The capacity to engage creatively in cognitive processing to understand and resolve problem situations where a method of solution is not immediately obvious (including motivational and affective aspects).
2. 2 PISA in brief
• Over half a million students…
– representing 28 million 15-year-olds in 65 countries/economies
– Schools and students randomly selected by OECD
… 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 .
…the capacity to engage creatively in
cognitive processing to understand and
resolve problem situations where a method
of solution is not immediately obvious
(including motivational and affective aspects).
Problem Solving: 85 000 students
in 44 countries/economies took
an additional 40-min test
3. 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 distribution
3
The case for creative problem-solving
Trends in different tasks in occupations (United States)
Source: Autor, David H. and Brendan M. Price. 2013. "The Changing Task Composition of the US Labor Market: An Update of Autor, Le
vy, and Murnane (2003)." MIT Mimeograph, June.
4. 5
TRAFFIC
Problem Solving – Sample Question 1
Julio lives in Silver, Maria lives in Lincoln, and Don lives in Nobel.
They want to meet in a suburb on the map. No-one wants to travel
for more than 15 minutes.
Where could they meet?
This is an easy item – Level 1 on the
problem-solving scale (below baseline)
All information required is given at
the outset: it is a static problem
An embedded
calculator ensures
the item measures
problem solving –
not arithmetics
This item focuses on students’ ability
to monitor and reflect on solutions.
5. 6
TICKETS
You plan to take four trips
around the city on the
subway today. You are a
student, so you can use
concession fares.
Use the ticketing machine
to find the cheapest ticket
and press BUY.
Once you have pressed
BUY, you cannot return to
the question;
Problem Solving – Sample Question 2
This is a harder item – Level 5 on the
problem-solving scale
Students must engage with the
machine, and use the feedback and
information uncovered to reach a
solution: it is an interactive problem
This main demand is exploring and
understanding (knowledge acquisition)
Sample items can be tried at cbasq.acer.edu.au and www.oecd.org/pisa
6. 7 77 Performance in problem-solving
How well do 15-year-olds engage creatively in
cognitive processing to understand and resolve
problem situations?
• Exploring and understanding the information provided
with the problem.
• Representing and formulating: constructing
graphical, tabular, symbolic or verbal representations of the
problem situation and formulating hypotheses about the
relevant factors and relationships between them.
• Planning and executing: devising a plan by setting goals
and sub-goals, and executing the sequential steps identified
in the plan.
• Monitoring and reflecting: monitoring progress, reacting to
feedback, and reflecting on the solution, the information
provided with the problem, or the strategy adopted.
7. SingaporeKorea
Japan
Macao-ChinaHong Kong-China
Shanghai-ChinaChinese Taipei
Canada
AustraliaFinland
England (U.K.)Estonia France NetherlandsItalyCzech RepublicGermany
United States BelgiumAustriaNorway
IrelandDenmark
Portugal
SwedenRussian Fed.
Slovak RepublicPoland
SpainSlovenia Serbia
Croatia
Hungary
TurkeyIsrael
Chile
Brazil
Malaysia
U.A.E
Montenegro
UruguayBulgaria Colombia
390
400
410
420
430
440
450
460
470
480
490
500
510
520
530
540
550
560
570
Mean score
Strong performance in
problem solving
Low performance in problem solving
Average performance
of 15-year-olds in
problem solving
Fig V.2.3
8
9. 1010 The rising demand for advanced skills
-20
-15
-10
-5
0
5
10
15
20
25
%
Evolution of employment in occupational groups
defined by PIAAC problem-solving skills
Employment of
workers with advanced
problem-solving skills
Employment of workers with
poor problem-solving skillsEmployment of workers with
medium-low problem-solving
skills (PIAAC)
Source:PIAAC 2011
11. 1414 Strengths and weaknesses in problem-solving
Which countries have particular
strengths in problem-solving ?
