Programme for International Student Assessment

"PISA" redirects here. For other uses, seePisa (disambiguation).

Programme for International Student Assessment

Abbreviation	PISA
Formation	1997
Purpose	Comparison of education attainment across the world
Headquarters	OECD Headquarters
Location	2 rueAndré Pascal,75775 Paris Cedex 16
Region served	World
Membership	79 government education departments
Official language	English and French
Head of the Early Childhood and Schools Division	Yuri Belfali
Main organ	PISA Governing Body (Chair – Michele Bruniges)
Parent organization	OECD
Website	www.oecd.org/pisa/

PISA average Mathematics scores (2018)

PISA average Science scores (2018)

PISA average Reading scores (2018)

TheProgramme for International Student Assessment(PISA) is a worldwide study by theOrganisation for Economic Co-operation and Development(OECD) in member and non-member nations intended to evaluate educational systems by measuring 15-year-old school pupils' scholastic performance on mathematics, science, and reading.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.

Influence and impact

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 ofnew knowledge,changes inassessment policy,andexternal influence over national educational policymore 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 communitythe 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.

Framework

PISA stands in a tradition of international school studies, undertaken since the late 1950s by theInternational Association for the Evaluation of Educational Achievement(IEA). Much of PISA's methodology follows the example of theTrends 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'sProgress in International Reading Literacy Study(PIRLS).

PISA aims to testliteracythe 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.

Implementation

PISA is sponsored, governed, and coordinated by the OECD, but paid for by participating countries.

Method of testing

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 likeIcelandandLuxembourg,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

PISA test documents on a school table (Neues Gymnasium, Oldenburg, Germany, 2006)

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 withcomputer 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 thestandard deviationis 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 theRasch model,a model ofitem 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 Gaussianprior probabilitydistribution 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.

Ranking results

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 arestatistically 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.

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 2022 ranking summary

The results of PISA 2022 were presented on 5 December 2023, which included data for around 700,000 participating students in 81 countries and economies, withSingaporeemerging as the top performer in all categories.

BothLebanonand the Chinese provinces/municipalities ofBeijing,Shanghai,JiangsuandZhejiangwere participants in these edition, but their results were not published as they were not able to fully collect data because of COVID restrictions.

Because of theRussian full-scale invasion of Ukraine,only 18 of 27 Ukrainian regions had their data collected, thus the results are not representative of the following regions:Dnipropetrovsk Oblast,Donetsk Oblast,Kharkiv Oblast,Luhansk Oblast,Zaporizhzhia Oblast,Kherson Oblast,Mykolaiv Oblast,theAutonomous Republic of Crimeaand the city ofSevastopol.

