Introducing PIAAC - OECD's new programme for assessing adult competencies

No Slide TitlePIAAC OECD Programme for the International Assessment of Adult Competencies
PIAAC
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PIAAC OECD Programme for the International Assessment of Adult Competencies
Meeting of the Education Policy Committee
PIAAC
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PIAAC
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Context for PIAAC
Growth and competitiveness increasingly depend on the capacity of countries to
Anticipate the evolution of labour demand
Promote skill acquisition and equity of access to learning
Deploy their talent pool effectively by ensuring that the right mix of skills is being taught and learned and employers find workers with the skills they need
Develop efficient and sustainable approaches to the financing of learning that establish who should pay for what, when, where and how much.
Growth is not just affected positively by the available talent pool, but also negatively by the economic and social costs associated with inadequate skills .
Why are we proposing this? As we all know, growth and competitiveness increasingly depend on the capacity of countries to anticipate the evolution of labour demand and to promote skill acquisition and equity of access to learning. But an equally important challenge for countries is to deploy their talent pool effectively by ensuring that the right mix of skills is being taught and learned and employers find workers with the skills they need. And finally, it is important to develop more efficient and sustainable approaches to the financing of learning that also provide a rational basis for who should pay for what, when, where and how much. Transitions to environmentally sustainable economies are an additional driver in the mix of skills that countries require, as are enhanced skill requirements for social and political participation. International migration is also a source of skills but one that needs to be managed appropriately in order to match individual aspirations with the needs of both sending and receiving countries.
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PIAAC seeks to assist countries in improving economic and social outcomes through better skills and their effective utilisation
Responsiveness
Quality and efficiency in learning provision
Ensuring that the right skills are acquired at the right time, right place and in the most effective mode
Flexibility in provision
Allowing people to study/train what they want, when they want and how they want
Transferability of skills
Such that skills gained are documented in a commonly accepted and understandable form
Ease of access
Reducing barriers to entry such as institutional rigidities, up-front fees and age restrictions, existence of a variety of entry and re-entry pathways
Low costs of early exit
Recognition for components of learning, modular provision, credit accumulation and credit transfer systems exist .
With the Skills Strategy , the OECD seeks to assist countries with improving economic and social outcomes through better skills and their effective utilisation. More specifically, the Skills Strategy is about improving: (1) responsiveness (ensuring that education/training providers can adapt efficiently to changing demand); (2) quality and efficiency in learning provision (ensuring that the right skills are acquired at the right time, right place and in the most effective mode); (3) flexibility in provision (allowing people to study/train what they want, when they want and how they want); (4) transferability of skills (such that skills gained are documented in a commonly accepted and understandable form); (5) ease of access (e.g. by reducing barriers to entry such as institutional rigidities, up-front fees and age restrictions, existence of a variety of entry and re-entry pathways); and (6) low costs of early exit (e.g. credit is granted for components of learning, modular provision, credit accumulation and credit transfer systems exist).
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A work programme with four pillars
How do we identify and assess essential skills for strong, sustainable and balanced growth and what are the factors driving the evolution of skill demand?
Is the right mix of skills being taught and learned and can employers find workers with the skills they need?
Are skills developed in effective, equitable, efficient and sustainable ways?
How can governments build strong coalitions with the business sector and social investors and find sustainable approaches to who should pay for what, when, where and how much?
Pillar 1
(EDU and LEED)
We have structured the work under four pillars: The first pillar deals with the question: How do we identify and assess essential skills for strong, sustainable and balanced growth and what are the factors driving the evolution of skill demand? Pillar 2: Is the right mix of skills being taught and learned and can employers find workers with the skills they need? Pillar 3: Are skills developed in effective, equitable, efficient and sustainable ways? Pillar 4: How can governments build strong coalitions with the business sector and social investors and find sustainable approaches to who should pay for what, when, where and how much?
Let me briefly lead you through these pillars.
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Pillar 1
Issues
often driven by technology
affecting the composition of aggregate skills demand
New types of jobs, driven by innovation –
in products and in services
Greater need for transferable skills, in part driven by greater labour mobility .
Work proposals
Skill demands in health and green jobs [ELS]
Economic and social outcomes of skills [PIAAC, CERI] .
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Pillar 1
Issues
Increasingly complex and dynamic labour-markets combined with depreciation of domain-specific knowledge require individuals to upgrade their skills more regularly leading to changing patterns of work and learning
Individual and aggregate skill mismatches can be associated with ineffective signalling of labour market demands to education providers and individuals but can also be the consequence of a lack of responsiveness on the part of education and training providers
Age training gaps, gender gaps
Work proposals
Understanding the impact of age on skills [ELS] .