12. 200
300
400
500
600
700
800
200 300 400 500 600 700 800
Patterns of relative performance in problem solving
Problem solving performance
Mathematics performance
Fig V.2.16
Fig V.2.17
Average relationship
between problem solving
and mathematics
performance
The United States and England (UK) perform better-than-
expected in problem solving. The difference between observed
and expected performance is larger among strong performers in
mathematics
Japan performs better-than-expected in
problem solving. The difference between
observed and expected performance is
larger among low achievers in
mathematics
Poland’s performance is lower-than-expected in
problem solving. The gap between observed and
expected performance is similar at all levels of
mathematics performance.
15
Spain’s performance is lower-than-
expected in problem solving. The gap
between observed and expected
performance is wider among low
achievers in mathematics.
Singapore’s performance in
problem solving is as high as
expected at all levels of
mathematics performance
14. Strengths and weaknesses:
interactive and static tasks
Fig V.3.10
Better performance
on static tasks
Better performance
on interactive tasks
17
United States
Germany
Austria
France
Japan
Sweden
Australia
Israel
Canada
Ireland
Belgium
Norway
Korea
Italy
Hong Kong-China
Chinese Taipei
Macao-China
Singapore
Shanghai-China
Poland
England
Estonia
Finland
Slovak Rep.
Czech Rep.
Turkey Hungary
Chile
Netherlands
Spain
Denmark
Slovenia
Portugal
Brazil
Uruguay
Croatia
Bulgaria
U.A.E.
Montenegro
Colombia
Malaysia
Serbia
Russian Fed.
15. Strengths and weaknesses:
knowledge-generation and knowledge-utilisation
Fig V.3.10
United States
England
Germany
Czech Rep.
France Japan
Australia
Canada
Ireland
Chile Belgium
Spain
Portugal Korea
Italy
Brazil
U.A.E. SingaporeColombia
Poland
Estonia
Finland
Slovak Rep.
AustriaTurkey
SwedenHungary
Israel
NetherlandsDenmark
Slovenia
Norway
Hong Kong-ChinaUruguay
Croatia
Chinese Taipei
Bulgaria
Macao-China
Montenegro
Malaysia
Serbia
Russian Fed.
Shanghai-China
Better
performance
on
knowledge-
utilisation
tasks
Better
performance
on
knowledge-
generation
tasks
18
16. Strengths and weaknesses Fig V.3.10
United States
Poland
England
Estonia
Finland
Slovak Rep.
Germany
Austria
Czech Rep.
France
Japan
Turkey
Sweden
Hungary
Australia
Israel
Canada
Ireland
Chile
Belgium
Netherlands
Spain
Denmark
Slovenia
Portugal
Norway
Korea
Italy
Hong Kong-China
Brazil
Uruguay
Croatia
Chinese Taipei
Bulgaria
Macao-China
U.A.E.
Montenegro
Singapore
Colombia
Malaysia
Serbia
Russian Fed.
Shanghai-China
OECD average
OECDaverage
Better performance
on interactive tasks
Better performance on
static tasks
Better
performance
on
knowledge-
acquisition
tasks
Better
performance
on
knowledge-
generation
tasks
Stronger-than-expected performance on interactive
items, weaker-than-expected performance on
knowledge-acquisition tasks
Stronger-than-expected performance on interactive
items and on knowledge-acquisition tasks
Weaker-than-expected performance on interactive
items and on knowledge-acquisition tasks
Weaker-than-expected performance on interactive
items , stronger-than-expected performance on
knowledge-acquisition tasks
19
17. 2020 Student resilience
The country where students go to class matters
more than what social class students come from
18. 2121
PISA mathematics performance
by decile of social background
300325350375400425450475500525550575600625650675
Mexico
Chile
Greece
Norway
Sweden
Iceland
Israel
Italy
UnitedStates
Spain
Denmark
Luxembourg
Australia
Ireland
UnitedKingdom
Hungary
Canada
Finland
Austria
Turkey
Liechtenstein
CzechRepublic
Estonia
Portugal
Slovenia
SlovakRepublic
NewZealand
Germany
Netherlands
France
Switzerland
Poland
Belgium
Japan
Macao-China
HongKong-China
Korea
Singapore
ChineseTaipei
Shanghai-China
Source: PISA 2012
23. Country examples
• Involve employers and parents in developing
a vision for education
• Make problem-solving competence an
overarching goal of the curriculum
• Give every student a chance to engage in deep
learning through meaningful projects
• Support teachers to ensure that
project time is learning time
Embed learning of 21st century competencies and
attitudes such as inquiry-based authentic learning in
curricular subjects and co-curricular activities
Clear articulation of desired student outcomes to guide
schools’ and teachers’ efforts and ensure coherence and
alignment of curriculum, pedagogy and assessment.
