PISA 2018 Results (Volume I)

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 249 Results for countries and economies Annex B1 Table I.B1.13 [2/2] Distribution of reading scores, 2000 through 2018 Average 3-year trend in percentiles of reading performance across PISA assessments1 10th percentile 25th percentile Median (50th percentile) 75th percentile 90th percentile Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. PartnersAlbania 14.4 (1.7) 12.3 (1.6) 9.7 (1.5) 7.9 (1.4) 7.9 (1.4) Argentina 4.4 (2.4) 0.8 (2.4) -2.5 (2.2) -3.8 (2.0) -4.3 (2.1) Baku (Azerbaijan) m m m m m m m m m m Belarus m m m m m m m m m m Bosnia and Herzegovina m m m m m m m m m m Brazil 2.6 (1.5) 1.5 (1.4) 1.6 (1.4) 3.3 (1.4) 4.0 (1.4) Brunei Darussalam m m m m m m m m m m B-S-J-Z (China) m m m m m m m m m m Bulgaria 0.9 (1.8) -0.4 (1.8) 0.1 (1.8) 1.2 (1.8) 1.8 (1.9) Costa Rica -7.6 (2.5) -8.3 (2.2) -8.3 (2.2) -6.1 (2.5) -3.7 (3.0) Croatia 1.4 (2.0) 0.7 (1.7) 0.4 (1.6) 1.7 (1.6) 2.9 (1.6) Cyprus -0.7 (3.1) -12.6 (2.4) -17.4 (2.4) -16.8 (2.5) -14.7 (2.7) Dominican Republic -9.4 (6.0) -15.6 (5.9) -19.7 (6.1) -20.8 (6.9) -17.5 (8.5) Georgia 11.6 (2.4) 5.2 (2.2) 0.3 (2.0) -0.1 (2.0) 0.5 (2.4) Hong Kong (China)* -1.5 (1.7) -0.3 (1.5) 1.3 (1.4) 3.1 (1.3) 4.8 (1.3) Indonesia 1.2 (1.5) 0.7 (1.4) 0.7 (1.4) 0.9 (1.5) 2.1 (1.6) Jordan 4.9 (2.2) 4.7 (1.7) 4.0 (1.6) 3.5 (1.6) 2.6 (1.7) Kazakhstan 5.0 (1.7) 0.9 (1.6) -2.8 (1.7) -6.1 (1.8) -6.2 (2.2) Kosovo 22.0 (5.2) 10.0 (5.0) 2.1 (4.7) -4.3 (4.9) -4.6 (5.2) Lebanon 8.4 (8.4) 3.5 (7.8) 8.4 (8.8) 8.6 (9.0) 4.0 (9.4) Macao (China) -0.1 (1.5) 3.0 (1.4) 6.3 (1.3) 9.3 (1.5) 11.2 (1.4) Malaysia 1.1 (2.4) -0.3 (2.2) 0.8 (2.2) 3.1 (2.2) 5.6 (2.4) Malta 5.4 (2.9) 1.1 (2.0) 0.3 (2.0) -0.3 (2.0) 2.2 (2.0) Moldova 11.1 (2.3) 11.1 (2.3) 12.8 (2.1) 15.9 (2.2) 17.0 (2.2) Montenegro 8.2 (1.5) 7.5 (1.4) 7.0 (1.3) 7.4 (1.3) 8.0 (1.4) Morocco m m m m m m m m m m North Macedonia 0.5 (4.0) 1.1 (4.0) 1.1 (4.0) 0.8 (4.0) 1.6 (4.0) Panama 6.3 (3.7) 3.5 (2.9) 2.0 (2.8) -0.0 (3.2) -2.8 (3.8) Peru 14.6 (1.6) 13.9 (1.6) 13.5 (1.6) 12.9 (1.7) 12.5 (1.7) Philippines m m m m m m m m m m Qatar 19.3 (1.3) 21.3 (1.3) 24.2 (1.3) 23.7 (1.3) 20.9 (1.6) Romania 5.4 (2.3) 6.1 (2.4) 7.0 (2.2) 8.1 (2.1) 10.1 (2.2) Russia 7.7 (1.6) 7.0 (1.5) 6.1 (1.4) 6.4 (1.4) 6.7 (1.4) Saudi Arabia m m m m m m m m m m Serbia 4.8 (1.9) 4.9 (1.9) 7.0 (1.8) 9.0 (1.7) 11.3 (1.7) Singapore 0.3 (1.8) 5.0 (1.6) 7.4 (1.6) 8.6 (1.6) 9.5 (1.7) Chinese Taipei -3.7 (1.9) -1.5 (1.8) 1.2 (1.6) 4.6 (1.6) 7.4 (1.8) Thailand -4.1 (1.4) -4.8 (1.4) -5.0 (1.4) -4.0 (1.4) -2.6 (1.5) Ukraine m m m m m m m m m m United Arab Emirates -8.1 (2.5) -6.6 (2.4) -2.5 (2.3) 3.8 (2.4) 8.9 (2.4) Uruguay 8.4 (1.6) 3.4 (1.5) -0.5 (1.5) -3.2 (1.5) -5.8 (1.6) Viet Nam** -17.1 (9.7) -24.2 (7.2) -25.0 (5.9) -22.7 (6.2) -18.9 (7.8) 1. The average 3-year trend is the average change, per 3-year-period, between the earliest available measurement in PISA and PISA 2018, calculated by a linear regression. *PISA 2018 data did not meet the PISA technical standards but were accepted as largely comparable (see Annexes A2 and A4). **The data for Viet Nam have not yet been fully validated. Due to a lack of consistency in the response pattern of some performance data, the OECD cannot yet assure full international comparability of the results (see Annexes A2 and A4). Notes: Values that are statistically significant are indicated in bold (see Annex A3). Albania, Argentina, Bulgaria, Chile, Indonesia, the Republic of North Macedonia, Peru and Thailand conducted the PISA 2000 assessment in 2001, Hong Kong (China), Israel and Romania conducted the assessment in 2002, as part of PISA 2000+. Costa Rica, Georgia, Malta and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+. Estimates of the average 3-year trend and the curvilinear trend for these countries consider the year in which the assessment was conducted. The full version of this table is available on line, at the 12 StatLink below. https://doi.org/10.1787/888934029090

