Student Learning in Mathematics and Science

Policymakers, legislators, and educators in the United States continue to strive to improve K–12 STEM education. Access to high-quality STEM education for all students and students’ strong performance in STEM subjects are necessary for achieving and maintaining the STEM proficiency needed for economic growth, international competitiveness, and scientific literacy (Bush 2019; Committee on STEM Education 2018; NSB 2020). This section presents indicators of U.S. students’ performance in STEM subjects in elementary and secondary school, beginning with performance in mathematics in fourth and eighth grades. Next, it examines mathematics and science performance of U.S. 15-year-olds in an international context. Finally, it examines U.S. performance in computer science, both nationally and internationally.

International Comparisons of Mathematics and Science Performance

U.S. 15-year-olds rank higher internationally in science literacy than they do in mathematics literacy, as shown by their performance on the 2018 Program for International Student Assessment (PISA). In mathematics, U.S. 15-year-olds in 2018 ranked 25th among 37 OECD countries; compared to the 36 other OECD members, the U.S. average in mathematics literacy for 15-year-olds was lower than the average in 24 education systems, higher than in 6, and not measurably different than in 6 (Figure K12-5). The average score in 2018 was lower than the OECD average and did not measurably change since 2003 (Figure K12-6). In comparison, U.S. students fared better in science, ranking in the 7th position out of 37; compared to the 36 other OECD members, the U.S. average score in science literacy was lower than the average in 6 education systems, higher than in 19, and not measurably different than in 11. The U.S. average science score was higher than the OECD average in 2018 and improved by 13 points between 2006 and 2018.

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Average scores of 15-year-old students on the PISA mathematics and science literacy scales, by OECD education system: 2018

(Average score)
Education system Average score
Japan* 527
South Korea* 526
Estonia* 523
Netherlands* 519
Poland* 516
Switzerland* 515
Canada* 512
Denmark* 509
Slovenia* 509
Belgium* 508
Finland* 507
Sweden* 502
United Kingdom* 502
Norway* 501
Germany* 500
Ireland* 500
Czechia* 499
Austria* 499
Latvia* 496
France* 495
Iceland* 495
New Zealand* 494
Portugal* 492
Australia* 491
OECD average* 489
Italy 487
Slovakia 486
Luxembourg 483
Spain 481
Lithuania 481
Hungary 481
United States 478
Israel* 462
Turkey* 454
Greece* 451
Chile* 417
Mexico* 409
Colombia* 391
(Average score)
Education system Average score
Estonia* 530
Japan* 529
Finland* 522
South Korea* 519
Canada* 518
Poland* 511
New Zealand 508
Slovenia 507
United Kingdom 505
Netherlands 503
Germany 503
Australia 503
United States 502
Sweden 499
Belgium 499
Czechia 497
Ireland 496
Switzerland 495
France* 493
Denmark* 493
Portugal* 492
Norway* 490
Austria* 490
OECD average* 489
Latvia* 487
Spain* 483
Lithuania* 482
Hungary* 481
Luxembourg* 477
Iceland* 475
Turkey* 468
Italy* 468
Slovakia* 464
Israel* 462
Greece* 452
Chile* 444
Mexico* 419
Colombia* 413

* p < 0.05. Significantly different from the U.S. estimate at the 0.05 level of statistical significance.

OECD = Organisation for Economic Co-operation and Development; PISA = Program for International Student Assessment.

Note(s):

The score of mathematics and science scores is 0–1,000. The OECD average is the average of the national averages of the OECD member countries, with each country weighted equally. For Colombia, Mexico, and Turkey, at least 50% but less than 75% of the 15-year-old population is covered by the PISA sample.

Source(s):

OECD, PISA, 2018. https://nces.ed.gov/surveys/pisa/pisa2018/index.asp#/math/intlcompare.