A better understanding of the drivers of changes in skill demand within firms, occupations and countries will be crucial for countries to shift the focus of learning provision from supplying skills for today’s labour market to shaping future jobs. Labour markets are becoming increasingly complex and dynamic, are characterised by growing convergence of occupational sectors and rising job and occupational mobility. These forces combined with depreciation of domain-specific knowledge require individuals to upgrade their skills more regularly leading to changing patterns of work and learning. Skill mismatches occur at both the individual level – when a worker would be more productive in another position – as well as at the aggregate level – when there is a general surplus or shortage of specific skills. It is important in this context that policy makers are seeking to meet skills shortages, and not just labour shortages created by unattractive and low quality employment.
There are also ‘age training gaps’ and ‘gender training gaps’ with older workers and women often being less involved in training that their younger and male counterparts, respectively. Why do these gaps exist and how can be best addressed? What are the key institutional factors that can promote participation in training of older workers (e.g. wage-setting mechanisms; retirement policies)? What policy and institutions could reduce the gender training gap (e.g. family-friendly policies that encourage more continuity in working careers for women)?
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Pillar 1
(EDU and LEED)
Pillar 3: Are skills developed in effective, equitable and sustainable ways
Issues
Establishing efficient and fair ways of lifelong and lifewide learning, and ensuring responsiveness, quality and flexibility in provision
Incentive systems and support structures to enhancing skills through the formal educational system, in the work-place or through incentives addressed at the general population and training
Establishing an appropriate mix of academic and vocational learning in ways that reflect student preferences and employers’ needs, with vocational training providing immediate employability, but also basic transferable skills to support occupational mobility
Work proposals
Equity in access and educational mobility [PIAAC, PISA]
Utilising the skill potential of immigrants [ELS]
Developing innovation oriented skills [CERI] .
Third, with a rapidly rising demand for skills, countries can no longer simply rely on education and training systems that efficiently sort individuals, but need to improve their skill base throughout the population and to capitalise on the full potential of all individuals. This requires countries to ensure that skills are developed in effective, efficient and fair ways through lifelong and lifewide learning, and to ensure responsiveness, quality and flexibility in provision. The OECD could play a pathfinder role for countries to: (1) identify effective strategies for new ways of learning and skill provision; (2) improve the knowledge base about skill development; and (3) support systems of continuous innovation and feedback to develop knowledge of what policies work in which circumstances. This would also involve identifying the policy levers, incentive systems and support structures that lead to enhancing skills through the formal educational system, in the work-place or through incentives addressed at the general population. It would also include sustaining workplace training and meeting the increased demand for full-time vocational education and training.
There is also significant potential for peer-learning among countries with regard to how individuals learn differently, and differently at different stages of their lives, and what effective policies are to meet those individual needs of people, wherever they learn, to look into new ways to take learning to the learner, examine new forms of educational provision and new relationships between learners, providers, funders and social innovators.
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Pillar 1
(EDU and LEED)
Pillar 4: Who should pay for what, when, where and how much?
Issues
Building new relationships, networks and coalitions between learners, providers, governments, businesses, social investors and innovators that bring together the legitimacy, innovation, and resources that are needed to make lifelong learning a reality for all
Finding ways to encourage both employers and students to participate in workplace training, and ensuring that such training is of good quality, with effective quality assurance and contractual frameworks for apprentices
Mobilising time and money
Joining up local skill strategies .
Fourth, governments need to build new relationships, networks and coalitions between learners, providers, governments, businesses, social investors and innovators that bring together the legitimacy, innovation, and resources that are needed to make lifelong learning a reality for all. Much of this networking and engagement takes place at the level of local labour markets, and it is therefore at this level that relevant stakeholders interact and collaborate to gear education and training to local labour market needs, attract and retain talent, and ensure that disadvantaged groups are integrated into learning systems.
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PIAAC will…
in each country interview 5000 adults aged 16-65 in their homes and test their skills with a computer-adaptive assessment
collect information on the antecedents, outcomes and contexts of skill development and use
… in order to…
of the human capital stock
For high performers, show to what extent they are able to apply their skills to solve challenging problems requiring mastery of technology
For those with low literacy, show to what extent their problem is with performing basic reading functions or with understanding and application
show to what extent skills held by individuals are actually used at work and identify the role skills play in improving labour market prospects of at-risk populations
improve understanding of the labour market and social returns to education and training
help governments better understand how education and training systems can nurture these skills .