Alberta’s Curriculum
Redesign Project
Singapore’s 21st Century
Competencies Framework
Japan’s Zest for Life approach
24. 2828Lessonsfromhighperformers
Strong performers and successful reformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
25. 2929Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
26. 3030Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
A commitment to education and the belief that
competencies can be learned and therefore all
children can achieve
Universal educational standards and personalization as
the approach to heterogeneity in the student body…
… as opposed to a belief that students have different
destinations to be met with different expectations, and
selection/stratification as the approach to
heterogeneity
Clear articulation who is responsible for ensuring
student success and to whom
27. Students and perseverance
Percentage of students who reported that the following statements describe someone "very
much like me" or "mostly like me" (*) or "not much like me" or "not at all like me" (**)
0 10 20 30 40 50 60 70
Disagree: When confronted with a problem, I
give up easily
Disagree: I put off difficult problems
Agree: I remain interested in the tasks that I
start
Agree: I continue working on tasks until
everything is perfect
Agree: When confronted with a problem, I do
more than what is expected of me
Singapore OECD average
Fig III.3.2
31
29. Openness to problem solving
Percentage of students who reported "agree" or "strongly agree" with the following statements:
0 20 40 60 80 100
I can handle a lot of information
I am quick to understand things
I seek explanation for things
I can easily link facts together
I like to solve complex
problems
%
Poland Singapore OECD average
Fig III.3.4
33
31. 3535Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
Clear ambitious goals that are shared across the
system and aligned with high stakes gateways and
instructional systems
Well established delivery chain through which
curricular goals translate into instructional systems,
instructional practices and student learning (intended,
implemented and achieved)
High level of metacognitive content of instruction …
32. 3636Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
Capacity at the point of delivery
Attracting, developing and retaining high quality
teachers and school leaders and a work organisation in
which they can use their potential
Instructional leadership and human resource
management in schools
Keeping teaching an attractive profession
System-wide career development …
33. 3737Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
Incentives, accountability, knowledge management
Aligned incentive structures
For students
How gateways affect the strength, direction, clarity and nature of the
incentives operating on students at each stage of their education
Degree to which students have incentives to take tough courses and study hard
Opportunity costs for staying in school and performing well
For teachers
Make innovations in pedagogy and/or organisation
Improve their own performance
and the performance of their colleagues
Pursue professional development opportunities
that lead to stronger pedagogical practices
A balance between vertical and lateral accountability
Effective instruments to manage and share knowledge and spread
innovation – communication within the system and with
stakeholders around it
A capable centre with authority and legitimacy to act
35. 39
39
39
Hong Kong-China
Brazil
Uruguay
Albania
Croatia
Latvia
Lithuania
Chinese Taipei
ThailandBulgaria
Jordan
Macao-China
UAE Argentina
Indonesia
Kazakhstan
Peru
Costa Rica
Tunisia
Qatar
Singapore
Colombia
Malaysia
Serbia
Romania
Viet Nam
Shanghai-China
USA
Poland
New Zealand
Greece
UK
Estonia
Finland
Slovak Rep.
Luxembourg
Germany
Austria
Czech Rep.