Science and Engineering Indicators

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Average scores of U.S. 15-year-old students on the PISA mathematics and science literacy scales: 2003–18

(Average score)
Year Average mathematics score Average science score
2003 483 NA
2006 474 489
2009 487 502
2012 481 497
2015 470 496
2018 478 502

PISA = Program for International Student Assessment.

Note(s):

The score of mathematics and science scores is 0–1,000. The PISA science framework was revised in 2006. Because of changes in the framework, it is not possible to compare science learning outcomes from PISA 2003 with those from PISA 2006, 2009, 2012, 2015, and 2018.

Source(s):

Organisation for Economic Co-operation and Development (OECD), PISA, 2003, 2006, 2009, 2012, 2015, and 2018. https://nces.ed.gov/surveys/pisa/pisa2018/index.asp#/math/intlcompare.

Science and Engineering Indicators

Japan, South Korea, Estonia, and the Netherlands were the highest-scoring OECD countries in mathematics in 2018, and Estonia and Japan were the highest scoring in science. PISA also tests students in several city-based and non-OECD-country education systems (Figure K12-7). Among these entities, Beijing, Shanghai, Jiangsu, and Zhejiang (B-S-J-Z) in China, Singapore, and Macau (China) were the highest scorers in both mathematics and science. The scores for cities and small countries in Figure K12-7 are not directly comparable to those of the United States, which has a much larger and more heterogenous education system. These scores are presented to provide context for U.S. performance compared to that of some of its global competitors in science and technology businesses and innovation.

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Average scores of 15-year-old students on the PISA mathematics and science literacy scales in the United States and top-scoring non-OECD education systems: 2018

(Average score)
Education system Average mathematics score
B-S-J-Z (China)* 591
Singapore* 569
Macau (China)* 558
Hong Kong (China)* 551
Chinese Taipei* 531
Russia* 488
United States 478
(Average score)
Education system Average science score
B-S-J-Z (China)* 590
Singapore* 551
Macau (China)* 544
Hong Kong (China)* 517
Chinese Taipei* 516
United States 502
Russia* 478

* p < 0.05. Significantly different from the U.S. estimate at the 0.05 level of statistical significance.

OECD = Organisation for Economic Co-operation and Development; PISA = Program for International Student Assessment.

Note(s):

The scale of mathematics and science scores is 0–1,000. B-S-J-Z (China) refers to the four PISA-participating China provinces: Beijing, Shanghai, Jiangsu, and Zhejiang.

Source(s):

OECD, PISA, 2018. https://nces.ed.gov/surveys/pisa/pisa2018/index.asp#/math/intlcompare.

Science and Engineering Indicators

Average PISA scores indicate score gaps between male and female students in many countries, including the United States (Figure K12-8). In the United States, male students outperformed female students in mathematics literacy by 9 points, but there was no measurable difference between male and female students’ scores in science. Among OECD countries, on average, male students outscored female students by 5 points in mathematics, and female students outscored male students by 2 points in science. In such countries as Finland, Norway, Iceland, and Israel, female students outscored male students by substantial margins in both mathematics and science.

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Male-female score gaps of 15-year-old students on the PISA mathematics and science literacy scales, by OECD education system: 2018

(Score gap)
Education system Male-female mathematics score difference
Iceland* -10
Israel -9
Norway* -7
Finland* -6
Lithuania -2
Sweden* -1
Greece 0
Slovenia* 1
Netherlands 1
Poland 1
Czechia 4
Denmark 4
Portugal 4
Slovakia 5
Canada* 5
Turkey 5
OECD average* 5
Ireland 6
Australia* 6
France* 6
Spain* 6
Latvia* 7
Germany* 7
Switzerland* 7
Chile 7
Luxembourg* 7
Estonia* 8
United States* 9
Hungary* 9
New Zealand* 9
South Korea 9
Japan* 10
Mexico* 12
Belgium* 12
United Kingdom* 12
Austria* 13
Italy* 16
Colombia* 20
(Score gap)
Education system Male-female science score difference
Finland* -24
Israel* -19
Greece* -11
Norway* -11
Slovenia* -10
Iceland* -8
Latvia* -8
Netherlands* -8
Sweden* -8
Turkey* -7
Lithuania* -6
Slovakia -6
Estonia* -5
Luxembourg* -5
Canada -3
OECD average* -2
Denmark -2
France -2
Czechia -2
Ireland -1
Germany -1
Poland 0
Switzerland 0
United States 1
United Kingdom 1
Spain 1
Australia 2
New Zealand 2
Austria 2
Japan 3
Italy 3
Chile 3
Portugal 4
Belgium 5
South Korea 5
Hungary 6
Mexico* 9
Colombia* 12