Mathematics	Science	Reading
1 Singapore 575 2 Macau 552 3 Chinese Taipei 547 4 Hong Kong 540 5 Japan 536 6 South Korea 527 7 Estonia 510 8 Switzerland 508 9 Canada 497 10 Netherlands 493 11 Ireland 492 12 Belgium 489 13 Denmark 489 14 United Kingdom 489 15 Poland 489 16 Australia 487 17 Austria 487 18 Czech Republic 487 19 Slovenia 485 20 Finland 484 21 Latvia 483 22 Sweden 482 23 New Zealand 479 24 Germany 475 25 Lithuania 475 26 France 474 27 Spain 473 28 Hungary 473 29 Portugal 472 International Average (OECD) 472 30 Italy 471 31 Vietnam 469 32 Norway 468 33 Malta 466 34 United States 465 35 Slovakia 464 36 Croatia 463 37 Iceland 459 38 Israel 458 39 Turkey 453 40 Brunei 442 41 Ukraine 441 42 Serbia 440 43 United Arab Emirates 431 44 Greece 430 45 Romania 428 46 Kazakhstan 425 47 Mongolia 425 48 Cyprus 418 49 Bulgaria 417 50 Moldova 417 51 Qatar 414 52 Chile 412 53 Uruguay 409 54 Malaysia 409 55 Montenegro 406 56 Azerbaijan 397 57 Mexico 395 58 Thailand 485 59 Peru 391 60 Georgia 390 61 North Macedonia 389 62 Saudi Arabia 389 63 Costa Rica 385 64 Colombia 383 65 Brazil 379 66 Argentina 378 67 Jamaica 377 68 Albania 368 69 Indonesia 366 70 Palestinian Authority 366 71 Morocco 365 72 Uzbekistan 364 73 Jordan 361 74 Panama 357 75 Kosovo 355 76 Philippines 355 77 Guatemala 344 78 El Salvador 343 79 Dominican Republic 339 80 Paraguay 338 81 Cambodia 336	1 Singapore 561 2 Japan 547 3 Macau 543 4 Chinese Taipei 537 5 South Korea 528 6 Estonia 526 7 Hong Kong 520 8 Canada 515 9 Finland 511 10 Australia 507 11 Ireland 504 12 New Zealand 504 13 Switzerland 503 14 Slovenia 500 15 United Kingdom 500 16 United States 499 17 Poland 499 18 Czech Republic 498 19 Denmark 494 20 Latvia 494 21 Sweden 494 22 Germany 492 23 Austria 491 24 Belgium 491 25 Netherlands 488 26 France 487 27 Hungary 486 28 Spain 485 29 International Average (OECD) 485 Lithuania 484 30 Portugal 484 31 Croatia 483 32 Norway 478 33 Italy 477 34 Turkey 476 35 Vietnam 472 36 Malta 466 37 Israel 465 38 Slovakia 462 39 Ukraine 450 40 Iceland 447 41 Serbia 447 42 Brunei 446 43 Chile 444 44 Greece 441 45 Uruguay 435 46 United Arab Emirates 432 47 Qatar 432 48 Romania 428 49 Kazakhstan 423 50 Bulgaria 421 51 Moldova 417 52 Malaysia 416 53 Mongolia 412 54 Cyprus 411 55 Colombia 411 56 Costa Rica 411 57 Mexico 410 58 Thailand 500 59 Peru 408 60 Argentina 406 61 Brazil 403 62 Jamaica 403 63 Montenegro 403 64 Saudi Arabia 390 65 Panama 388 66 Georgia 384 67 Indonesia 383 68 Azerbaijan 380 69 North Macedonia 380 70 Albania 376 71 Jordan 375 72 El Salvador 374 73 Guatemala 373 74 Palestinian Authority 369 75 Paraguay 368 76 Morocco 365 77 Dominican Republic 360 78 Kosovo 357 79 Philippines 356 80 Uzbekistan 355 81 Cambodia 347	1 Singapore 543 2 Ireland 516 3 Japan 516 4 South Korea 515 5 Chinese Taipei 515 6 Estonia 511 7 Macau 510 8 Canada 507 9 United States 504 10 New Zealand 501 11 Hong Kong 500 12 Australia 498 13 United Kingdom 494 14 Finland 490 15 Denmark 489 16 Poland 489 17 Czech Republic 489 18 Sweden 487 19 Switzerland 483 20 Italy 482 21 Germany 480 22 Austria 480 23 Belgium 479 24 Norway 477 25 Portugal 477 26 International Average (OECD) 476 27 Croatia 475 28 Latvia 475 29 Spain 474 France 474 30 Israel 474 31 Hungary 473 32 Lithuania 472 33 Slovenia 469 34 Vietnam 462 35 Netherlands 459 36 Turkey 456 37 Chile 448 38 Slovakia 447 39 Malta 445 40 Serbia 440 41 Greece 438 42 Iceland 436 43 Uruguay 430 44 Brunei 429 45 Romania 428 46 Ukraine 428 47 Qatar 419 48 United Arab Emirates 417 49 Costa Rica 415 50 Mexico 415 51 Moldova 411 52 Brazil 410 53 Jamaica 410 54 Colombia 409 55 Peru 408 56 Montenegro 405 57 Bulgaria 404 58 Argentina 401 59 Panama 392 60 Malaysia 388 61 Kazakhstan 386 62 Saudi Arabia 383 63 Cyprus 381 64 Thailand 470 65 Mongolia 378 66 Georgia 374 67 Guatemala 374 68 Paraguay 373 69 Azerbaijan 365 70 El Salvador 365 71 Indonesia 359 72 North Macedonia 359 73 Albania 358 74 Dominican Republic 351 75 Palestinian Authority 349 76 Philippines 347 77 Jordan 342 78 Kosovo 342 79 Morocco 339 80 Uzbekistan 336 81 Cambodia 329

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
ChinaB-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
ArgentinaCABA	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
ChinaB-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
ArgentinaCABA	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
ChinaB-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
ArgentinaCABA	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	—	—	—	—	—	—	—	—

Previous years

Main article:Programme for International Student Assessment (2000 to 2012)