France
Japan
Turkey
Sweden
Hungary
Australia
Israel
Canada
Chile
Belgium
Netherlands
Spain
Denmark
Switzerland
Iceland
Slovenia
Portugal
Norway
Korea
Italy
R² = 0.13
300
350
400
450
500
550
600
650
-1.5 -1 -0.5 0 0.5 1 1.5
Mathematicsperformance(scorepoints)
Index of school responsibility for curriculum and assessment
(index points)
Countries that grant schools autonomy over curricula and
assessments tend to perform better in mathematics
Source: PISA 2012
36. No standardised
math policy
Standardised math
policy455
460
465
470
475
480
485
Less school autonomy
More school autonomy
Schools with more autonomy perform better than schools with
less autonomy in systems with standardised math policies
Score points
School autonomy for curriculum and assessment
x system's extent of implementing a standardised math policy (e.g. curriculum and
instructional materials)
Fig IV.1.16
37. Schools with more autonomy perform better than schools with
less autonomy in systems with more collaboration
Teachers don't participate
in management
Teachers participate in
management455
460
465
470
475
480
485
Less school autonomy
More school autonomy
Score points
School autonomy for resource allocation x System's level of teachers
participating in school management
Across all participating countries and economies
Fig IV.1.17
38. Schools with more autonomy perform better than schools with
less autonomy in systems with more accountability arrangements
School data not public
School data public
464
466
468
470
472
474
476
478
Less school autonomy
More school autonomy
Score points
School autonomy for curriculum and assessment
x system's level of posting achievement data publicly
Fig IV.1.16
39. 0 20 40 60 80 100
Written specification of the school's curriculum and
educational goals
Written specification of student-performance standards
Systematic recording of data, including teacher and
student attendance and graduation rates, test results…
Internal evaluation/self-evaluation
External evaluation
Written feedback from students (e.g. regarding
lessons, teachers or resources)
Teacher mentoring
Regular consultation with one or more experts over a
period of at least six months with the aim of improving…
Implementation of a standardised policy for
mathematics
%
Percentage of students in schools whose principal reported that their schools have the
following for quality assurance and improvement:
Singapore OECD average
Quality assurance and school improvement Fig IV.4.14
43
40. 4444Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
Investing resources where they can make most
of a difference
Alignment of resources with key challenges (e.g.
attracting the most talented teachers to the most
challenging classrooms)
Effective spending choices that prioritise high quality
teachers over smaller classes
41. 4545 Align the resources with the challenges
Hong Kong-China
Brazil
Uruguay
Croatia
Latvia
Chinese Taipei
Thailand
Bulgaria
Jordan
Macao-China
UAE
Argentina
Indonesia
Kazakhstan
Peru
Costa Rica
Montenegro
Tunisia
Qatar
Singapore
Colombia
Malaysia
Serbia
Romania
Viet Nam
Shanghai-China
USA
Poland
New Zealand
Greece
UK
Estonia
Finland
Slovak Rep.
Luxembourg
Germany
AustriaFrance
Japan
Turkey
Sweden Hungary
Australia
Israel
Canada
Ireland
Chile
Belgium
SpainDenmark
Switzerland
Iceland
Slovenia
Portugal
Norway
Mexico
Korea
Italy
R² = 0.19
300
350
400
450
500
550
600
650
700
-0.500.511.5
Mathematicsperformance(scorepoints)
Equity in resource allocation
(index points)
Greater equityLess equity
Adjusted by per capita GDP
Countries with better performance in mathematics tend to
allocate educational resources more equitably
Source: PISA 2012
42. 4646 Adequate resources to address disadvantage
Disadvantaged schools reported
more teacher shortage
Advantaged schools reported
more teacher shortage
-0.5
-0.3
-0.1
0.1
0.3
0.5
0.7
0.9
1.1
1.3
1.5
Korea
Estonia
Israel
Latvia
Slovenia
Italy
Poland
Singapore
Argentina
Netherlands
Portugal
Colombia
France
Finland
Tunisia
Macao-China
Spain
Greece
Switzerland
Norway
RussianFed.
