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Programme for International Student Assessment

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Programme for International Student Assessment
AbbreviationPISA
Formation1997
PurposeComparison of education attainment across the world
HeadquartersOECD Headquarters
Location
Region served World
Membership79 government education departments
Official language English and French
Head of the Early Childhood and Schools DivisionYuri Belfali
Main organPISA Governing Body (Chair – Michele Bruniges)
Parent organizationOECD
Websitewww.oecd.org/pisa/
PISA average Mathematics scores (2018)
PISA average Science scores (2018)
PISA average Reading scores (2018)

The Programme for International Student Assessment (PISA) is a worldwide study by the Organisation 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 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.

Framework

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.

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 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

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 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.

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 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.

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 2018 were presented on 5 December 2018, which included data for around 700,000 participating students in 81 countries and economies, with Singapore emerging as the top performer in all categories.

Both Lebanon and the Chinese provinces/municipalities of Beijing, Shanghai, Jiangsu and Zhejiang were 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 the Russian 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, the Autonomous Republic of Crimea and the city of Sevastopol.

Mathematics Science Reading
1  Singapore 575
2  Macau 552
3  Taiwan 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 394
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  Taiwan 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 409
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  Taiwan 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 379
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
 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
  1. ^ Shanghai (2009, 2012); Beijing, Shanghai, Jiangsu, Guangdong (2015)
  2. ^ Ciudad Autónoma de Buenos Aires

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 in problem 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 to Shanghai, Hong Kong, and Macau as 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 the general 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 were Beijing, Shanghai, Jiangsu and Zhejiang. 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 to hukou restrictions, thus skewing the composition of the city's high school students in favor of wealthier local families. A population chart of Shanghai reproduced in The New York Times shows 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 the Department 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 in Swedish-speaking schools. Former minister of Education and Science Krista Kiuru expressed 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.

A Kendriya Vidyalaya Sangathan (KVS) committee as well as a group of secretaries on education constituted by the Prime Minister of India Narendra Modi recommended that India should participate in PISA. Accordingly, in February 2017, the Ministry of Human Resource Development under Prakash Javadekar decided 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 PISA rounds citing due to COVID-19 pandemic disruption.

Malaysia

In 2015, the results from Malaysia were found by the OECD to have not met the maximum response rate. Opposition politician Ong Kian Ming said 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 Democrat Stefan 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 newspaper Expressen revealed that Sweden had inflated their score in PISA 2018 by not conforming to OECD standards. According to professor Magnus Henrekson a large number of foreign-born students had not been tested.

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, Scotland and Northern Ireland also 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 Wales Huw Lewis expressed 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 for socio-economic background 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 the Daily Telegraph, Ambrose Evans-Pritchard warned 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 low birthrate, which he argued could harm the economic performance in the future more than a good PISA score would outweigh.

In 2013, the Times 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, Professor Harvey Goldstein of the University of Bristol was 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 Belfast mathematician 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 the University 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
United States US Average 481
 Florida 467
 Massachusetts 527
 Connecticut 521
United States US Average 497
 Florida 485
 Massachusetts 527
 Connecticut 521
United States US Average 498
 Florida 492
2015 US State results
Mathematics Science Reading
 Massachusetts 500
 North Carolina 471
United States US Average 470
 Puerto Rico 378
 Massachusetts 529
 North Carolina 502
United States US Average 496
 Puerto Rico 403
 Massachusetts 527
 North Carolina 500
United States 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, notably Eric 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 Spiegelhalter of Cambridge wrote: "Pisa does present the uncertainty in the scores and ranks - for example the United Kingdom rank 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, as Germany, Norway and Denmark did after doing badly in 2001."

According to a Forbes opinion article, some countries such as China, Hong Kong, Macau, and Argentina select PISA samples from only the best-educated areas or from their top-performing students, slanting the results.

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

According to O 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

Explanatory notes

References

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