250 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex B1 Results for countries and economies Table I.B1.14 [1/2] Distribution of mathematics scores, 2003 through 2018 Average 3-year trend in percentiles of mathematics performance across PISA assessments1 10th percentile 25th percentile Median (50th percentile) 75th percentile 90th percentile Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. OECDAustralia -7.1 (1.1) -7.5 (1.1) -7.5 (1.1) -7.4 (1.1) -6.9 (1.2) Austria -1.7 (1.5) -1.5 (1.4) -1.3 (1.3) -1.8 (1.3) -2.3 (1.3) Belgium -1.1 (1.5) -3.4 (1.2) -4.8 (1.2) -6.2 (1.1) -6.8 (1.2) Canada -5.5 (1.2) -5.0 (1.2) -4.2 (1.1) -3.5 (1.1) -2.9 (1.2) Chile 0.9 (1.5) 1.5 (1.4) 2.1 (1.5) 1.9 (1.6) 0.9 (1.8) Colombia 7.2 (1.8) 5.2 (1.6) 4.3 (1.5) 4.4 (1.6) 4.9 (1.5) Czech Republic -2.0 (1.5) -2.7 (1.3) -3.2 (1.3) -4.8 (1.3) -5.9 (1.3) Denmark 1.0 (1.3) 0.2 (1.2) -0.9 (1.1) -2.1 (1.2) -3.4 (1.2) Estonia 2.2 (1.4) 1.8 (1.2) 2.4 (1.2) 2.6 (1.3) 2.6 (1.2) Finland -9.7 (1.2) -9.2 (1.2) -8.5 (1.1) -9.2 (1.1) -9.3 (1.1) France -3.1 (1.4) -2.7 (1.3) -2.1 (1.2) -2.2 (1.2) -2.8 (1.2) Germany 2.8 (1.5) 1.1 (1.4) -0.4 (1.3) -1.7 (1.3) -2.8 (1.2) Greece 0.5 (1.6) 0.0 (1.4) 0.2 (1.3) 0.1 (1.3) -0.8 (1.4) Hungary -3.7 (1.4) -3.3 (1.2) -2.3 (1.2) -2.4 (1.3) -3.0 (1.4) Iceland -5.6 (1.3) -5.2 (1.2) -4.6 (1.1) -4.5 (1.1) -4.1 (1.2) Ireland 1.3 (1.3) 1.1 (1.3) 0.2 (1.2) -0.8 (1.1) -1.8 (1.2) Israel 4.4 (2.1) 6.0 (1.8) 7.6 (1.7) 7.2 (1.6) 5.8 (1.6) Italy 5.2 (1.4) 5.6 (1.3) 5.9 (1.2) 5.4 (1.2) 4.6 (1.3) Japan 2.9 (1.6) 1.3 (1.4) -0.2 (1.3) -1.5 (1.3) -2.7 (1.5) Korea -7.3 (1.5) -5.1 (1.3) -3.6 (1.3) -2.6 (1.4) -1.9 (1.6) Latvia 3.5 (1.5) 2.5 (1.3) 1.5 (1.2) 0.8 (1.2) 0.1 (1.3) Lithuania -0.9 (1.4) -1.2 (1.3) -0.6 (1.2) -0.6 (1.3) -0.8 (1.7) Luxembourg -3.1 (1.2) -3.2 (1.1) -1.9 (1.1) -0.5 (1.1) -0.3 (1.1) Mexico 6.0 (1.3) 4.6 (1.2) 3.1 (1.2) 1.9 (1.3) 0.7 (1.3) Netherlands* -5.2 (1.5) -4.1 (1.5) -3.6 (1.3) -4.4 (1.2) -4.1 (1.2) New Zealand -6.0 (1.2) -6.7 (1.2) -7.2 (1.1) -7.5 (1.1) -7.9 (1.3) Norway 1.8 (1.3) 2.0 (1.2) 2.1 (1.2) 1.2 (1.2) 0.5 (1.1) Poland 4.4 (1.2) 5.1 (1.2) 5.3 (1.2) 5.0 (1.2) 4.7 (1.3) Portugal* 2.6 (1.4) 4.6 (1.4) 6.7 (1.3) 7.9 (1.2) 7.8 (1.2) Slovak Republic -6.1 (1.5) -4.6 (1.4) -2.7 (1.2) -2.6 (1.2) -2.8 (1.3) Slovenia 2.0 (1.1) 2.8 (1.1) 2.8 (1.1) 1.3 (1.0) -0.8 (1.2) Spain 0.4 (1.2) -0.1 (1.2) 0.1 (1.1) 0.0 (1.1) -0.6 (1.1) Sweden -2.0 (1.4) -2.0 (1.2) -1.7 (1.3) -2.4 (1.2) -2.9 (1.3) Switzerland -1.1 (1.3) -2.8 (1.3) -2.6 (1.3) -3.0 (1.4) -3.4 (1.5) Turkey 6.3 (1.4) 6.3 (1.4) 5.3 (1.5) 3.9 (1.8) -0.2 (2.6) United Kingdom -0.8 (1.4) 0.6 (1.2) 2.2 (1.2) 2.5 (1.2) 1.9 (1.4) United States* -0.1 (1.4) -1.0 (1.3) -1.1 (1.3) -1.6 (1.3) -2.3 (1.3) OECD average-29a -1.0 (1.0) -1.2 (1.0) -1.1 (1.0) -1.5 (1.0) -2.1 (1.0) OECD average-30 -1.1 (1.0) -1.2 (1.0) -1.1 (1.0) -1.6 (1.0) -2.1 (1.0) OECD average-36b -0.4 (0.9) -0.5 (0.9) -0.3 (0.9) -0.7 (0.9) -1.3 (0.9) OECD average-37 -0.5 (0.9) -0.5 (0.9) -0.4 (0.9) -0.7 (0.9) -1.3 (0.9) 1. The average 3-year trend is the average change, per 3-year-period, between the earliest available measurement in PISA and PISA 2018, calculated by a linear regression. *PISA 2018 