Programme For International Student Assessment

It was first performed in 2000 and then repeated every three years. Its aim is to provide comparable data with a view to enabling countries to improve their education policies and outcomes. It measures problem solving and cognition.

The results of the 2022 data collection were released in December 2023.

PISA, and similar international standardised assessments of educational attainment are increasingly used in the process of education policymaking at both national and international levels.

PISA was conceived to set in a wider context the information provided by national monitoring of education system performance through regular assessments within a common, internationally agreed framework; by investigating relationships between student learning and other factors they can "offer insights into sources of variation in performances within and between countries".

Until the 1990s, few European countries used national tests. In the 1990s, ten countries / regions introduced standardised assessment, and since the early 2000s, ten more followed suit. By 2009, only five European education systems had no national student assessments.

The impact of these international standardised assessments in the field of educational policy has been significant, in terms of the creation of new knowledge, changes in assessment policy, and external influence over national educational policy more broadly.

Creation of new knowledge

Data from international standardised assessments can be useful in research on causal factors within or across education systems. Mons notes that the databases generated by large-scale international assessments have made it possible to carry out inventories and comparisons of education systems on an unprecedented scale* on themes ranging from the conditions for learning mathematics and reading, to institutional autonomy and admissions policies. They allow typologies to be developed that can be used for comparative statistical analyses of education performance indicators, thereby identifying the consequences of different policy choices. They have generated new knowledge about education: PISA findings have challenged deeply embedded educational practices, such as the early tracking of students into vocational or academic pathways.

• 79 countries and economies participated in the 2018 data collection.

Barroso and de Carvalho find that PISA provides a common reference connecting academic research in education and the political realm of public policy, operating as a mediator between different strands of knowledge from the realm of education and public policy. However, although the key findings from comparative assessments are widely shared in the research community the knowledge they create does not necessarily fit with government reform agendas; this leads to some inappropriate uses of assessment data.

Changes in national assessment policy

Emerging research suggests that international standardised assessments are having an impact on national assessment policy and practice. PISA is being integrated into national policies and practices on assessment, evaluation, curriculum standards and performance targets; its assessment frameworks and instruments are being used as best-practice models for improving national assessments; many countries have explicitly incorporated and emphasise PISA-like competencies in revised national standards and curricula; others use PISA data to complement national data and validate national results against an international benchmark.

External influence over national educational policy

PISA may influence national education policy choices in a variety of ways. Participation in international assessments like PISA has been linked to significant education policy changes and outcomes, such as higher student enrollments and education reforms. However, critics have argued that participation could lead to undesirable outcomes, such as higher repetition rates and narrowing of curricula. The impact of PISA may also vary according to the specific country context.

Policy-makers in most participating countries see PISA as an important indicator of system performance; PISA reports can define policy problems and set the agenda for national policy debate; policymakers seem to accept PISA as a valid and reliable instrument for internationally benchmarking system performance and changes over time; most countries—irrespective of whether they performed above, at, or below the average PISA score—have begun policy reforms in response to PISA reports.

Against this, impact on national education systems varies markedly. For example, in Germany, the results of the first PISA assessment caused the so-called 'PISA shock': a questioning of previously accepted educational policies; in a state marked by jealously guarded regional policy differences, it led ultimately to an agreement by all Länder to introduce common national standards and even an institutionalised structure to ensure that they were observed. In Hungary, by comparison, which shared similar conditions to Germany, PISA results have not led to significant changes in educational policy.

Because many countries have set national performance targets based on their relative rank or absolute PISA score, PISA assessments have increased the influence of their (non-elected) commissioning body, the OECD, as an international education monitor and policy actor, which implies an important degree of 'policy transfer' from the international to the national level; PISA in particular is having "an influential normative effect on the direction of national education policies". Thus, it is argued that the use of international standardised assessments has led to a shift towards international, external accountability for national system performance; Rey contends that PISA surveys, portrayed as objective, third-party diagnoses of education systems, actually serve to promote specific orientations on educational issues.