* p < 0.05. Difference between male and female scores at the country level is significantly different at the 0.05 level of statistical significance.

OECD = Organisation for Economic Co-operation and Development; PISA = Program for International Student Assessment.

Note(s):

The scale of mathematics and science scores is 0–1,000. The OECD average is the average of the national averages of the OECD member countries, with each country weighted equally. For Colombia, Mexico, and Turkey, at least 50% but less than 75% of the 15-year-old population is covered by the PISA sample. A positive score gap indicates that male students outperform female students on PISA scales.

Source(s):

OECD, PISA, 2018. https://nces.ed.gov/surveys/pisa/pisa2018/index.asp#/math/intlcompare.

Science and Engineering Indicators

The Trends in International Mathematics and Science Study (TIMSS) is another international comparative study that measures trends in mathematics and science achievement in fourth and eighth grades every 4 years. TIMSS is designed to align broadly with mathematics and science curricula in the participating education systems and, therefore, to reflect students’ school-based learning. The United States has participated in every administration of TIMSS since its inception in 1995, including the most recent administration in 2019. TIMSS 2019 data were released too late for inclusion in this edition of Indicators; data on U.S performance in 2019 are available here: TIMSS 2019 U.S. Results.

International Comparisons of Computer Science Performance

In the 2018 International Computer and Information Literacy Study (ICILS), U.S. eighth-grade students’ average score was higher than the international average on computer and information literacy and was not measurably different from the international average on computational thinking (Figure K12-9). Computer and information literacy refers to the ability to use computers effectively in everyday life at home, work, and school, whereas computational thinking refers to the use of computers to solve problems and includes such skills as programming. The United States scored 5th among the 14 education systems that participated in the computer and information literacy assessment and 4th among the 9 education systems that participated in the computational thinking assessment. Internationally, Denmark and South Korea were the highest-scoring countries on both assessments. The city of Moscow had the second-highest score in computer and information literacy. U.S. students outperformed their counterparts in France, Luxembourg, Chile, Italy, Uruguay, and Kazakhstan in computer and information literacy and Germany, Portugal, and Luxembourg in computational thinking.

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Average CIL and CT scores of students in grade 8, by education system: 2018

(Average score)
Education system CIL score
Denmark* 553
Moscow* 549
South Korea* 542
Finland* 531
United States 519
Germany 518
Portugal 516
North Rhine–Westphalia 515
France* 499
ICILS 2018 average* 496
Luxembourg* 482
Chile* 476
Italy* 461
Uruguay* 450
Kazakhstan* 395
(Average score)
Education system CT score
South Korea* 536
Denmark* 527
Finland* 508
France 501
ICILS 2018 average 500
United States 498
Germany* 486
North Rhine–Westphalia* 485
Portugal* 482
Luxembourg* 460

* p < 0.05. Significantly different from the U.S. estimate at the 0.05 level of statistical significance.

CIL = computer and information literacy; CT = computational thinking.

Note(s):

The scale of CIL and CT scores is 100–700. The International Computer and Information Literacy Study (ICILS) 2018 average is the average of all participating education systems meeting international technical standards, with each education system weighted equally. The United States did not meet the guidelines for a sample participation rate of 85% and was not included in the international average. Moscow and North Rhine–Westphalia are included as benchmarking participants.