Japan
Austria
Montenegro
Croatia
Canada
OECDaverage
Germany
Denmark
Hungary
UnitedKingdom
Luxembourg
HongKong-China
Belgium
Iceland
VietNam
Ireland
UnitedStates
Chile
CzechRepublic
Serbia
Turkey
Mexico
Indonesia
Uruguay
Shanghai-China
SlovakRepublic
Sweden
Brazil
NewZealand
Australia
ChineseTaipei
Meanindexdifference
Difference between socio-economically disadvantaged and socio-economically advantaged schools
A shortage of qualified teachers is more of concern
in disadvantaged schools
44. 4848Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
Coherence of policies and practices
Alignment of policies
across all aspects of the system
Coherence of policies
over sustained periods of time
Consistency of implementation
Fidelity of implementation
(without excessive control)
45. 4949Lessonsfromhighperformers
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional
systems
Capacity
at point of delivery
Incentive structures and
accountability
Resources
where they yield most
A learning system
Coherence
46. 5050Lessonsfromhighperformers
Some students learn at high levels All students need to learn at high levels
Student inclusion
Routine cognitive skills, rote learning Learning to learn, complex ways of thinking, ways
of working
Curriculum, instruction and assessment
Few years more than secondary High-level professional knowledge workers
Teacher quality
‘Tayloristic’, hierarchical Flat, collegial
Work organisation
Primarily to authorities Primarily to peers and stakeholders
Accountability
What it all means
The old bureaucratic system The modern enabling system
47. Thank you !
Find out more about PISA at www.pisa.oecd.org
• All national and international publications
• The complete micro-level database
Email: Andreas.Schleicher@OECD.org
Twitter: SchleicherEDU
and remember:
Without data, you are just another person with an opinion
Hinweis der Redaktion
Another way of looking at the evolution of demand for skills is provided by Autor, Levy and Murnane (2003), whoclassify jobs into routine and non-routine tasks. They argue that the share of non-routine analytic and interactive jobtasks (tasks that involve expert thinking and complex communication skills) performed by American workers hasincreased steadily since 1960. The share of routine cognitive and manual tasks began to decline in theearly 1970s and 1980s, respectively – coinciding with the introduction of computers and computerised productionprocesses. These are tasks that are more readily automated and put into formal algorithms. The share of non-routinemanual tasks also declined, but stabilised in the 1990s, possibly due to the fact that they cannot be easily computerisedor outsourced.
In the unit TRAFFIC, students are given a map of a road network with travel times indicated. While this is a unit with static items, because all the information about travel times is provided at the outset, it still exploits the advantages of computer delivery. Students can click on the map to highlight a route, with a calculator in the bottom left corner adding up travel times for the selected route. The context for the items in these units is classified as social and non-technological. In the third item, students have to use a drop-down menu to select the meeting point that satisfies a condition on travel times for all three participants in a meeting. The demand in this third item is classified as a monitoring and reflecting task, because students have to evaluate possible solutions against a given condition.Students who use spatial reasoning in this item – selecting the geometrical midpoint between the three starting positions – are likely to select the correct answer. This makes the item easier than other tasks with similar demands.This taskmeasures anelementarylevel of problemsolvingskills – Level 1 in a scalethat comprises six describedlevels in total. Across the OECD, 21% of students are only able to solvetasksatthislevel of difficulty – if any. At Level 1, students can explore a problem scenario only in a limited way, but tend to do so only when they have encountered very similar situations before. In general, students at Level 1 can solve straightforward problems provided there is only a simple condition to be satisfied and there are only one or two steps to be performed to reach the goal. Level 1 students tend not to be able to plan ahead or set subgoals.