National policy actors refer to high-performing PISA countries to "help legitimise and justify their intended reform agenda within contested national policy debates". PISA data can be "used to fuel long-standing debates around pre-existing conflicts or rivalries between different policy options, such as in the French Community of Belgium". In such instances, PISA assessment data are used selectively: in public discourse governments often only use superficial features of PISA surveys such as country rankings and not the more detailed analyses. Rey (2010:145, citing Greger, 2008) notes that often the real results of PISA assessments are ignored as policymakers selectively refer to data in order to legitimise policies introduced for other reasons.

In addition, PISA's international comparisons can be used to justify reforms with which the data themselves have no connection; in Portugal, for example, PISA data were used to justify new arrangements for teacher assessment (based on inferences that were not justified by the assessments and data themselves); they also fed the government's discourse about the issue of pupils repeating a year, (which, according to research, fails to improve student results). In Finland, the country's PISA results (that are in other countries deemed to be excellent) were used by Ministers to promote new policies for 'gifted' students. Such uses and interpretations often assume causal relationships that cannot legitimately be based upon PISA data which would normally require fuller investigation through qualitative in-depth studies and longitudinal surveys based on mixed quantitative and qualitative methods, which politicians are often reluctant to fund.

Recent decades have witnessed an expansion in the uses of PISA and similar assessments, from assessing students' learning, to connecting "the educational realm (their traditional remit) with the political realm". This raises the question of whether PISA data are sufficiently robust to bear the weight of the major policy decisions that are being based upon them, for, according to Breakspear, PISA data have "come to increasingly shape, define and evaluate the key goals of the national / federal education system". This implies that those who set the PISA tests – e.g. in choosing the content to be assessed and not assessed – are in a position of considerable power to set the terms of the education debate, and to orient educational reform in many countries around the globe.

PISA stands in a tradition of international school studies, undertaken since the late 1950s by the International Association for the Evaluation of Educational Achievement (IEA). Much of PISA's methodology follows the example of the Trends in International Mathematics and Science Study (TIMSS, started in 1995), which in turn was much influenced by the U.S. National Assessment of Educational Progress (NAEP). The reading component of PISA is inspired by the IEA's Progress in International Reading Literacy Study (PIRLS).

PISA aims to test literacy the competence of students in three fields: reading, mathematics, science on an indefinite scale.

The PISA mathematics literacy test asks students to apply their mathematical knowledge to solve problems set in real-world contexts. To solve the problems students must activate a number of mathematical competencies as well as a broad range of mathematical content knowledge. TIMSS, on the other hand, measures more traditional classroom content such as an understanding of fractions and decimals and the relationship between them (curriculum attainment). PISA claims to measure education's application to real-life problems and lifelong learning (workforce knowledge).

In the reading test, "OECD/PISA does not measure the extent to which 15-year-old students are fluent readers or how competent they are at word recognition tasks or spelling." Instead, they should be able to "construct, extend and reflect on the meaning of what they have read across a wide range of continuous and non-continuous texts."

PISA also assesses students in innovative domains. In 2012 and 2015 in addition to reading, mathematics and science, they were tested in collaborative problem solving. In 2018 the additional innovative domain was global competence.

PISA is sponsored, governed, and coordinated by the OECD, but paid for by participating countries.^{[citation needed]}

Sampling

The students tested by PISA are aged between 15 years and 3 months and 16 years and 2 months at the beginning of the assessment period. The school year pupils are in is not taken into consideration. Only students at school are tested, not home-schoolers. In PISA 2006, however, several countries also used a grade-based sample of students. This made it possible to study how age and school year interact.

To fulfill OECD requirements, each country must draw a sample of at least 5,000 students. In small countries like Iceland and Luxembourg, where there are fewer than 5,000 students per year, an entire age cohort is tested. Some countries used much larger samples than required to allow comparisons between regions.