Country participation
PIAAC
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Measures of adult competencies
Test-based measures in areas where methodologies exist
Indirect measures in other areas that support PIAAC‘s policy objectives
Measures of key social and economic outcomes
Labour-market experience , status and transitions, earnings, adult learning, social outcomes
Measures of the
Surveyed: individuals
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PIAAC
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Moderate policy impact
economic and social outcomes
Equity and intergenerational mobility
What levels of skills do individuals and countries demonstrate, and how do these relate to educational attainment?
How well do education and training systems deliver in generating the required competencies
Improving the labour-market prospects of those at risk
aggregate
individual
x
(Skip examples)
Where does initial education leave us in terms of skill supply with their different forms of organisation of the education and training system?
Has the rapid growth in educational attainment translated into better foundation skills?
How do the results compare to those observed in earlier schooling (PISA)? How do people gain and lose skills as they grow older?
How will changes in the age structure of populations and aspects such as educational attainment feed through to the future talent pool?
How well can adults solve problems in technology-rich environments? How does this relate to the incidence and intensity of using information technology in and outside work
What can we learn about the impact of age on skills and skill utilisation, how has this changed over recent decades and the policy levers associated with this (separating biological effects of aging from differences in the experiences of cohorts over time)?
To what extent can and do skills play a role in levelling the playing field, both in terms of providing high quality education to all and giving access to higher education to those who are able and motivated to continue their schooling, irrespective of their social background?
Further analysis on intergenerational mobility will also be possible with the JRA measurement of what people do in their jobs
Description of the population with low skills, or special population groups such as immigrants, and interrelationships with labour-market outcomes.
What is the role of skills in explaining differences in labour-market outcomes between immigrant and native-born workers? Do skill differences depend on where human capital was acquired? Do immigrants receive different returns to these skills than observationally similar native-born workers?
Is education or skills mismatch mostly confined to youth early on in their professional careers and subsequently diminishes? Is mismatch important and does it translate into large earnings penalties? Have education and training systems in OECD countries shown sufficient adaptability in the face of changing skill demands or are skills mismatches endemic? How do task-based learning (JRA) and job-related training relate to the length of the working life? (but keep in mind that labour-market outcomes and training are snapshots in time whereas the measured skills are accumulated over the lifespan)
Labour force skills and the price of these skills are crucial to understand in the perspective of increasing global competition for jobs higher up in the skill hierarchy. PIAAC can tell us more about which cognitive and non-cognitive skills are important in particular.
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Source: International Adult Literacy and Life Skills Study (ALLS)
1 – less than upper secondary
2 – upper secondary
4 – tertiary education
The qualifications we acquired don’t tell us everything about the skills we have
Mean problem solving1,2 scores on a scale with range 0-500 points, by level of educational attainment, populations aged 16-65, 2003
Chart2
Norway
Norway
Norway
Norway
Norway
Norway
Norway
Norway
Norway
Norway
Norway
Norway
Norway
1
1
1
246.97
1
1
1
1
1
2
2
2
284.99
2
2
2
2
2
3
3
3
283.68
3
3
3
3
3
4
4
4
306.6
4
4
4
4
4
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
Switzerland
1
1
1
257.9
1
1
1
1
1
2
2
2
277.62
2
2
2
2
2
4
4
4
298.46
4
4
4
4
4
Canada
Canada
Canada
Canada
Canada
Canada
Canada
Canada
Canada
Canada
Canada
Canada
Canada
1
1
1
237.62
1
1
1
1
1
2
2
2
273.65
2
2
2
2
2
3
3
3
279.8
3
3
3
3
3
4
4
4
293.15
4
4
4
4
4
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
Bermuda
1
1
1
215.52
1
1
1
1
1
2
2
2
256.62
2
2
2
2
2
3
3
3
278.96
3
3
3
3
3
4
4
4
302.92
4
4
4
4
4
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
Italy
1
1
1
203.7
1
1
1
1
1
2
2
2
248.01
2
2
2
2
2
3
3
3
242.25
3
3
3
3
3
4
4
4
252.86
4
4
4
4
4
5
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Educational attainment and skills proficiencies
A. Mean numeracy scores on a scale with range 0-500 points, by level of educational attainment, populations aged 16-65, 2003
Graph data: Formulas based on data in orange block
VERTICAL SORT
Data imported from SAS
Percentiles
SORT 1
Study: ALL : if cntridx ne 3 , if edlev4 = 1 or edlev4 = 2 or edlev4 = 3 or edlev4 = 4,
Switzerland
288.19
Estimated Means for num by domain and cntridx edlev4, Based on 5 sets of Plausible Values and adjusted D.F.