data did not meet the PISA technical standards but were accepted as largely comparable (see Annexes A2 and A4). **The data for Viet Nam have not yet been fully validated. Due to a lack of consistency in the response pattern of some performance data, the OECD cannot yet assure full international comparability of the results (see Annexes A2 and A4). Notes: Values that are statistically significant are indicated in bold (see Annex A3). Costa Rica, Georgia, Malta and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+. Estimates of the average 3-year trend and the curvilinear trend for these countries consider the year in which the assessment was conducted. The full version of this table is available on line, at the 12 StatLink below. https://doi.org/10.1787/888934029090

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 251 Results for countries and economies Annex B1 Table I.B1.14 [2/2] Distribution of mathematics scores, 2003 through 2018 Average 3-year trend in percentiles of mathematics performance across PISA assessments1 10th percentile 25th percentile Median (50th percentile) 75th percentile 90th percentile Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. PartnersAlbania 24.0 (2.4) 20.6 (2.3) 18.5 (2.0) 18.1 (2.1) 16.7 (2.5) Argentina 5.3 (2.4) 1.0 (2.0) -2.2 (1.8) -4.1 (1.8) -5.6 (2.2) Baku (Azerbaijan) m m m m m m m m m m Belarus m m m m m m m m m m Bosnia and Herzegovina m m m m m m m m m m Brazil 7.4 (1.4) 5.8 (1.2) 4.3 (1.3) 3.7 (1.4) 2.6 (1.9) Brunei Darussalam m m m m m m m m m m B-S-J-Z (China) m m m m m m m m m m Bulgaria 6.2 (2.1) 5.8 (1.9) 5.9 (1.9) 5.7 (2.0) 5.4 (2.5) Costa Rica -5.0 (2.2) -3.9 (1.9) -2.8 (2.2) -1.8 (2.4) -1.5 (2.8) Croatia -0.9 (1.4) -0.9 (1.3) -0.4 (1.3) 0.2 (1.3) 0.6 (1.5) Cyprus 2.6 (2.4) 4.5 (2.2) 7.6 (2.2) 7.6 (2.2) 5.6 (2.3) Dominican Republic -6.4 (5.3) -4.7 (4.8) -2.3 (4.8) -2.5 (5.3) 0.4 (7.1) Georgia 5.9 (2.6) 6.4 (2.2) 6.6 (2.0) 8.8 (2.2) 11.2 (2.6) Hong Kong (China)* 1.6 (1.8) 1.4 (1.6) 0.1 (1.3) -0.7 (1.2) -1.0 (1.3) Indonesia 2.7 (1.4) 2.3 (1.2) 2.2 (1.3) 1.5 (1.5) 1.5 (1.8) Jordan 1.6 (1.6) 1.8 (1.4) 2.3 (1.4) 2.8 (1.5) 3.6 (1.7) Kazakhstan 1.3 (1.7) 4.0 (1.7) 5.7 (1.7) 6.5 (2.0) 6.7 (2.4) Kosovo 3.1 (4.6) 3.6 (3.9) 3.6 (3.5) 3.0 (4.2) 5.3 (5.8) Lebanon -11.9 (7.4) -7.0 (7.3) -0.9 (7.1) 4.3 (7.2) 1.4 (7.7) Macao (China) 7.4 (1.4) 7.6 (1.2) 6.5 (1.2) 5.5 (1.1) 4.5 (1.4) Malaysia 8.7 (2.0) 11.1 (1.9) 12.8 (1.9) 15.0 (2.3) 16.8 (2.8) Malta 3.1 (2.3) 3.7 (2.3) 4.6 (2.0) 3.8 (1.9) 2.4 (1.9) Moldova 5.0 (2.4) 6.0 (2.3) 8.9 (2.2) 11.9 (2.4) 13.6 (2.9) Montenegro 7.8 (1.3) 7.0 (1.1) 7.5 (1.1) 8.1 (1.0) 7.8 (1.1) Morocco m m m m m m m m m m North Macedonia 23.7 (4.8) 23.7 (4.0) 25.4 (3.7) 24.1 (4.0) 20.2 (4.6) Panama -2.1 (2.9) -1.9 (2.4) -1.5 (2.4) -1.7 (2.8) -4.0 (3.6) Peru 14.5 (2.0) 13.1 (2.0) 12.1 (2.0) 11.3 (2.3) 10.8 (2.7) Philippines m m m m m m m m m m Qatar 18.1 (1.2) 20.6 (1.0) 24.6 (1.0) 26.9 (1.0) 23.9 (1.1) Romania 1.2 (2.3) 2.4 (1.8) 4.3 (1.8) 6.9 (1.9) 8.8 (2.3) Russia 5.8 (1.5) 5.5 (1.4) 5.4 (1.3) 4.5 (1.4) 2.8 (1.4) Saudi Arabia m m m m m m m m m m Serbia 1.2 (1.7) 1.2 (1.6) 2.2 (1.5) 4.5 (1.6) 5.6 (1.6) Singapore 5.9 (1.9) 5.3 (1.6) 1.7 (1.5) -2.4 (1.6) -5.1 (1.8) Chinese Taipei -2.4 (1.8) -2.1 (1.8) -3.9 (1.5) -5.0 (1.4) -5.2 (1.6) Thailand -1.1 (1.3) -0.4 (1.2) 0.4 (1.2) 0.8 (1.3) 1.4 (1.6) Ukraine m m m m m m m m m m United Arab Emirates -3.7 (2.3) 0.2 (2.2) 4.3 (2.1) 8.4 (2.1) 10.0 (2.2) Uruguay 3.1 (1.3) 0.0 (1.3) -2.9 (1.3) -4.3 (1.3) -5.4 (1.4) Viet Nam** -12.9 (9.1) -18.2 (7.3) -18.3 (6.8) -17.7 (7.3) -21.2 (9.8) 1. The average 3-year trend