Test

 

Each student takes a two-hour computer based test. Part of the test is multiple-choice and part involves fuller answers. There are six and a half hours of assessment material, but each student is not tested on all the parts. Following the cognitive test, participating students spend nearly one more hour answering a questionnaire on their background including learning habits, motivation, and family. School directors fill in a questionnaire describing school demographics, funding, etc. In 2012 the participants were, for the first time in the history of large-scale testing and assessments, offered a new type of problem, i.e. interactive (complex) problems requiring exploration of a novel virtual device.

In selected countries, PISA started experimentation with computer adaptive testing.

National add-ons

Countries are allowed to combine PISA with complementary national tests.

Germany does this in a very extensive way: On the day following the international test, students take a national test called PISA-E (E=Ergänzung=complement). Test items of PISA-E are closer to TIMSS than to PISA. While only about 5,000 German students participate in the international and the national test, another 45,000 take the national test only. This large sample is needed to allow an analysis by federal states. Following a clash about the interpretation of 2006 results, the OECD warned Germany that it might withdraw the right to use the "PISA" label for national tests.

Data scaling

From the beginning, PISA has been designed with one particular method of data analysis in mind. Since students work on different test booklets, raw scores must be 'scaled' to allow meaningful comparisons. Scores are thus scaled so that the OECD average in each domain (mathematics, reading and science) is 500 and the standard deviation is 100. This is true only for the initial PISA cycle when the scale was first introduced, though, subsequent cycles are linked to the previous cycles through IRT scale linking methods.

This generation of proficiency estimates is done using a latent regression extension of the Rasch model, a model of item response theory (IRT), also known as conditioning model or population model. The proficiency estimates are provided in the form of so-called plausible values, which allow unbiased estimates of differences between groups. The latent regression, together with the use of a Gaussian prior probability distribution of student competencies allows estimation of the proficiency distributions of groups of participating students. The scaling and conditioning procedures are described in nearly identical terms in the Technical Reports of PISA 2000, 2003, 2006. NAEP and TIMSS use similar scaling methods.

All PISA results are tabulated by country; recent PISA cycles have separate provincial or regional results for some countries. Most public attention concentrates on just one outcome: the mean scores of countries and their rankings of countries against one another. In the official reports, however, country-by-country rankings are given not as simple league tables but as cross tables indicating for each pair of countries whether or not mean score differences are statistically significant (unlikely to be due to random fluctuations in student sampling or in item functioning). In favorable cases, a difference of 9 points is sufficient to be considered significant.^{[citation needed]}

PISA never combines mathematics, science and reading domain scores into an overall score. However, commentators have sometimes combined test results from all three domains into an overall country ranking. Such meta-analysis is not endorsed by the OECD, although official summaries sometimes use scores from a testing cycle's principal domain as a proxy for overall student ability.

PISA 2018 ranking summary

The results of PISA 2018 were presented on 3 December 2019, which included data for around 600,000 participating students in 79 countries and economies, with China's economic area of Beijing, Shanghai, Jiangsu and Zhejiang emerging as the top performer in all categories. Note that this does not represent the entirety of mainland China. Reading results for Spain were not released due to perceived anomalies.