Estimated 5 th Percentiles for num controlling for domain by cntridx edlev4, based on
1
184.53
46.68
27.31
2.24
2
2.24
25.29
50.5
261.76
Switzerland
Controlling for domain
5 sets of Plausible Values and 29 D.F.. Method based on Woodruff approach.
2
215.88
42.48
28.32
0.51
2
0.51
27.96
45.21
288.19
245.86
285.09
315.63
1.88
345.86
384.43
315.63
288.19
attainment
attainment
attainment
attainment
attainment
288.19
240.84
286.31
310.82
1.14
338.49
374.24
310.82
281.81
1
ALL
3
1
261.76
3.24
0
13.19
1
ALL
3
1
184.53
8.85
1
ALL
3
1
231.21
3.17
1
ALL
3
1
290.29
5.5
1
ALL
3
1
340.79
11.24
281.81
2
ALL
3
2
288.19
1.51
0
14
2
ALL
3
2
215.88
3.4
2
ALL
3
2
258.36
2.26
2
ALL
3
2
317.66
2.76
2
ALL
3
2
362.87
4.44
Canada
268.61
1
133.92
61.41
36.92
0.63
2
0.63
38.56
52.06
233.88
Canada
211.9
267.85
297.91
1.69
332.14
372.43
297.91
268.61
7
ALL
10
3
245.56
5.14
0
25.38
7
ALL
10
3
179.15
7.92
7
ALL
10
3
218.16
8.85
7
ALL
10
3
274.72
6.81
7
ALL
10
3
312
73.58
268.61
8
ALL
10
4
270.72
3.38
0
27.3
8
ALL
10
4
195.21
6.91
8
ALL
10
4
238.93
5.36
8
ALL
10
4
301.39
4.64
8
ALL
10
4
343.23
8.82
216.97
268.34
297.83
2.55
329.7
367.93
297.83
254.98
13
ALL
13
1
207.52
2.96
0
29
13
ALL
13
1
137.17
8.78
13
ALL
13
1
174.57
4.7
13
ALL
13
1
239.77
5.61
13
ALL
13
1
289.02
9.84
The countries are ranked by the mean of the numeracy score of those completed upper secondary.
254.98
14
ALL
13
2
253.5
2.83
0
19.21
14
ALL
13
2
170.1
5.63
14
ALL
13
2
222.3
3.91
14
ALL
13
2
284.49
4.82
14
ALL
13
2
337.51
4.7
Bermuda
253.50
15
ALL
13
3
270.08
2.26
0
19.84
15
ALL
13
3
193.86
6.12
15
ALL
13
3
237.96
3.35
15
ALL
13
3
302.05
3.25
15
ALL
13
3
348.94
4.99
1
137.17
37.4
29.99
1.96
2
1.96
29.29
49.25
207.52
Bermuda
224.82
277.8
307.63
1.51
339.9
380.91
307.63
253.50
19
ALL
14
3
244.44
4.37
0
29
19
ALL
14
3
162.85
14.86
19
ALL
14
3
213.1
10.27
19
ALL
14
3
278.56
4.67
19
ALL
14
3
319.18
5.69
253.50
20
ALL
14
4
297.83
2.55
0
29
20
ALL
14
4
216.97
7.06
20
ALL
14
4
268.34
3.31
20
ALL
14
4
329.7
3.09
20
ALL
14
4
367.93
3.94
2
177.83
45.33
27.5
0.8
2
0.8
28.32
41.88
252.46
195.21
238.93
270.72
3.38
301.39
343.23
270.72
252.46
Add the bar on the right hand side of the figure to show 5 levels of the literacy scale.
252.46
Add the graphic showing the 4 percentiles and the mean and 95% confidence interval below Figure 3-1a.
5
10
SUPERIMPOSE GRIDLINES FOR 225,275,325 & 475 only (delete all other gridlines)
Canada
1
0
2
0
3
0
4
0
1
0
2
0
3
0
4
0
Bermuda
1
0
2
0
3
0
4
0
Italy
1
0
2
0
3
0
4
0
The countries are ranked by the mean of the numeracy score of those completed upper secondary.