Period	Focus	OECD countries	Partner countries	Participating students	Notes
2000	Reading	28	4 + 11	265,000	The Netherlands disqualified from data analysis. 11 additional non-OECD countries took the test in 2002.
2003	Mathematics	30	11	275,000	UK disqualified from data analysis, due to its low response rate.Also included test inproblem solving.
2006	Science	30	27	400,000	Reading scores for US disqualified from analysis due to misprint in testing materials.
2009	Reading	34	41 + 10	470,000	10 additional non-OECD countries took the test in 2010.
2012	Mathematics	34	31	510,000

Reception

Further information:Programme for International Student Assessment (2000 to 2012)

China

China's participation in the 2012 test was limited toShanghai,Hong Kong,andMacauas separate entities. In 2012, Shanghai participated for the second time, again topping the rankings in all three subjects, as well as improving scores in the subjects compared to the 2009 tests. Shanghai's score of 613 in mathematics was 113 points above the average score, putting the performance of Shanghai pupils about 3 school years ahead of pupils in average countries. Educational experts debated to what degree this result reflected the quality of thegeneral educational system in China,pointing out that Shanghai has greater wealth and better-paid teachers than the rest of China.Hong Kong placed second in reading and science and third in maths.

Andreas Schleicher,PISA division head and co-ordinator, stated that PISA tests administered in rural China have produced some results approaching the OECD average. Citing further as-yet-unpublished OECD research, he said, "We have actually done Pisa in 12 of the provinces in China. Even in some of the very poor areas you get performance close to the OECD average."Schleicher believes that China has also expanded school access and has moved away from learning by rote,performing well in both rote-based and broader assessments.

In 2018 the Chinese provinces that participated wereBeijing,Shanghai,JiangsuandZhejiang.In 2015, the participating provinces were Jiangsu,Guangdong,Beijing, and Shanghai.The 2015 Beijing-Shanghai-Jiangsu-Guangdong cohort scored a median 518 in science in 2015, while the 2012 Shanghai cohort scored a median 580.

Critics of PISA counter that in Shanghai and other Chinese cities, most children of migrant workers can only attend city schools up to the ninth grade, and must return to their parents' hometowns for high school due tohukourestrictions, thus skewing the composition of the city's high school students in favor of wealthier local families. A population chart of Shanghai reproduced inThe New York Timesshows a steep drop off in the number of 15-year-olds residing there.According to Schleicher, 27% of Shanghai's 15-year-olds are excluded from its school system (and hence from testing). As a result, the percentage of Shanghai's 15-year-olds tested by PISA was 73%, lower than the 89% tested in the US.Following the 2015 testing, OECD published in depth studies on the education systems of a selected few countries including China.

In 2014,Liz Truss,the British Parliamentary Under-Secretary of State at theDepartment for Education,led a fact-finding visit to schools and teacher-training centres in Shanghai.Britain increased exchanges with Chinese teachers and schools to find out how to improve quality. In 2014, 60 teachers from Shanghai were invited to the UK to help share their teaching methods, support pupils who are struggling, and help to train other teachers.In 2016, Britain invited 120 Chinese teachers, planning to adopt Chinese styles of teaching in 8,000 aided schools.By 2019, approximately 5,000 of Britain's 16,000 primary schools had adopted the Shanghai's teaching methods.The performance of British schools in PISA improved after adopting China's teaching styles.

Finland

Finland, which received several top positions in the first tests, fell in all three subjects in 2012, but remained the best performing country overall in Europe, achieving their best result in science with 545 points (5th) and worst in mathematics with 519 (12th) in which the country was outperformed by four other European countries. The drop in mathematics was 25 points since 2003, the last time mathematics was the focus of the tests. For the first time Finnish girls outperformed boys in mathematics narrowly. It was also the first time pupils in Finnish-speaking schools did not perform better than pupils inSwedish-speakingschools. Former minister of Education and ScienceKrista Kiuruexpressed concern for the overall drop, as well as the fact that the number of low-performers had increased from 7% to 12%.

India

India participated in the 2009 round of testing but pulled out of the 2012 PISA testing, with the Indian government attributing its action to the unfairness of PISA testing to Indian students.India had ranked 72nd out of 73 countries tested in 2009.The Indian Express reported, "The ministry (of education) has concluded that there was a socio-cultural disconnect between the questions and Indian students. The ministry will write to the OECD and drive home the need to factor in India's" socio-cultural milieu ". India's participation in the next PISA cycle will hinge on this".The Indian Express also noted that "Considering that over 70 nations participate in PISA, it is uncertain whether an exception would be made for India".

