world? What PISA studies tell us , Figure 4.6, , Figure 4.6, p.65.p.65.
Index of ICT Internet/entertainment use
Index of ICT program/software use
6969Other research
“Northern lights” Regional studies Longitudinal studies Science attitudes Reading engagement Mathematics anxiety Indigenous students Rural education Selection practices
7070Other research
Social background Teaching and learning strategies –
cumulative study (caution) Problem solving
7171Some country interests
Germany - social background, regional effects, effect of tracking, migration
Netherlands – social background, migration Australia – longitudinal, indigenous, rural,
regions Japan – attitudes to science, US – reading interest, difference in
performance of students in TIMSS and in PISA
Belgium – regions, social background Switzerland – grade sample
7272Some country interests
Denmark – longitudinal Luxembourg – language background Italy – regions Ireland – relationship of PISA with
National examinations Turkey – school variation Canada – longitudinal, province
differences Iceland – gender differences
7373Further information
www.pisa.oecd.org– All national and international publications– The complete database– Data analysis manuals (SPSS, SAS)
email: [email protected]