is the average change, per 3-year-period, between the earliest available measurement in PISA and PISA 2018, calculated by a linear regression. *PISA 2018 data did not meet the PISA technical standards but were accepted as largely comparable (see Annexes A2 and A4). **The data for Viet Nam have not yet been fully validated. Due to a lack of consistency in the response pattern of some performance data, the OECD cannot yet assure full international comparability of the results (see Annexes A2 and A4). Notes: Values that are statistically significant are indicated in bold (see Annex A3). Costa Rica, Georgia, Malta and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+. Estimates of the average 3-year trend and the curvilinear trend for these countries consider the year in which the assessment was conducted. The full version of this table is available on line, at the 12 StatLink below. https://doi.org/10.1787/888934029090

252 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex B1 Results for countries and economies Table I.B1.15 [1/2] Distribution of science scores, 2006 through 2018 Average 3-year trend in percentiles of science performance across PISA assessments1 10th percentile 25th percentile Median (50th percentile) 75th percentile 90th percentile Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. OECDAustralia -7.6 (1.4) -7.7 (1.3) -6.6 (1.3) -5.9 (1.3) -6.0 (1.4) Austria -4.7 (2.0) -6.4 (1.9) -6.3 (1.7) -5.7 (1.6) -5.1 (1.6) Belgium -2.2 (1.9) -3.5 (1.5) -3.3 (1.4) -3.3 (1.3) -2.5 (1.3) Canada -4.3 (1.4) -4.3 (1.3) -3.8 (1.3) -3.0 (1.3) -2.0 (1.4) Chile 1.9 (1.6) 1.7 (1.5) 1.6 (1.6) 0.8 (1.9) -0.7 (1.8) Colombia 8.0 (1.7) 5.5 (1.7) 5.0 (1.5) 6.1 (1.7) 7.3 (1.7) Czech Republic -3.2 (1.8) -3.9 (1.6) -4.4 (1.5) -4.5 (1.5) -4.9 (1.6) Denmark 0.2 (1.7) -0.1 (1.5) -0.3 (1.4) -0.8 (1.4) -1.2 (1.5) Estonia -1.3 (1.7) -0.9 (1.4) 0.4 (1.3) 1.5 (1.4) 2.1 (1.5) Finland -15.5 (1.6) -12.8 (1.4) -10.3 (1.3) -8.1 (1.3) -7.2 (1.4) France 0.7 (1.8) -1.0 (1.7) -1.4 (1.6) -1.4 (1.5) -1.7 (1.5) Germany -4.2 (2.1) -4.4 (1.8) -3.8 (1.6) -3.3 (1.5) -2.6 (1.4) Greece -5.3 (2.0) -6.6 (1.8) -6.4 (1.6) -6.1 (1.5) -6.4 (1.5) Hungary -10.6 (1.8) -10.1 (1.5) -7.3 (1.5) -5.0 (1.4) -3.6 (1.5) Iceland -3.8 (1.5) -5.7 (1.4) -6.1 (1.3) -6.4 (1.3) -6.1 (1.4) Ireland -0.7 (1.6) -2.1 (1.5) -3.6 (1.4) -4.5 (1.5) -5.0 (1.6) Israel 2.0 (1.9) 2.1 (1.9) 3.3 (1.8) 3.5 (1.7) 2.9 (1.7) Italy -0.9 (1.5) -1.3 (1.4) -2.4 (1.4) -3.3 (1.3) -4.3 (1.5) Japan 2.3 (2.0) -0.2 (1.7) -1.5 (1.5) -2.0 (1.4) -2.2 (1.4) Korea -7.6 (1.8) -5.3 (1.6) -2.5 (1.5) -0.7 (1.5) 1.0 (1.7) Latvia -1.4 (1.7) -1.4 (1.5) -1.1 (1.4) -0.3 (1.4) 0.1 (1.4) Lithuania -3.7 (1.5) -3.6 (1.4) -3.3 (1.4) -2.1 (1.4) -1.5 (1.5) Luxembourg -1.4 (1.5) -3.7 (1.3) -3.2 (1.2) -1.4 (1.2) -0.6 (1.3) Mexico 4.5 (1.6) 2.7 (1.4) 1.5 (1.4) 0.4 (1.4) -0.2 (1.5) Netherlands* -8.5 (2.0) -7.6 (1.8) -5.8 (1.7) -3.8 (1.4) -2.9 (1.5) New Zealand -5.1 (1.6) -6.0 (1.5) -6.5 (1.5) -7.1 (1.4) -7.1 (1.4) Norway -2.7 (1.7) -0.5 (1.5) 1.3 (1.4) 1.6 (1.4) 1.9 (1.5) Poland 1.0 (1.4) 1.5 (1.4) 2.2 (1.4) 2.6 (1.4) 3.0 (1.5) Portugal* 1.7 (1.8) 3.2 (1.6) 4.3 (1.5) 5.7 (1.4) 6.0 (1.5) Slovak Republic -10.0 (1.7) -9.4 (1.4) -7.7 (1.4) -7.0 (1.5) -6.2 (1.5) Slovenia -0.2 (1.5) -0.5 (1.3) -1.8 (1.2) -3.9 (1.2) -5.0 (1.4) Spain -0.9 (1.4) -1.0 (1.3) -0.8 (1.3) -0.3 (1.3) -0.2 (1.3) Sweden -3.8 (1.9) -2.3 (1.6) -0.6 (1.5) 0.4 (1.4) 0.5 (1.5) Switzerland -3.9 (1.7) -5.7 (1.6) -5.1 (1.5) -4.3 (1.6) -3.3 (1.8) Turkey 4.8 (1.5) 5.7 (1.4) 7.1 (1.5) 7.4 (1.8) 5.1 (2.4) United Kingdom -1.0 (1.6) -1.8 (1.5) -2.6 (1.3) -3.3 (1.4) -4.2 (1.4) United States* 3.6 (1.9) 3.4 (1.8) 2.5 (1.7) 1.0 (1.8) -0.2 (1.7) OECD average-36b -2.2 (1.1) -2.4 (1.1) -2.0 (1.1) -1.7 (1.1) -1.6 (1.1) OECD average-37 -2.3 (1.1) -2.5 (1.1) -2.1 (1.1) -1.8 (1.1) -1.7 (1.1) 1. The average 3-year trend is the average change, per 3-year-period, between the earliest available measurement in PISA and PISA 2018, calculated by a linear regression. *PISA 2018 data did not meet the PISA technical standards but were accepted as largely comparable (see Annexes A2 and A4). **The data for Viet Nam have not yet been fully validated. Due to a lack of consistency in the response pattern of some performance data, the OECD cannot yet assure full international comparability of the results (see Annexes A2 and A4). Notes: Values that are statistically significant are indicated in bold (see Annex A3). Costa Rica, Georgia, Malta and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+. Estimates of the average 3-year trend and the curvilinear trend for these countries consider the year in which the assessment was conducted The full version of this table is available on line, at the 12 StatLink below. https://doi.org/10.1787/888934029090

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 253 Results for countries and economies Annex B1 Table I.B1.15 [2/2] Distribution of science scores, 2006 through 2018 Average 3-year trend in percentiles of science performance across PISA assessments1 10th percentile 25th percentile Median (50th percentile) 75th percentile 90th percentile Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. Coef. S.E. PartnersAlbania 19.7 (2.4) 13.4 (2.2) 9.2 (2.2) 5.6 (2.2) 4.1 (2.5) Argentina 8.3 (2.3) 4.0 (1.9) 1.5 (1.8) 0.5 (1.8) 0.0 (1.9) Baku (Azerbaijan) m m m m m m m m m m Belarus m m m m m m m m m m Bosnia and Herzegovina m m m m m m m m m m Brazil 1.2 (1.4) 0.9 (1.2) 1.8 (1.3) 3.4 (1.5) 4.0 (1.8) Brunei Darussalam m m m m m m m m m m B-S-J-Z (China) m m m m m m m m m m Bulgaria 2.0 (2.2) -0.3 (2.0) -2.0 (2.2) -3.3 (2.3) -4.6 (2.3) Costa Rica -5.2 (2.3) -6.4 (2.4) -6.7 (2.3) -5.8 (2.4) -5.5 (3.1) Croatia -7.4 (1.6) -6.8 (1.5) -5.8 (1.5) -4.3 (1.4) -2.9 (1.5) Cyprus 3.1 (2.8) -0.6 (2.5) -1.0 (2.5) 0.6 (2.6) 0.7 (2.6) Dominican Republic 6.2 (4.2) 4.9 (3.8) 3.5 (4.3) 3.2 (5.1) 2.0 (7.0) Georgia 10.6 (2.2) 6.7 (2.2) 4.0 (2.2) 3.3 (2.2) 3.4 (2.5) Hong Kong (China)* -5.4 (1.9) -6.3 (1.5) -8.1 (1.4) -9.4 (1.3) -9.6 (1.4) Indonesia 3.0 (1.5) 2.7 (1.6) 2.3 (1.7) 2.2 (2.1) 1.9 (2.8) Jordan 1.1 (1.7) 1.0 (1.5) 0.8 (1.4) 0.3 (1.5) -0.1 (1.6) Kazakhstan 2.2 (1.9) -1.0 (1.8) -4.3 (1.7) -7.1 (1.9) -6.6 (2.5) Kosovo -3.5 (3.6) -8.2 (3.1) -14.4 (2.9) -20.3 (3.1) -24.1 (4.8) Lebanon -10.6 (5.5) -6.9 (5.4) -2.0 (6.2) 2.5 (7.2) 2.6 (7.1) Macao (China) 6.0 (1.3) 7.6 (1.2) 8.4 (1.2) 9.1 (1.2) 9.7 (1.3) Malaysia 6.5 (2.2) 6.0 (1.9) 6.1 (2.0) 6.8 (2.1) 7.5 (2.5) Malta 2.6 (2.2) -0.7 (2.1) -2.2 (2.0) -3.8 (2.2) -4.3 (2.1) Moldova 5.9 (2.4) 4.1 (2.4) 4.4 (2.3) 7.1 (2.1) 8.6 (2.4) Montenegro 1.0 (1.3) 1.4 (1.2) 1.3 (1.2) 1.7 (1.2) 2.6 (1.4) Morocco m m m m m m m m m m North Macedonia 18.9 (3.8) 23.9 (3.1) 29.1 (3.3) 36.1 (4.3) 36.6 (4.8) Panama -0.4 (3.2) -3.3 (3.0) -4.1 (2.8) -5.4 (2.9) -5.5 (3.5) Peru 17.3 (2.2) 13.5 (2.0) 11.7 (2.0) 11.0 (2.3) 10.3 (2.7) Philippines m m m m m m m m m m Qatar 11.3 (1.1) 14.3 (1.1) 19.2 (1.1) 23.1 (1.2) 22.2 (1.4) Romania 0.1 (1.8) 0.8 (1.8) 2.1 (1.9) 3.3 (1.9) 4.5 (2.1) Russia 2.5 (1.8) 1.4 (1.6) 0.6 (1.6) -0.6 (1.5) -1.9 (1.6) Saudi Arabia m m m m m m m m m m Serbia -1.8 (1.6) -1.3 (1.5) 0.0 (1.5) 1.9 (1.6) 4.4 (1.7) Singapore 4.4 (2.1) 5.6 (1.7) 4.4 (1.8) 