Mathematics	Science	Reading
1   China (B-S-J-Z) 591 2   Singapore 569 3   Macau 558 4   Hong Kong 551 5   Taiwan 531 6   Japan 527 7   South Korea 526 8   Estonia 523 9   Netherlands 519 10   Poland 516 11    Switzerland 515 12   Canada 512 13   Denmark 509 13   Slovenia 509 15   Belgium 508 16   Finland 507 17   Sweden 502 17   United Kingdom 502 19   Norway 501 20   Germany 500 20   Ireland 500 22   Czech Republic 499 22   Austria 499 24   Latvia 496 24   Vietnam 496 26   France 495 26   Iceland 495 28   New Zealand 494 29   Portugal 492 30   Australia 491 International Average (OECD) 489 31   Russia 488 32   Italy 487 33   Slovakia 486 34   Luxembourg 483 35   Lithuania 481 35   Spain 481 35   Hungary 481 38   United States 478 39   Belarus 472 39   Malta 472 41   Croatia 464 42   Israel 463 43   Turkey 454 44   Ukraine 453 45   Cyprus 451 45   Greece 451 47   Serbia 448 48   Malaysia 440 49   Albania 437 50   Bulgaria 436 51   United Arab Emirates 435 52   Brunei 430 52   Montenegro 430 52   Romania 430 55   Kazakhstan 423 56   Moldova 421 57   Azerbaijan 420 58   Thailand 419 59   Uruguay 418 60   Chile 417 61   Qatar 414 62   Mexico 409 63   Bosnia and Herzegovina 406 64   Costa Rica 402 65   Jordan 400 65   Peru 400 67   Georgia 398 68   North Macedonia 394 69   Lebanon 393 70   Colombia 391 71   Brazil 384 72   Argentina 379 72   Indonesia 379 74   Saudi Arabia 373 75   Morocco 368 76   Kosovo 366 77   Panama 353 77   Philippines 353 79   Dominican Republic 325	1   China (B-S-J-Z) 590 2   Singapore 551 3   Macau 544 4   Vietnam 543 5   Estonia 530 6   Japan 529 7   Finland 522 8   South Korea 519 9   Canada 518 10   Hong Kong 517 11   Taiwan 516 12   Poland 511 13   New Zealand 508 14   Slovenia 507 15   United Kingdom 505 16   Australia 503 16   Germany 503 16   Netherlands 503 19   United States 502 20   Belgium 499 20   Sweden 499 22   Czech Republic 497 23   Ireland 496 24    Switzerland 495 25   Denmark 493 25   France 493 27   Portugal 492 28   Austria 490 28   Norway 490 International Average (OECD) 489 30   Latvia 487 31   Spain 483 32   Lithuania 482 33   Hungary 481 34   Russia 478 35   Luxembourg 477 36   Iceland 475 37   Croatia 472 38   Belarus 