India did not participate in the 2012, 2015 and 2018 PISA rounds.

AKendriya Vidyalaya Sangathan(KVS) committee as well as a group of secretaries on education constituted by thePrime Minister of IndiaNarendra Modirecommended that India should participate in PISA. Accordingly, in February 2017, theMinistry of Human Resource DevelopmentunderPrakash Javadekardecided to end the boycott and participate in PISA from 2020. To address the socio-cultural disconnect between the test questions and students, it was reported that the OECD will update some questions. For example, the word avocado in a question may be replaced with a more popular Indian fruit such as mango.

India did not participate in the 2022 PIS rounds citing due toCOVID-19 pandemicdisruption.

Malaysia

In 2015, the results from Malaysia were found by the OECD to have not met the maximum response rate.Opposition politicianOng Kian Mingsaid the education ministry tried to oversample high-performing students in rich schools.

Sweden

Sweden's result dropped in all three subjects in the 2012 test, which was a continuation of a trend from 2006 and 2009. It saw the sharpest fall in mathematics performance with a drop in score from 509 in 2003 to 478 in 2012. The score in reading showed a drop from 516 in 2000 to 483 in 2012. The country performed below the OECD average in all three subjects.The leader of the opposition,Social DemocratStefan Löfven,described the situation as a national crisis.Along with the party's spokesperson on education,Ibrahim Baylan,he pointed to the downward trend in reading as most severe.

In 2020, Swedish newspaperExpressenrevealed that Sweden had inflated their score in PISA 2018 by not conforming to OECD standards. According to professorMagnus Henreksona large number of foreign-born students had not been tested.According to an article of Sveriges Radio, poor immigrant children's scores are a significant cause of the recent decrease in Swedish Pisa scores.

United Kingdom

In the 2012 test, as in 2009, the result was slightly above average for the United Kingdom, with the science ranking being highest (20).England,Wales,ScotlandandNorthern Irelandalso participated as separated entities, showing the worst result for Wales which in mathematics was 43rd of the 65 countries and economies. Minister of Education in WalesHuw Lewisexpressed disappointment in the results, said that there were no "quick fixes", but hoped that several educational reforms that have been implemented in the last few years would give better results in the next round of tests.The United Kingdom had a greater gap between high- and low-scoring students than the average. There was little difference between public and private schools when adjusted forsocio-economicbackground of students. The gender difference in favour of girls was less than in most other countries, as was the difference between natives and immigrants.

Writing in theDaily Telegraph,Ambrose Evans-Pritchardwarned against putting too much emphasis on the UK's international ranking, arguing that an overfocus on scholarly performances in East Asia might have contributed to the area's lowbirthrate,which he argued could harm the economic performance in the future more than a good PISA score would outweigh.

In 2013, theTimes Educational Supplement(TES) published an article, "Is PISA Fundamentally Flawed?" by William Stewart, detailing serious critiques of PISA's conceptual foundations and methods advanced by statisticians at major universities.

In the article, ProfessorHarvey Goldsteinof theUniversity of Bristolwas quoted as saying that when the OECD tries to rule out questions suspected of bias, it can have the effect of "smoothing out" key differences between countries. "That is leaving out many of the important things," he warned. "They simply don't get commented on. What you are looking at is something that happens to be common. But (is it) worth looking at? PISA results are taken at face value as providing some sort of common standard across countries. But as soon as you begin to unpick it, I think that all falls apart."

Queen's University Belfastmathematician Dr. Hugh Morrison stated that he found the statistical model underlying PISA to contain a fundamental, insoluble mathematical error that renders Pisa rankings "valueless".Goldstein remarked that Dr. Morrison's objection highlights "an important technical issue" if not a "profound conceptual error". However, Goldstein cautioned that PISA has been "used inappropriately", contending that some of the blame for this "lies with PISA itself. I think it tends to say too much for what it can do and it tends not to publicise the negative or the weaker aspects." Professors Morrison and Goldstein expressed dismay at the OECD's response to criticism. Morrison said that when he first published his criticisms of PISA in 2004 and also personally queried several of the OECD's "senior people" about them, his points were met with "absolute silence" and have yet to be addressed. "I was amazed at how unforthcoming they were," he told TES. "That makes me suspicious." "Pisa steadfastly ignored many of these issues," he says. "I am still concerned."