1.8 (1.7) -0.9 (1.8) Chinese Taipei -4.6 (1.7) -3.2 (1.8) -2.5 (1.5) -0.9 (1.5) 0.5 (1.4) Thailand -0.5 (1.5) -0.9 (1.4) 0.1 (1.4) 1.6 (1.6) 2.3 (1.7) Ukraine m m m m m m m m m m United Arab Emirates -6.5 (2.4) -6.2 (2.4) -3.7 (2.4) 0.9 (2.4) 3.0 (2.4) Uruguay 4.0 (1.7) 1.1 (1.5) -0.4 (1.4) -1.0 (1.5) -1.9 (1.6) Viet Nam** -0.7 (8.4) -8.5 (7.0) -7.9 (6.2) -4.2 (6.3) -0.9 (9.1) 1. The average 3-year trend is the average change, per 3-year-period, between the earliest available measurement in PISA and PISA 2018, calculated by a linear regression. *PISA 2018 data did not meet the PISA technical standards but were accepted as largely comparable (see Annexes A2 and A4). **The data for Viet Nam have not yet been fully validated. Due to a lack of consistency in the response pattern of some performance data, the OECD cannot yet assure full international comparability of the results (see Annexes A2 and A4). Notes: Values that are statistically significant are indicated in bold (see Annex A3). Costa Rica, Georgia, Malta and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+. Estimates of the average 3-year trend and the curvilinear trend for these countries consider the year in which the assessment was conducted The full version of this table is available on line, at the 12 StatLink below. https://doi.org/10.1787/888934029090

254 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex B1 Results for countries and economies Annex B1 List of tables available on line https://doi.org/10.1787/888934029090 WEB Table I.B1.16 Percentage of students at each level on the cognitive process subscale of reading "locate information" WEB Table I.B1.17 Percentage of students at each level on the cognitive process subscale of reading "understand" WEB Table I.B1.18 Percentage of students at each level on the cognitive process subscale of reading "evaluate and reflect" WEB Table I.B1.19 Percentage of students at each level on the text structure subscale of reading "single" WEB Table I.B1.20 Percentage of students at each level on the text structure subscale of reading "multiple" WEB Table I.B1.21 Mean score and variation in the cognitive process subscale of reading "locate information" WEB Table I.B1.22 Mean score and variation in the cognitive process subscale of reading "understand" WEB Table I.B1.23 Mean score and variation in the cognitive process subscale of reading "evaluate and reflect" WEB Table I.B1.24 Mean score and variation in the text structure subscale of reading "single" WEB Table I.B1.25 Mean score and variation in the text structure subscale of reading "multiple" WEB Table I.B1.26 Top performers in reading, mathematics and science WEB Table I.B1.27 Low achievers in reading, mathematics and science WEB Table I.B1.28 Variation in reading performance, 2000 through 2018 WEB Table I.B1.29 Variation in mathematics performance, 2003 through 2018 WEB Table I.B1.30 Variation in science performance, 2006 through 2018 WEB Table I.B1.31 Percentage of low achievers and top performers in reading among all 15-year-olds, 2009 through 2018 WEB Table I.B1.32 Percentage of low achievers and top performers in mathematics among all 15-year-olds, 2006 through 2018 WEB Table I.B1.33 Percentage of low achievers and top performers in sicence among all 15-year-olds, 2009 through 2018 WEB Table I.B1.34 Distribution of reading scores among 15-year-olds, 2009 through 2018 WEB Table I.B1.35 Distribution of mathematics scores among 15-year-olds, 2003 through 2018 WEB Table I.B1.36 Distribution of science scores among 15-year-olds, 2006 through 2018 WEB