471 39   Ukraine 469 40   Italy 468 40   Turkey 468 42   Slovakia 464 43   Israel 462 44   Malta 457 45   Greece 452 46   Chile 444 47   Serbia 440 48   Cyprus 439 49   Malaysia 438 50   United Arab Emirates 434 51   Brunei 431 52   Jordan 429 53   Moldova 428 54   Romania 426 54   Thailand 426 54   Uruguay 426 57   Bulgaria 424 58   Mexico 419 58   Qatar 419 60   Albania 417 61   Costa Rica 416 62   Montenegro 415 63   Colombia 413 63   North Macedonia 413 65   Argentina 404 65   Brazil 404 65   Peru 404 68   Azerbaijan 398 68   Bosnia and Herzegovina 398 70   Kazakhstan 397 71   Indonesia 396 72   Saudi Arabia 386 73   Lebanon 384 74   Georgia 383 75   Morocco 377 76   Kosovo 365 76   Panama 365 78   Philippines 357 79   Dominican Republic 336	1   China (B-S-J-Z) 555 2   Singapore 549 3   Macau 525 4   Hong Kong 524 5   Estonia 523 6   Canada 520 6   Finland 520 8   Ireland 518 9   South Korea 514 10   Poland 512 11   New Zealand 506 11   Sweden 506 13   United States 505 13   Vietnam 505 15   Japan 504 15   United Kingdom 504 17   Australia 503 17   Taiwan 503 19   Denmark 501 20   Norway 499 21   Germany 498 22   Slovenia 495 23   Belgium 493 23   France 493 25   Portugal 492 26   Czech Republic 490 International Average (OECD) 487 27   Netherlands 485 28   Austria 484 28    Switzerland 484 30   Croatia 479 30   Latvia 479 30   Russia 479 33   Hungary 476 33   Italy 476 33   Lithuania 476 36   Belarus 474 36   Iceland 474 38   Israel 470 38   Luxembourg 470 40   Turkey 466 40   Ukraine 466 42   Slovakia 458 43   Greece 457 44   Chile 452 45   Malta 448 46   Serbia 439 47   United Arab Emirates 432 48   Romania 428 49   Uruguay 427 50   Costa Rica 426 51   Cyprus 424 51   Moldova 424 53   Montenegro 421 54   Bulgaria 420 54   Mexico 420 56   Jordan 419 57   Malaysia 415 58   Brazil 413 59   Colombia 412 60   Brunei 408 61   Qatar 407 62   Albania 405 63   Bosnia and Herzegovina 403 64   Argentina 402 65   Peru 401 66   Saudi Arabia 399 67   North Macedonia 393 67   Thailand 393 69   Azerbaijan 389 70   Kazakhstan 387 71   Georgia 380 72   Panama 377 73   Indonesia 371 74   Morocco 359 75   Kosovo 353 75   Lebanon 353 77   Dominican Republic 342 78   Philippines 340