In the unit TICKETS, students are invited to imagine that they have just arrived at a train station that has an automated ticketing machine. The context for the items in these units is classified as social and technological. In this harder task, compared to the previous example, students must use targeted exploration to reach their goal. They are asked to find and buy the cheapest ticket that allows them to take four trips around the city on the subway, within a single day. As students, they can use concession fares. This item is an example of an interactive problem situation: students are required to engage with the unfamiliar machine and to use the machine to satisfy their needs, without having complete instructions and knowledge about the machine at the outset.This item is classified as exploring and understanding because the main (but not the only) demand of the item corresponds to the acquisition of knowledge about how the machine works, and the prices for the available options. It is therefore a knowledge-acquisition task. Indeed, to accomplish the task, students must use a targeted exploration strategy, first generating at least the two most obvious possible alternatives (a daily subway tickets with concession fares, or an individual concession fare ticket with four trips), then verifying which of these is the cheapest ticket. If students visit both screens before buying the cheapest ticket (which happens to be the individual ticket with four trips) they are given full credit. Students who buy one of the two tickets without comparing the prices for the two only earn partial credit. Solving this problem involves multiple steps.Across the OECD, only about one in ninestudents (11%) are able to solveproblemsatLevel 5 on the problem-solvingscale, such as this one. At Level 5, students can systematically explore a complex problem scenario to gain an understanding of how relevant information is structured. When faced with unfamiliar, moderately complex devices, such as vending machines, they respond quickly to feedback in order to control the device. In order to reach a solution, Level 5 problem-solvers think ahead to find the best strategy that addresses all the given constraints. They can immediately adjust their plans or backtrack when they detect unexpected difficulties or when they make mistakes that take them off course.Level 5 problem-solvers, together with students reaching proficiency level 6, are considered problem solving “top performers”.
TEST 2_ordre décroissant
Because problem-solving skills are required in all kinds of occupations, and are not taught as such in school, but rather are nurtured by good instructional practices in every subject, performance in problem solving should not be strongly influenced by such gender-based stereotypes. Problem-solving performance could then be regarded as an overall indicator of gender biases in a country’s education system.The good news is that in most countries, there are no large differences in boys’ and girls’ average performance in problem solving. While boys and girls do not differ markedly in their average performance, the variation in problem-solving performance is larger among boys than among girls. At lower levels of proficiency, there are, in general, equal proportions of boys and girls. But the highest-performing students in problem solving are largely boys – with a few notable exceptions, such as Australia, Finland and Norway, where the proportion of top-performing girls is about the same as the proportion of top-performing boys. In Croatia, Italy and the Slovak Republic, on the other hand, girls are particularly rare among top-performers.Similarly, the Survey of Adults Skills shows that among adults, top-performers in problem solving are mostly men – except in Canada, Australia and Finland. Because advanced problem-solving skills are the key to access leadership positions, a lack of female leadership figures may in turn create biases in society and teachers that limit girls’ ambition to perform at the top – and perpetrate the glass ceiling.Such biases should not run in the way of nurturing each students’ creative dispositions and problem-solving skills, to enable them to live full lives and contribute with their talents and skills to the country’s well-being.
As machines and computers are increasingly replacing humans for performing routine tasks, highly skilled workers, who are capable of applying their unique skills flexibly in a variety of contexts, regulating their own learning, and handling novel situations, are more and more in demand. Knowing the proportion of 15-year-old students who perform at the highest levels in problem solving allows countries to estimate how well they can respond to this demand. Of particular interest is the proportion of students who, in addition to performing at the highest levels in problem solving, also show excellent mastery of specific subjects. These are top performers who combine the mastery of a specific domain of knowledge with the ability to apply their unique skills flexibly, in a variety of contexts.
(more patternscanbeadded)Germany: same as Spain
TEST 1 _ L’ordre des pays est croissant (différent que dans la Figure V.2.15)
Interactive items are central to the PISA problem-solving assessment, and distinguish it from previous attempts at measuring problem-solving skills. They require students to be open to novelty, tolerate doubt and uncertainty, and dare to use intuitions to initiate a solution.