Professor Svend Kreiner, of theUniversity of Copenhagen,agreed: "One of the problems that everybody has with PISA is that they don't want to discuss things with people criticising or asking questions concerning the results. They didn't want to talk to me at all. I am sure it is because they can't defend themselves.

United States

Since 2012 a few states have participated in the PISA tests as separate entities. Only the 2012 and 2015 results are available on a state basis. Puerto Rico participated in 2015 as a separate US entity as well.

2012 US State results

Mathematics	Science	Reading
Massachusetts 514 Connecticut 506 US Average 481 Florida 467	Massachusetts 527 Connecticut 521 US Average 497 Florida 485	Massachusetts 527 Connecticut 521 US Average 498 Florida 492

2015 US State results

Mathematics	Science	Reading
Massachusetts 500 North Carolina 471 US Average 470 Puerto Rico 378	Massachusetts 529 North Carolina 502 US Average 496 Puerto Rico 403	Massachusetts 527 North Carolina 500 US Average 497 Puerto Rico 410

PISA results for the United States by race and ethnicity

Mathematics
Race	2018	2015	2012	2009	2006	2003
	Score	Score	Score	Score	Score	Score
Asian	539	498	549	524	494	506
White	503	499	506	515	502	512
US Average	478	470	481	487	474	483
More than one race	474	475	492	487	482	502
Hispanic	452	446	455	453	436	443
Other	—	423	436	460	446	446
Black	419	419	421	423	404	417

Science
Race	2018	2015	2012	2009	2006
	Score	Score	Score	Score	Score
Asian	551	525	546	536	499
White	529	531	528	532	523
US Average	502	496	497	502	489
More than one race	502	503	511	503	501
Hispanic	478	470	462	464	439
Other	—	462	439	465	453
Black	440	433	439	435	409

Reading
Race	2018	2015	2012	2009	2006	2003	2000
	Score	Score	Score	Score	Score	Score	Score
Asian	556	527	550	541	—	513	546
White	531	526	519	525	—	525	538
US Average	505	497	498	500	—	495	504
More than one race	501	498	517	502	—	515	—
Hispanic	481	478	478	466	—	453	449
Black	448	443	443	441	—	430	445
Other	—	440	438	462	—	456	455

Research on possible causes of PISA disparities in different countries

Although PISA and TIMSS officials and researchers themselves generally refrain from hypothesizing about the large and stable differences in student achievement between countries, since 2000, literature on the differences in PISA and TIMSS results and their possible causes has emerged.Data from PISA have furnished several researchers, notablyEric Hanushek,Ludger Wößmann,Heiner Rindermann, and Stephen J. Ceci, with material for books and articles about the relationship between student achievement and economic development,democratization,and health;as well as the roles of such single educational factors as high-stakes exams,the presence or absence of private schools and the effects and timing of ability tracking.

Comments on accuracy

David Spiegelhalterof Cambridge wrote: "Pisa does present the uncertainty in the scores and ranks - for example theUnited Kingdomrank in the 65 countries is said to be between 23 and 31. It's unwise for countries to base education policy on their Pisa results, asGermany,NorwayandDenmarkdid after doing badly in 2001. "

According to aForbesopinion article, some countries such asChina,Hong Kong,Macau,andArgentinaselect PISA samples from only the best-educated areas or from their top-performing students, slanting the results.

According to an open letter toAndreas Schleicher,director of PISA, various academics and educators argued that "OECD and Pisa tests are damaging education worldwide".

According toO Estado de São Paulo,Brazil shows a great disparity when classifying the results between public and private schools, where public schools would rank worse than Peru, while private schools would rank better than Finland.

See also

• Gender gaps in mathematics and readingin PISA 2009
• Progress in International Reading Literacy Study(PIRLS)
• Teaching And Learning International Survey(TALIS)
• Trends in International Mathematics and Science Study(TIMSS)

External links

• OECD/PISA website
  • OECD (1999):Measuring Student Knowledge and Skills: A New Framework for Assessment.Paris: OECD,ISBN92-64-17053-7
  • OECD (2014): PISA 2012 results: Creative problem solving: Students' skills in tackling real-life problems (Volume V)[2]
• OECD's Education GPS: Interactive data from PISA 2015
• PISA Data Explorer
• Gunda Tire: "Estonians believe in education, and this belief has been essential for centuries"—Interview of Gunda Tire, OECDPISANational Project Manager, forCaucasian Journal
• QEdu – PISA scores and percentage of adequate learning by country