Rankings comparison 2000–2015

Mathematics
Country	2015		2012		2009		2006		2003		2000
	Score	Rank	Score	Rank	Score	Rank	Score	Rank	Score	Rank	Score	Rank
International Average (OECD)	490	—	494	—	495	—	494	—	499	—	492	—
Albania	413	57	394	54	377	53	—	—	—	—	381	33
Algeria	360	72	—	—	—	—	—	—	—	—	—	—
Argentina	409	58	—	—	—	—	—	—	—	—	388	30
Australia	494	25	504	17	514	13	520	12	524	10	533	6
Austria	497	20	506	16	496	22	505	17	506	18	503	12
China B-S-J-G	531	6	—	—	—	—	—	—	—	—	—	—
Belgium	507	15	515	13	515	12	520	11	529	7	520	8
Brazil	377	68	389	55	386	51	370	50	356	39	334	35
Bulgaria	441	47	439	43	428	41	413	43	—	—	430	28
Argentina CABA	456	43	418	49	—	—	—	—	—	—	—	—
Canada	516	10	518	11	527	8	527	7	532	6	533	6
Chile	423	50	423	47	421	44	411	44	—	—	384	32
Taiwan	542	4	560	3	543	4	549	1	—	—	—	—
Colombia	390	64	376	58	381	52	370	49	—	—	—	—
Costa Rica	400	62	407	53	—	—	—	—	—	—	—	—
Croatia	464	41	471	38	460	38	467	34	—	—	—	—
Cyprus	437	48	—	—	—	—	—	—	—	—	—	—
Czech Republic	492	28	499	22	493	25	510	15	516	12	498	14
Denmark	511	12	500	20	503	17	513	14	514	14	514	10
Dominican Republic	328	73	—	—	—	—	—	—	—	—	—	—
Estonia	520	9	521	9	512	15	515	13	—	—	—	—
Finland	511	13	519	10	541	5	548	2	544	2	536	5
France	493	26	495	23	497	20	496	22	511	15	517	9
Macedonia	371	69	—	—	—	—	—	—	—	—	381	33
Georgia	404	60	—	—	—	—	—	—	—	—	—	—
Germany	506	16	514	14	513	14	504	19	503	19	490	16
Greece	454	44	453	40	466	37	459	37	445	32	447	24
Hong Kong	548	2	561	2	555	2	547	3	550	1	560	1
Hungary	477	37	477	37	490	27	491	26	490	25	488	17
Iceland	488	31	493	25	507	16	506	16	515	13	514	10
Indonesia	386	66	375	60	371	55	391	47	360	37	367	34
Ireland	504	18	501	18	487	30	501	21	503	20	503	12
Israel	470	39	466	39	447	39	442	38	—	—	433	26
Italy	490	30	485	30	483	33	462	36	466	31	457	22
Japan	532	5	536	6	529	7	523	9	534	5	557	2
Jordan	380	67	386	57	387	50	384	48	—	—	—	—
Kazakhstan	460	42	432	45	405	48	—	—	—	—	—	—
South Korea	524	7	554	4	546	3	547	4	542	3	547	3
Kosovo	362	71	—	—	—	—	—	—	—	—	—	—
Latvia	482	34	491	26	482	34	486	30	483	27	463	21
Lebanon	396	63	—	—	—	—	—	—	—	—	—	—
Lithuania	478	36	479	35	477	35	486	29	—	—	—	—
Luxembourg	486	33	490	27	489	28	490	27	493	23	446	25
Macau	544	3	538	5	525	10	525	8	527	8	—	—
Malaysia	446	45	421	48	—	—	—	—	—	—	—	—
Malta	479	35	—	—	—	—	—	—	—	—	—	—
Mexico	408	59	413	50	419	46	406	45	385	36	387	31
Moldova	420	52	—	—	—	—	—	—	—	—	—	—
Montenegro	418	54	410	51	403	49	399	46	—	—	—	—
Netherlands	512	11	523	8	526	9	531	5	538	4	—	—
New Zealand	495	21	500	21	519	11	522	10	523	11	537	4
Norway	502	19	489	28	498	19	490	28	495	22	499	13
Peru	387	65	368	61	365	57	—	—	—	—	292	36
Poland	504	17	518	12	495	23	495	24	490	24	470	20
Portugal	492	29	487	29	487	31	466	35	466	30	454	23
Qatar	402	61	376	59	368	56	318	52	—	—	—	—
Romania	444	46	445	42	427	42	415	42	—	—	426	29
Russia	494	23	482	32	468	36	476	32	468	29	478	18
Singapore	564	1	573	1	562	1	—	—	—	—	—	—
Slovakia	475	38	482	33	497	21	492	25	498	21	—	—
Slovenia	510	14	501	19	501	18	504	18	—	—	—	—
Spain	486	32	484	31	483	32	480	31	485	26	476	19
Sweden	494	24	478	36	494	24	502	20	509	16	510	11
Switzerland	521	8	531	7	534	6	530	6	527	9	529	7
Thailand	415	56	427	46	419	45	417	41	417	35	432	27
Trinidad and Tobago	417	55	—	—	414	47	—	—	—	—	—	—
Tunisia	367	70	388	56	371	54	365	51	359	38	—	—
Turkey	420	51	448	41	445	40	424	40	423	33	—	—
United Arab Emirates	427	49	434	44	—	—	—	—	—	—	—	—
United Kingdom	492	27	494	24	492	26	495	23	508	17	529	7
United States	470	40	481	34	487	29	474	33	483	28	493	15
Uruguay	418	53	409	52	427	43	427	39	422	34	—	—
Vietnam	495	22	511	15	—	—	—	—	—	—	—	—