Tasks can also be distinguished by the problem-solving process that constitutes their main cognitive demand. A major distinction is between knowledge-acquisition tasks and knowledge-utilisation tasks.In knowledge-acquisition tasks, the goal is for students to develop or refine their own representation of the problem space. Students need to generate and manipulate the information in a mental representation. The movement is from concrete to abstract, from information to knowledge. The sample item TICKETS is an example. In knowledge-utilisation tasks, the goal is for students to solve a concrete problem. The movement is from abstract to concrete, from knowledge to action. Knowledge-utilisation tasks correspond to the process of “planning and executing”. To ensure that no additional generation or refinement of knowledge about the problem is needed, items targeting “planning and executing” often had the results of “representing and formulating” tasks available.The best-performing countries in problem-solving often excel particularly on knowledge-acquisition tasks that require high levels of reasoning skills and self-directed learning.
Together, the differences in performance according to the nature of the problem situation and the major problem-solving process targeted identify several groups of countries. These groups often overlap with historical and geographical groupings.Six East Asian countries and economies, namely Korea, Singapore, Hong Kong-China, Macao-China, Chinese Taipei and Shanghai-China, stand out for their very high success rates on knowledge-acquisition tasks, compared to their success rates on planning and executing tasks. Within this group, however, there are relatively stark differences in their performance on interactive problems. Students in Korea and Singapore are significantly more at ease with these problems than students in Shanghai-China, Chinese Taipei and Macao-China. Students from Hong Kong-China are in a middle position. While all of these countries and economies are in the top positions for overall performance, this analysis suggests that in Shanghai-China, Chinese Taipei and Macao-China, a focus on students’ skills at dealing with interactive problem situations is required in order to improve further and close the performance gap with Korea and Singapore. In reviewing their curricula, teachers and curriculum developers may want to introduce more opportunities for students to develop and exercise the traits that are linked to success on interactive items, such as curiosity, perseverance and creativity. They may find inspiration in the curricula and teaching practices of their regional neighbours. Among lower-performing countries and economies, the poor performance of several Latin American countries (Brazil, Colombia, Chile and Uruguay) appears to be mainly due to a large performance gap on knowledge-acquisition tasks. These countries have no particular difficulty with interactive tasks – and Brazil even shows a relative strength on such tasks. In these countries, efforts to raise problem-solving competency should concentrate mainly on improving students’ performance on “exploring and understanding” and on “representing and formulating” tasks. These tasks require students to build mental representations of the problem situation from the pieces of information with which they are presented. Moving from the concrete problem scenario to an abstract representation and understanding of it often demands inductive or deductive reasoning skills. Teachers and curriculum experts may question whether current curricula include sufficient opportunities to model these abstract reasoning skills and whether these opportunities are offered in the classroom.In contrast, several countries in Southern and Eastern Europe, namely Bulgaria, Montenegro, Slovenia, Croatia and Serbia, show relatively weak performance both on knowledge-acquisition tasks and on interactive tasks, compared to their performance on “planning and executing” and on static tasks. In these countries, students seem to find it particularly difficult to understand, elaborate on, and integrate information that is not explicitly given to them (in a verbal or visual format), but has to be inferred from experimental manipulation of the environment and careful observation of the effects of that manipulation. Students in these countries may benefit from greater opportunities to learn from hands-on experience.The performance gap between OECD countries in Europe and North America and the top-performing countries in problem solving mainly originates from differences in students’ performance on knowledge-acquisition tasks. In general, the PISA problem-solving assessment shows that there is significant room for improving students’ ability to turn information into useful knowledge, as measured by performance differences on the dimensions of “exploring and understanding” and “representing and formulating” problem situations.Within this group, Ireland and the United States stand out for their strong performance on interactive items, compared, for instance, to the Nordic countries (Sweden, Finland, Norway and Denmark), the Netherlands, and some countries in Central Europe (in particular, Poland, Hungary, the Slovak Republic). Therefore, the analysis also identifies a strong potential for the latter group of countries to improve on their students’ ability to cope with interactive problem situations. To do so, educators may need to foster such dispositions as being open to novelty, tolerating doubt and uncertainty, and daring to use intuition to initiate a solution.Finally, several countries, while performing at different levels, show a similar balance of skill when compared to each other, and one that is close to the OECD average pattern of performance. Italy and Australia, for instance, have a very similar pattern of performance to that observed in Japan, although in terms of overall performance, Japan ranks significantly above Australia, which, in turn, performs better than Italy. These three countries all perform close to their expected level on interactive items (based on the OECD average pattern of performance), and slightly above their expected level on knowledge-acquisition tasks (although the example of Korea and Singapore shows that significant gains are still possible for them). In other countries, such as Spain, England (United Kingdom) and Germany, performance across tasks reflects the balance observed across OECD countries, on average.