Fig3-1a
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Level
5
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Tab 3-1a
TABLE 3.1
A. Mean numeracy scores on a scale with range 0-500 points, by level of educational attainment, populations aged 16-65, 2003
Data copied from the yellow block in the figure worksheet
Level of educational attainment
224.8
(7.9)
277.8
(2.3)
307.6
(1.5)
339.9
(1.6)
380.9
(5.4)
224.82
7.88
277.8
2.27
307.63
1.51
339.9
1.58
380.91
5.39
Bermuda
Canada
211.9
(4.0)
267.9
(2.0)
297.9
(1.7)
332.1
(2.3)
372.4
(3.3)
211.9
4.02
267.85
2.02
297.91
1.69
332.14
2.26
372.43
3.25
Canada
195.2
(6.9)
238.9
(5.4)
270.7
(3.4)
301.4
(4.6)
343.2
(8.8)
Italy
195.21
6.91
238.93
5.36
270.72
3.38
301.39
4.64
343.23
8.82
Italy
240.8
(3.0)
286.3
(1.5)
310.8
(1.1)
338.5
(1.0)
374.2
(2.6)
Norway
Norway
240.84
3.02
286.31
1.52
310.82
1.14
338.49
1.01
374.24
2.62
Norway
245.9
(5.2)
285.1
(3.0)
315.6
(1.9)
345.9
(2.6)
384.4
(5.8)
Norway
Switzerland
217.0
(7.1)
268.3
(3.3)
297.8
(2.6)
329.7
(3.1)
367.9
(3.9)
245.86
5.18
285.09
3
315.63
1.88
345.86
2.63
384.43
5.75
Switzerland
Switzerland
216.97
7.06
268.34
3.31
297.83
2.55
329.7
3.09
367.93
3.94
5
10
Educational attainment and skills proficiencies
B. Mean problem solving1,2 scores on a scale with range 0-500 points, by level of educational attainment, populations aged 16-65, 2003
Graph data: Formulas based on data in orange block
VERTICAL SORT
Percentiles
SORT 1

2 or edlev4 = 3 or edlev4 = 4,
Study: ALL : if cntridx = 1 or cntridx = 10 or cntridx = 11 or cntridx = 13 , if edlev4 = 1 or edlev4 =
1
154.39
59.08
30.84
1.66
2
1.66
35.2
45.5
246.97
Norway
154.39
213.47
246.97
2.66
284.83
330.33
246.97
284.99
Estimated Means for prob by domain and cntridx edlev4, Based on 5 sets of Plausible Values and adjusted
2
207.63
47.63
27.51
1.22
2
1.22
29.52
39.37
284.99
207.63
255.26
284.99
2.22
316.73
356.1
284.99
284.99
D.F.
Estimated 5 th Percentiles for prob controlling for domain by cntridx edlev4, based on
3
212.95
45.36
21.18
3.19
2
3.19
23.1
39.47
283.68
Controlling for domain
4
230.23
51.95
23.28
0.14
2
0.14
27.44
35.99
306.6
230.23
282.18
306.6
1.14
335.18
371.17
306.6
284.99
284.99
Obs
Domain
cntridx
Educational
estimate
223.07
268.86
298.46
2.06
327.91
374.76
298.46
277.62
3
ALL
1
3
279.8
2.35
0
11.85
3
ALL
1
3
205.5
5.85
3
ALL
1
3
253.73
2.41
3
ALL
1
3
308.59
3.97
3
ALL
1
3
348.21
6.28
277.62
4
ALL
1
4
293.15
1.54
0
11.66
4
ALL
1
4
213.15
4.92
4
ALL
1
4
264.79
2.42
4
ALL
1
4
324.48
1.68
4
ALL
1
4
364.88
2.55
Canada
273.65
1
ALL
3
1
257.9
3.42
0
14
1
ALL
3
1
176.23
17.97
1
ALL
3
1
226.39
7.88
1
ALL
3
1
292.33
4.36
1
ALL
3
1
340.34
10.36
1
140.25
63.04
32.66
0.67
2
0.67
36.48
43.74
237.62
Canada
213.15
264.79
293.15
1.54
324.48
364.88
293.15
273.65
5
ALL
10
1
203.7
2.11
0
29
5
ALL
10
1
117.83
5.17
5
ALL
10
1
167.41
2.66
5
ALL
10
1
238.42
2.45
5
ALL
10
1
291.94
3.04
273.65
6
ALL
10
2
248.01
1.84
0
29
6
ALL
10
2
163.69
4.15
6
ALL
10
2
213.4
2.92
6
ALL
10
2
283.69
2.43
6
ALL
10
2
334.17
3.57
Bermuda
256.62
7
ALL
10
3
242.25
6.05
0
29
7
ALL
10
3
163.21
12.79
7
ALL
10
3
207.53
11.39
7
ALL
10
3
272.98
7.73
7
ALL
10
3
328.63
15.87
1
132.99
52.68
26.89
1.96
2
1.96
29.34
46.37
215.52
Bermuda
228.73
274.72
302.92
1.75
332.94
372.69
302.92
256.62
11
ALL
11
3
283.68
4.19
0
7.12
11
ALL
11
3
212.95
7.04
11
ALL
11
3
258.31
5.27
11
ALL
11
3
310.97
4.9
11
ALL
11
3
350.44
7.99
The countries are ranked by the mean of the problem solving score of those completed upper secondary.