Source(s):

International Association for the Evaluation of Educational Achievement (IEA), ICILS, 2018. https://nces.ed.gov/surveys/icils/icils2018/theme1.asp?tabontop.

Science and Engineering Indicators

ICILS also provides information about U.S. eighth-grade student scores by sex, race or ethnicity, and school poverty level. Female students outperformed male students in computer and information literacy by 23 points (531 compared to 508); there was no measurable difference in scores between male students and female students in computational thinking (Figure K12-10). Scores differed far more substantially by school poverty level. U.S. eighth-grade students in schools with less than 10% of students eligible for free or reduced-price lunch outscored students in schools with 75% or more students eligible by 88 points in computer and information literacy (564 compared to 476) and 112 points (557 compared to 444) in computational thinking (Figure K12-11).

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Average CIL and CT scores of U.S. students in grade 8, by sex: 2018

(Average score)
Score type Male Female
Average CIL score 508 531
Average CT score 502 495

CIL = computer and information literacy; CT = computational thinking.

Note(s):

The scale of CIL and CT scores is 100–700.

Source(s):

International Association for the Evaluation of Educational Achievement (IEA), International Computer and Information Literacy Study (ICILS), 2018. https://nces.ed.gov/surveys/icils/icils2018/theme1.asp?tabontop.

Science and Engineering Indicators

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Average CIL and CT scores of U.S. students in grade 8, by school poverty level: 2018

(Average score)
School poverty level Average CIL score
75.0% or more 476
50.0%–74.9% 506
25.0%–49.9% 529
10.0%–24.9% 550
Less than 10.0% 564
(Average score)
School poverty level Average CT score
75.0% or more 444
50.0%–74.9% 481
25.0%–49.9% 513
10.0%–24.9% 534
Less than 10.0% 557

CIL = computer and information literacy; CT = computational thinking.

Note(s):

The scale of CIL and CT scores is 100–700. School poverty level is the percentage of students eligible for free or reduced-price lunch.

Source(s):

International Association for the Evaluation of Educational Achievement (IEA), International Computer and Information Literacy Study (ICILS), 2018. https://nces.ed.gov/surveys/icils/icils2018/theme1.asp?tabontop.

Science and Engineering Indicators

As with NAEP scores, ICILS scores by race or ethnicity indicate that U.S. Black, Hispanic, Native Hawaiian or Pacific Islander, and American Indian or Alaska Native students posted scores that lag behind those of their White and Asian counterparts in both computer and information literacy and computational thinking (Figure K12-12). Researchers suggest that contributors to these persistent differences include inequitable access to high-quality computer science instruction and to computer or wireless technology, lack of a culturally relevant curriculum, and societal narratives about who is good at computer science (IEA 2020; Margolis et al. 2017; Vakil 2018). ICILS scores ranged from 563 for Asian students to 470 for American Indian or Alaska Native students.

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Average CIL and CT scores of U.S. students in grade 8, by race or ethnicity: 2018

(Average score)
Race or ethnicity Average CIL score
White 540
Black 475
Hispanic 502
Asian 563
Native Hawaiian or Pacific Islander 473
American Indian or Alaska Native 470
Two or more races 491
(Average score)
Race or ethnicity Average CT score
White 526
Black 432
Hispanic 476
Asian 549
Native Hawaiian or Pacific Islander 431
American Indian or Alaska Native 437
Two or more races 460

CIL = computer and information literacy; CT = computational thinking.

Note(s):

The scale of CIL and CT scores is 100–700. Hispanic may be any race; race categories exclude Hispanic origin.

Source(s):

International Association for the Evaluation of Educational Achievement (IEA), International Computer and Information Literacy Study (ICILS), 2018. https://nces.ed.gov/surveys/icils/icils2018/theme1.asp?tabontop.

Science and Engineering Indicators