While large and significant, the impact of socio-economic disadvantage on problem-solving skills is weaker than it is on performance in mathematics, reading or science. At all levels of the socio-economic ladder, there is more variation in performance in problem solving than there is in mathematics, perhaps because after-school opportunities to develop problem-solving skills are more evenly distributed than opportunities to develop proficiency in mathematics or reading.
Within all countries, problem-solving results vary greatly between schools: differences in problem-solving performance between schools are as large as differences in mathematics performance, indicating that schools have an important role to play in building these skills. The variation in performance between schools is a measure of how big “school effects” are. These school effects may have three distinct explanations: first, they may reflect selection mechanisms that assign students to schools; in addition, they may be the result of differences in policies and practices across schools; finally, they may be the traces of local school cultures, which develop not by design as a result of policies or deliberate practices, but by the interactions among local communities.The between-school variation in student results is therefore not a direct measure of the importance of school policies and practices for student performance in problem solving. However, if the between-school variation is compared across different student characteristics – some sensitive to education policy and practices, such as performance in mathematics, others not, such as socio-economic status – one may infer the extent to which problem-solving results are related to instructional policies and practices.One might expect the proportion of variation in performance observed between schools to be smaller in problem solving than in reading, science, and mathematics. First, the skills required in the PISA assessment of problem solving are not taught as a specific school subject in most countries, in contrast to those required in reading, science, and mathematics. Second, assessments of problem solving are not explicitly used in high-stakes examinations that influence decisions about selecting students for different classes or schools, where these exist. Yet the association ofdifferences in instruction and selection mechanisms with performance in problem solving is as strong as the association with performance in mathematics.The between-school variation, on the other hand, is much larger in student outcome measures – such as reading, mathematics, or indeed problem solving – than in student background factors that influence performance, such as the PISA index of economic, cultural, and social status (ESCS).
Studentswho, at best, are only able to solveproblemssuch as sampletask TRAFFIC.In six partner countries, more thanhalf of all students do not reach the baseline. In Korea, Japan, Macao-China and Singapore, on the other hand, lessthan one in tenstudentis.
Table V.4.23 has the data for Problem Solving – results are very similar
(Fig. II.4.5)
Table V.4.23 has the data for Problem Solving – results are very similar
I want to conclude with what we have learned about successful reform trajectories In the past when you only needed a small slice of well-educated people it was efficient for governments to invest a large sum in a small elite to lead the country. But the social and economic cost of low educational performance has risen substantially and all young people now need to leave school with strong foundation skills.When you could still assume that what you learn in school will last for a lifetime, teaching content and routine cognitive skills was at the centre of education. Today, where you can access content on Google, where routine cognitive skills are being digitised or outsourced, and where jobs are changing rapidly, the focus is on enabling people to become lifelong learners, to manage complex ways of thinking and complex ways of working that computers cannot take over easily.In the past, teachers had sometimes only a few years more education than the students they taught. When teacher quality is so low, governments tend to tell their teachers exactly what to do and exactly how they want it done and they tend to use Tayloristic methods of administrative control and accountability to get the results they want. Today the challenge is to make teaching a profession of high-level knowledge workers. But such people will not work in schools organised as Tayloristic workplaces using administrative forms of accountability and bureaucratic command and control systems to direct their work. To attract the people they need, successful education systems have transformed the form of work organisation in their schools to a professional form of work organisation in which professional norms of control complement bureaucratic and administrative forms of control.