256.62
12
ALL
11
4
306.6
1.14
0
13.39
12
ALL
11
4
230.23
5.79
12
ALL
11
4
282.18
1.34
12
ALL
11
4
335.18
1.43
12
ALL
11
4
371.17
1.99
Italy
248.01
13
ALL
13
1
215.52
2.96
0
29
13
ALL
13
1
132.99
11.73
13
ALL
13
1
185.67
3.46
13
ALL
13
1
247.82
4.65
13
ALL
13
1
294.19
8
1
117.83
49.58
34.18
1.11
2
1.11
32.61
53.52
203.7
Italy
117.83
167.41
203.7
2.11
238.42
291.94
203.7
248.01
14
ALL
13
2
256.62
2.94
0
29
14
ALL
13
2
175.98
5.21
14
ALL
13
2
224.4
4.68
14
ALL
13
2
290.81
3.23
14
ALL
13
2
335.37
6.22
1 United States did not field the problem solving skills domain.
2
163.69
49.71
32.77
0.84
2
0.84
33.84
50.48
248.01
163.21
207.53
242.25
6.05
272.98
328.63
242.25
248.01
16
ALL
13
4
302.92
1.75
0
12.85
16
ALL
13
4
228.73
5.41
16
ALL
13
4
274.72
2.72
16
ALL
13
4
332.94
2.84
16
ALL
13
4
372.69
5.93
2 The problem solving skills scores for Switzerland apply to the German and French speaking communities only since they did not field the problem solving skills domain in the Italian speaking community.
4
160.48
57.57
29.54
4.27
2
4.27
31.33
48.39
252.86
160.48
218.05
252.86
5.27
289.46
337.85
252.86
248.01
248.01
Type-setting:
1
2
189.52
245.4
273.65
1.82
306.13
346.18
273.65
3
1
176.23
226.39
257.9
3.42
292.33
340.34
257.9
Add the bar on the right hand side of the figure to show 5 levels of the literacy scale.
5
10
75
95
3
2
196.14
244.11
277.62
1.67
311.07
358.77
277.62
Norway
Add the graphic showing the 4 percentiles and the mean and 95% confidence interval below Figure 3-1b.
1
0
3
4
223.07
268.86
298.46
2.06
327.91
374.76
298.46
2
0
3
0
10
1
117.83
167.41
203.7
2.11
238.42
291.94
203.7
4
0
10
2
163.69
213.4
248.01
1.84
283.69
334.17
248.01
10
3
163.21
207.53
242.25
6.05
272.98
328.63
242.25
Switzerland
10
4
160.48
218.05
252.86
5.27
289.46
337.85
252.86
1
0
2
0
11
1
154.39
213.47
246.97
2.66
284.83
330.33
246.97
11
2
207.63
255.26
284.99
2.22
316.73
356.1
284.99
4
0
11
3
212.95
258.31
283.68
4.19
310.97
350.44
283.68
11
4
230.23
282.18
306.6
1.14
335.18
371.17
306.6
Canada
1
0
13
1
132.99
185.67
215.52
2.96
247.82
294.19
215.52
2
0
13
2
175.98
224.4
256.62
2.94
290.81
335.37
256.62
3
0
13
3
199.19
248.65
278.96
2.55
310.24
355.94
278.96
4
0
13
4
228.73
274.72
302.92
1.75
332.94
372.69
302.92
SUPERIMPOSE GRIDLINES FOR 225,275,325 & 475 only (delete all other gridlines)
Bermuda
1
0
2
0
3
0
4
0
Italy
1
0
2
0
3
0
4
0
The countries are ranked by the mean of the problem solving score of those completed upper secondary.