Science
Country	2015		2012		2009		2006
	Score	Rank	Score	Rank	Score	Rank	Score	Rank
International Average (OECD)	493	—	501	—	501	—	498	—
Albania	427	54	397	58	391	54	—	—
Algeria	376	72	—	—	—	—	—	—
Argentina	432	52	—	—	—	—	—	—
Australia	510	14	521	14	527	9	527	8
Austria	495	26	506	21	494	28	511	17
China B-S-J-G	518	10	—	—	—	—	—	—
Belgium	502	20	505	22	507	19	510	18
Brazil	401	66	402	55	405	49	390	49
Bulgaria	446	46	446	43	439	42	434	40
Argentina CABA	475	38	425	49	—	—	—	—
Canada	528	7	525	9	529	7	534	3
Chile	447	45	445	44	447	41	438	39
Taiwan	532	4	523	11	520	11	532	4
Colombia	416	60	399	56	402	50	388	50
Costa Rica	420	58	429	47	—	—	—	—
Croatia	475	37	491	32	486	35	493	25
Cyprus	433	51	—	—	—	—	—	—
Czech Republic	493	29	508	20	500	22	513	14
Denmark	502	21	498	25	499	24	496	23
Dominican Republic	332	73	—	—	—	—	—	—
Estonia	534	3	541	5	528	8	531	5
Finland	531	5	545	4	554	1	563	1
France	495	27	499	24	498	25	495	24
Macedonia	384	70	—	—	—	—	—	—
Georgia	411	63	—	—	—	—	—	—
Germany	509	16	524	10	520	12	516	12
Greece	455	44	467	40	470	38	473	37
Hong Kong	523	9	555	1	549	2	542	2
Hungary	477	35	494	30	503	20	504	20
Iceland	473	39	478	37	496	26	491	26
Indonesia	403	65	382	60	383	55	393	48
Ireland	503	19	522	13	508	18	508	19
Israel	467	40	470	39	455	39	454	38
Italy	481	34	494	31	489	33	475	35
Japan	538	2	547	3	539	4	531	6
Jordan	409	64	409	54	415	47	422	43
Kazakhstan	456	43	425	48	400	53	—	—
South Korea	516	11	538	6	538	5	522	10
Kosovo	378	71	—	—	—	—	—	—
Latvia	490	31	502	23	494	29	490	27
Lebanon	386	68	—	—	—	—	—	—
Lithuania	475	36	496	28	491	31	488	31
Luxembourg	483	33	491	33	484	36	486	33
Macau	529	6	521	15	511	16	511	16
Malaysia	443	47	420	50	—	—	—	—
Malta	465	41	—	—	—	—	—	—
Mexico	416	61	415	52	416	46	410	47
Moldova	428	53	—	—	—	—	—	—
Montenegro	411	62	410	53	401	51	412	46
Netherlands	509	17	522	12	522	10	525	9
New Zealand	513	12	516	16	532	6	530	7
Norway	498	24	495	29	500	23	487	32
Peru	397	67	373	61	369	57	—	—
Poland	501	22	526	8	508	17	498	22
Portugal	501	23	489	34	493	30	474	36
Qatar	418	59	384	59	379	56	349	52
Romania	435	50	439	46	428	43	418	45
Russia	487	32	486	35	478	37	479	34
Singapore	556	1	551	2	542	3	—	—
Slovakia	461	42	471	38	490	32	488	29
Slovenia	513	13	514	18	512	15	519	11
Spain	493	30	496	27	488	34	488	30
Sweden	493	28	485	36	495	27	503	21
Switzerland	506	18	515	17	517	13	512	15
Thailand	421	57	444	45	425	45	421	44
Trinidad and Tobago	425	56	—	—	410	48	—	—
Tunisia	386	69	398	57	401	52	386	51
Turkey	425	55	463	41	454	40	424	42
United Arab Emirates	437	48	448	42	—	—	—	—
United Kingdom	509	15	514	19	514	14	515	13
United States	496	25	497	26	502	21	489	28
Uruguay	435	49	416	51	427	44	428	41
Vietnam	525	8	528	7	—	—	—	—