Sources: Adult Literacy and Life skills survey, 2003.
Fig3-1b
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
10
Tab 3-1b
TABLE 3.1
B. Mean problem solving1 scores on a scale with range 0-500 points, by level of educational attainment, populations aged 16-65, 2003
Data copied from the yellow block in the figure worksheet
Level of educational attainment
228.7
(5.4)
274.7
(2.7)
302.9
(1.8)
332.9
(2.8)
372.7
(5.9)
228.73
5.41
274.72
2.72
302.92
1.75
332.94
2.84
372.69
5.93
Bermuda
Canada
213.2
(4.9)
264.8
(2.4)
293.2
(1.5)
324.5
(1.7)
364.9
(2.6)
213.15
4.92
264.79
2.42
293.15
1.54
324.48
1.68
364.88
2.55
Canada
160.5
(14.9)
218.1
(6.1)
252.9
(5.3)
289.5
(6.4)
337.9
(7.2)
Italy
160.48
14.89
218.05
6.14
252.86
5.27
289.46
6.35
337.85
7.18
Italy
230.2
(5.8)
282.2
(1.3)
306.6
(1.1)
335.2
(1.4)
371.2
(2.0)
Norway
Norway
230.23
5.79
282.18
1.34
306.6
1.14
335.18
1.43
371.17
1.99
Norway
223.1
(4.3)
268.9
(3.0)
298.5
(2.1)
327.9
(2.9)
374.8
(10.3)
Norway
Switzerland2
Switzerland2
176.23
17.97
226.39
7.88
257.9
3.42
292.33
4.36
340.34
10.36
Switzerland2
1 United States did not field the problem solving skills domain.
Upper secondary
196.14
5.27
244.11
2.79
277.62
1.67
311.07
1.9
358.77
3.75
Switzerland2
Switzerland2
2 The problem solving skills scores for Switzerland apply to the German and French speaking communities only since they did not field the problem solving skills domain in the Italian speaking community.
Tertiary type B or higher
223.07
4.34
268.86
3.02
298.46
2.06
327.91
2.94
374.76
10.28
Switzerland2
Switzerland2
5
10
Skill make a difference for labour market outcomes
The probabilities of unemployed adults aged 16 to 65 to exit unemployment over a 52 week period, by low (Levels 1 and 2) and medium to high (Levels 3 and 4/5) skills, document scale, 2003
Source: International Adult Literacy and Life Skills Study (ALLS)
High skills
Low skills
High skills (Levels 3, 4 and 5)
Weeks
Probability
0.12368
0.16052
0.12368
0.16052
0.2531
0.3632
0.2531
0.3632
0.28068
0.39234
0.28068
0.39234
0.34458
0.51112
0.34458
0.51112
0.3495
0.52952
0.3495
0.52952
0.39506
0.57752
0.39506
0.57752
0.39744
0.58292
0.39744
0.58292
0.42012
0.6205
0.42012
0.6205
0.42336
0.62606
0.42336
0.62606
0.44754
0.64326
0.44754
0.64326
0.45286
0.647
0.45286
0.647
0.46784
0.6599
0.46784
0.6599
0.46878
0.66338
0.46878
0.66338
0.4739
0.67292
0.4739
0.67292
0.47462
0.67482
0.47462
0.67482
0.48386
0.68266
0.48386
0.68266
0.48544
0.68338
0.48544
0.68338
0.49402
0.6867
0.49402
0.6867
0.49508
0.68726
0.49508
0.68726
0.49974
0.69448
0.49974
0.69448
0.50012
0.69572
0.50012
0.69572
0.50218
0.70014
0.50218
0.70014
0.50244
0.70108
0.50244
0.70108
0.50244
0.70108
0.50244
0.70108
0.50244
0.70108
Probability of exiting unemployment by skills levels
The probabilities of unemployed adults aged 16-65 to exit unemployment over a 52 week period, by low (Levels 1 and 2) and medium to high (Levels 3 and 4/5) skills, document scale, 2003
Formula based on data in yellow block
Average of 5 PVs
(1-survivor function)
22
0.44754
41
0.49508
41
0.4997
43
0.5003
43
0.505
43
0.4971
43
0.4917
43
0.5006
43