Reading
Country	2015		2012		2009		2006		2003		2000
	Score	Rank	Score	Rank	Score	Rank	Score	Rank	Score	Rank	Score	Rank
International Average (OECD)	493	—	496	—	493	—	489	—	494	—	493	—
Albania	405	63	394	58	385	55	—	—	—	—	349	39
Algeria	350	71	—	—	—	—	—	—	—	—	—	—
Argentina	425	56	—	—	—	—	—	—	—	—	—	—
Australia	503	16	512	12	515	8	513	7	525	4	528	4
Austria	485	33	490	26	470	37	490	21	491	22	492	19
China B-S-J-G	494	27	—	—	—	—	—	—	—	—	—	—
Belgium	499	20	509	16	506	10	501	11	507	11	507	11
Brazil	407	62	407	52	412	49	393	47	403	36	396	36
Bulgaria	432	49	436	47	429	42	402	43	—	—	430	32
Argentina CABA	475	38	429	48	—	—	—	—	—	—	—	—
Canada	527	3	523	7	524	5	527	4	528	3	534	2
Chile	459	42	441	43	449	41	442	37	—	—	410	35
Taiwan	497	23	523	8	495	21	496	15	—	—	—	—
Colombia	425	57	403	54	413	48	385	49	—	—	—	—
Costa Rica	427	52	441	45	—	—	—	—	—	—	—	—
Croatia	487	31	485	33	476	34	477	29	—	—	—	—
Cyprus	443	45	—	—	—	—	—	—	—	—	—	—
Czech Republic	487	30	493	24	478	32	483	25	489	24	492	20
Denmark	500	18	496	23	495	22	494	18	492	19	497	16
Dominican Republic	358	69	—	—	—	—	—	—	—	—	—	—
Estonia	519	6	516	10	501	12	501	12	—	—	—	—
Finland	526	4	524	5	536	2	547	2	543	1	546	1
France	499	19	505	19	496	20	488	22	496	17	505	14
Macedonia	352	70	—	—	—	—	—	—	—	—	373	37
Georgia	401	65	—	—	—	—	—	—	—	—	—	—
Germany	509	11	508	18	497	18	495	17	491	21	484	22
Greece	467	41	477	38	483	30	460	35	472	30	474	25
Hong Kong	527	2	545	1	533	3	536	3	510	9	525	6
Hungary	470	40	488	28	494	24	482	26	482	25	480	23
Iceland	482	35	483	35	500	15	484	23	492	20	507	12
Indonesia	397	67	396	57	402	53	393	46	382	38	371	38
Ireland	521	5	523	6	496	19	517	6	515	6	527	5
Israel	479	37	486	32	474	35	439	39	—	—	452	29
Italy	485	34	490	25	486	27	469	32	476	29	487	21
Japan	516	8	538	3	520	7	498	14	498	14	522	9
Jordan	408	61	399	55	405	51	401	44	—	—	—	—
Kazakhstan	427	54	393	59	390	54	—	—	—	—	—	—
South Korea	517	7	536	4	539	1	556	1	534	2	525	7
Kosovo	347	72	—	—	—	—	—	—	—	—	—	—
Latvia	488	29	489	27	484	28	479	27	491	23	458	28
Lebanon	347	73	—	—	—	—	—	—	—	—	—	—
Lithuania	472	39	477	37	468	38	470	31	—	—	—	—
Luxembourg	481	36	488	30	472	36	479	28	479	27	441	30
Macau	509	12	509	15	487	26	492	20	498	15	—	—
Malaysia	431	50	398	56	—	—	—	—	—	—	—	—
Malta	447	44	—	—	—	—	—	—	—	—	—	—
Mexico	423	58	424	49	425	44	410	42	400	37	422	34
Moldova	416	59	—	—	—	—	—	—	—	—	—	—
Montenegro	427	55	422	50	408	50	392	48	—	—	—	—
Netherlands	503	15	511	13	508	9	507	10	513	8	‡	‡
New Zealand	509	10	512	11	521	6	521	5	522	5	529	3
Norway	513	9	504	20	503	11	484	24	500	12	505	13
Peru	398	66	384	61	370	57	—	—	—	—	327	40
Poland	506	13	518	9	500	14	508	8	497	16	479	24
Portugal	498	21	488	31	489	25	472	30	478	28	470	26
Qatar	402	64	388	60	372	56	312	51	—	—	—	—
Romania	434	47	438	46	424	45	396	45	—	—	428	33
Russia	495	26	475	40	459	40	440	38	442	32	462	27
Singapore	535	1	542	2	526	4	—	—	—	—	—	—
Slovakia	453	43	463	41	477	33	466	33	469	31	—	—
Slovenia	505	14	481	36	483	29	494	19	—	—	—	—
Spain	496	25	488	29	481	31	461	34	481	26	493	18
Sweden	500	17	483	34	497	17	507	9	514	7	516	10
Switzerland	492	28	509	14	501	13	499	13	499	13	494	17
Thailand	409	60	441	44	421	46	417	40	420	35	431	31
Trinidad and Tobago	427	53	—	—	416	47	—	—	—	—	—	—
Tunisia	361	68	404	53	404	52	380	50	375	39	—	—
Turkey	428	51	475	39	464	39	447	36	441	33	—	—
United Arab Emirates	434	48	442	42	—	—	—	—	—	—	—	—
United Kingdom	498	22	499	21	494	23	495	16	507	10	523	8
United States	497	24	498	22	500	16	—	—	495	18	504	15
Uruguay	437	46	411	51	426	43	413	41	434	34	—	—
Vietnam	487	32	508	17	—	—	—	—	—	—	—	—