0.5069
22
0.45286
43
0.49974
43
0.5001
46
0.4999
46
0.5047
46
0.4968
46
0.4914
46
0.5003
46
0.5062
24
0.45286
46
0.50012
46
0.5022
48
0.4978
48
0.5025
48
0.4947
48
0.4891
48
0.4988
48
0.504
24
0.46784
48
0.50218
48
0.5024
50
0.4976
50
0.5023
50
0.4945
50
0.4889
50
0.4986
50
0.5035
26
0.46784
50
0.50244
50
1
52
0.0000
52
0
52
0
52
0
52
0
52
0
26
0.46878
52
1
52
1
52
0
28
0.46878
2
0.2531
28
0.4739
4
0.28068
30
0.4739
7
0.34458
30
0.47462
9
0.3495
33
0.47462
11
0.39506
33
0.48386
13
0.39744
35
0.48386
15
0.42012
35
0.48544
17
0.42336
37
0.48544
20
0.44754
37
0.49402
22
0.45286
39
0.49402
24
0.46784
39
0.49508
26
0.46878
41
0.49508
28
0.4739
41
0.49974
30
0.47462
43
0.49974
33
0.48386
43
0.50012
35
0.48544
46
0.50012
37
0.49402
46
0.50218
39
0.49508
48
0.50218
41
0.49974
48
0.50244
43
0.50012
50
0.50244
46
0.50218
50
0.50244
48
0.50244
52
0.50244
50
1
52
0.50244
52
1
Survivor
Time
Function
High skills (Levels 3, 4 and 5)
0
0.12368
0.16052
2
0.12368
0.16052
2
0.2531
0.3632
4
0.2531
0.3632
4
0.28068
0.39234
7
0.28068
0.39234
7
0.34458
0.51112
9
0.34458
0.51112
9
0.3495
0.52952
11
0.3495
0.52952
11
0.39506
0.57752
13
0.39506
0.57752
13
0.39744
0.58292
15
0.39744
0.58292
15
0.42012
0.6205
17
0.42012
0.6205
17
0.42336
0.62606
20
0.42336
0.62606
20
0.44754
0.64326
22
0.44754
0.64326
22
0.45286
0.647
24
0.45286
0.647
24
0.46784
0.6599
26
0.46784
0.6599
26
0.46878
0.66338
28
0.46878
0.66338
28
0.4739
0.67292
30
0.4739
0.67292
30
0.47462
0.67482
33
0.47462
0.67482
33
0.48386
0.68266
35
0.48386
0.68266
35
0.48544
0.68338
37
0.48544
0.68338
37
0.49402
0.6867
39
0.49402
0.6867
39
0.49508
0.68726
41
0.49508
0.68726
41
0.49974
0.69448
43
0.49974
0.69448
43
0.50012
0.69572
46
0.50012
0.69572
46
0.50218
0.70014
48
0.50218
0.70014
48
0.50244
0.70108
50
0.50244
0.70108
50
0.50244
0.70108
52
0.50244
0.70108
52
0.50244
0.70108
TABLE 5.5
The probabilities of unemployed adults aged 16-65 to exit unemployment over a 52 week period, by low (Levels 1 and 2) and medium to high (Levels 3 and 4/5) skills, document scale, 2003
Low document skill
Weeks
Probability
Probability
0
0.124
0.161
2
0.253
0.363
4
0.281
0.392
7
0.345
0.511
9
0.350
0.530
11
0.395
0.578
13
0.397
0.583
15
0.420
0.621
17
0.423
0.626
20
0.448
0.643
22
0.453
0.647
24
0.468
0.660
26
0.469
0.663
28
0.474
0.673
30
0.475
0.675
33
0.484
0.683
35
0.485
0.683
37
0.494
0.687
39
0.495
0.687
41
0.500
0.694
43
0.500
0.696
46
0.502
0.700
48
0.502
0.701
50
0.502
0.701
52
0.502
0.701
*
*
State of play and opportunities to collaborate
PIAAC is now at a critical juncture of moving from an international strategy towards national implementation
Where we are…
Countries are currently administering a full trial of the assessment (with 1400 respondents)
A initial analysis plan has been prepared
Data will become available in December, we could establish joint projects to explore these data
We could collaborate on identifying institutional variables to explain differences in skill development and utilisation
… and what remains ahead
Main data collection (2011/2012)
Public release of results and database (2013)
*
*
Thank you !