Table I.B1.37 Percentage of low achievers and top performers in reading, 2009 through 2018, adjusted for demographic changes WEB Table I.B1.38 Percentage of low achievers and top performers in mathematics, 2012 through 2018, adjusted for demographic changes WEB Table I.B1.39 Percentage of low achievers and top performers in science, in 2015 and 2018, adjusted for demographic changes WEB Table I.B1.40 Mean reading performance, 2009 through 2018, adjusted for demographic changes WEB Table I.B1.41 Mean mathematics performance, 2012 through 2018, adjusted for demographic changes WEB Table I.B1.42 Mean science performance, 2015 and 2018, adjusted for demographic changes WEB Table I.B1.43 Distribution of reading scores, 2009 through 2018, adjusted for demographic changes WEB Table I.B1.44 Distribution of mathematics scores, 2012 through 2018, adjusted for demographic changes WEB Table I.B1.45 Distribution of science scores, 2015 and 2018, adjusted for demographic changes WEB Table I.B1.46 Variation in reading performance, 2009 through 2018, adjusted for demographic changes WEB Table I.B1.47 Variation in mathematics performance, 2012 through 2018, adjusted for demographic changes WEB Table I.B1.48 Variation in science performance, 2015 and 2018, adjusted for demographic changes WEB Table I.B1.49 Minimum achievement in reading and mathematics (SDG 4.1) WEB Table I.B1.50 Disparities in minimum achievement in reading and mathematics (SDG 4.5) WEB Table I.B1.51 Time spent using the Internet (2012) WEB Table I.B1.52 Time spent using the Internet (2018) WEB Table I.B1.53 Change in time spent using the Internet (2012 to 2018) WEB Table I.B1.54 Availability of digital devices at home (2009) WEB Table I.B1.55 Availability of digital devices at home (2018) WEB Table I.B1.56 Change in the vailability of digital devices at home (2012 to 2018) WEB Table I.B1.57 Students’ reading habits and attitudes towards reading (2009) WEB Table I.B1.58 Students’ reading habits and attitudes towards reading (2018) WEB Table I.B1.59 Changes in students’ reading habits and attitudes towards reading (2009 to 2018)

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 255 Results for regions within countries Annex B2 Table I.B2.9 [1/2] Mean score and variation in reading performance, by region Mean score Standard deviation Percentiles 5th 10th 25th Median (50th) 75th 90th 95th Mean S.E. S.D. S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. OECDBelgium Flemish Community* 502 (3.4) 104 (1.9) 323 (6.3) 359 (6.4) 429 (5.1) 506 (4.1) 579 (3.1) 633 (3.2) 664 (4.1) French Community 481 (3.0) 100 (1.8) 310 (6.9) 345 (4.7) 412 (4.2) 487 (3.8) 553 (3.6) 608 (3.9) 636 (3.9) German-speaking Community 483 (4.6) 91 (3.5) 324 (12.0) 360 (12.1) 423 (9.0) 485 (7.3) 548 (7.2) 602 (9.3) 628 (9.8) Canada Alberta 532 (4.3) 101 (2.3) 357 (8.9) 396 (7.6) 464 (5.7) 537 (4.6) 604 (4.8) 659 (5.2) 689 (6.6) British Columbia 519 (4.5) 104 (2.1) 342 (8.2) 380 (6.7) 448 (6.1) 524 (5.7) 595 (4.8) 649 (4.3) 680 (5.9) Manitoba 494 (3.4) 99 (1.6) 329 (6.4) 366 (5.1) 427 (4.5) 497 (4.0) 562 (4.9) 621 (5.7) 655 (6.1) New Brunswick 489 (3.5) 103 (2.4) 316 (7.1) 352 (5.9) 419 (5.3) 490 (4.4) 564 (5.9) 621 (7.8) 656 (9.4) Newfoundland and Labrador 512 (4.3) 99 (2.8) 344 (9.5) 383 (7.7) 442 (6.6) 514 (5.2) 581 (6.2) 638 (7.4) 671 (9.5) Nova Scotia 516 (3.9) 102 (2.3) 343 (8.3) 383 (6.1) 447 (5.4) 519 (4.2) 586 (4.4) 645 (7.8) 679 (7.5) Ontario 524 (3.5) 101 (1.6) 352 (5.6) 390 (5.0) 455 (4.7) 528 (4.2) 596 (4.0) 650 (4.3) 681 (5.4) Prince Edward Island 503 (8.3) 103 (5.6) 325 (26.6) 364 (18.4) 435 (13.2) 509 (8.1) 574 (11.0) 635 (10.9) 662 (12.9) Québec 519 (3.5) 94 (1.8) 358 (5.8) 396 (4.8) 457 (4.2) 523 (4.0) 586 (4.3) 637 (4.4) 666 (4.5) Saskatchewan 499 (3.0) 95 (2.2) 338 (6.9) 376 (6.2) 436 (4.3) 501 (3.8) 565 (4.0) 621 (4.7) 651 (7.0) Colombia Bogotá 455 (5.4) 90 (2.9) 310 (7.5) 339 (7.2) 392 (6.0) 451 (6.0) 518 (7.1) 575 (7.9) 606 (8.3) Italy Bolzano 495 (3.3) 89 (2.0) 344 (7.6) 377 (6.2) 435 (4.2) 500 (4.2) 560 (4.7) 607 (5.9) 633 (7.6) Sardegna 462 (4.1) 92 (2.1) 310 (6.4) 340 (6.0) 397 (6.0) 464 (4.8) 527 (4.6) 580 (5.1) 612 (6.6) Toscana 482 (4.0) 94 (2.4) 315 (9.9) 355 (8.3) 420 (5.6) 490 (5.3) 550 (4.3) 597 (4.2) 625 (5.9) Trento 496 (2.3) 93 (2.0) 340 (6.1) 371 (5.0) 430 (3.9) 499 (3.7) 564 (5.3) 615 (4.9) 643 (6.7) Spain Andalusia m m m m m m m m m m m m m m m m m m Aragon m m m m m m m m m m m m m m m m m m Asturias m m m m m m m m m m m m m m m m m m Balearic Islands m m m m m m m m m m m m m m m m m m Basque Country m m m m m m m m m m m m m m m m m m Canary Islands m m m m m m m m m m m m m m m m m m Cantabria m m m m m m m m m m m m m m m m m m Castile and León m m m m m m m m m m m m m m m m m m Castile-La Mancha m m m m m m m m m m m m m m m m m m Catalonia m m m m m m m m m m m m m m m m m m Ceuta m m m m m m m m m m m m m m m m m m Comunidad Valenciana m m m m m m m m m m m m m m m m m m Extremadura m m m m m m m m m m m m m m m m m m Galicia m m m m m m m m m m m m m m m m m m La Rioja m m m m m m m m m m m m m m m m m m Madrid m m m m m m m m m m m m m m m m m m Melilla m m m m m m m m m m m m m m m m m m Murcia m m m m m m m m m m m m m m m m m m Navarre m m m m m m m m m m m m m m m m m m United Kingdom England 505 (3.0) 101 (1.5) 334 (5.1) 372 (5.2) 436 (3.9) 508 (3.2) 577 (3.5) 634 (4.1) 666 (4.5) Northern Ireland 501 (4.0) 98 (2.2) 332 (7.0) 368 (5.8) 434 (5.3) 506 (5.0) 571 (5.2) 623 (5.6) 655 (6.0) Scotland* 504 (3.0) 95 (1.9) 349 (5.5) 383 (3.6) 439 (3.5) 503 (3.7) 571 (4.2) 627 (4.7) 657 (5.9) Wales 483 (4.0) 97 (1.6) 322 (5.7) 359 (5.8) 417 (4.8) 484 (4.3) 552 (4.2) 608 (4.5) 640 (6.1) * PISA adjudicated region. 1Note: See Table I.B1.4 for national data. 2https://doi.org/10.1787/888934029109 ANNEX B2 Results for regions within countries

256 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex B2 Results for regions within countries Table I.B2.9 [2/2] Mean score and variation in reading performance, by region Mean score Standard deviation Percentiles 5th 10th 25th Median (50th) 75th 90th 95th Mean S.E. S.D. S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. PartnersArgentina CABA* 454 (5.4) 93 (2.3) 294 (8.1) 328 (8.0) 390 (7.3) 459 (6.4) 522 (5.6) 572 (5.2) 598 (6.3) Córdoba* 427 (4.5) 91 (2.5) 274 (5.8) 305 (5.5) 362 (5.6) 431 (5.3) 493 (5.5) 543 (6.4) 571 (6.9) PBA* 413 (5.8) 97 (2.3) 251 (7.3) 286 (7.0) 346 (6.1) 414 (7.1) 482 (7.0) 539 (6.9) 571 (7.2) Tucumán* 389 (5.0) 96 (2.5) 237 (6.8) 267 (5.5) 319 (5.1) 387 (6.6) 457 (7.3) 516 (6.5) 548 (7.0) Brazil North 392 (6.9) 91 (2.6) 254 (7.6) 280 (8.6) 328 (7.1) 383 (8.7) 451 (9.6) 514 (11.8) 558 (10.9) Northeast 389 (4.2) 99 (3.1) 243 (4.9) 269 (4.8) 316 (4.3) 378 (5.2) 456 (5.8) 525 (7.4) 566 (8.7) South 432 (6.3) 97 (3.0) 278 (8.3) 308 (7.5) 362 (6.9) 430 (7.5) 500 (9.3) 562 (8.6) 596 (8.9) Southeast 424 (3.0) 98 (1.6) 264 (3.8) 296 (3.3) 353 (3.3) 421 (3.6) 494 (4.2) 555 (4.9) 588 (5.9) Middle-West 425 (9.1) 103 (6.1) 269 (10.8) 294 (10.0) 348 (10.1) 418 (11.0) 493 (12.1) 565 (14.9) 608 (22.2) Indonesia DI Yogyakarta 414 (5.8) 83 (3.2) 283 (6.0) 309 (5.8) 352 (5.3) 411 (7.1) 472 (8.6) 527 (10.4) 557 (11.2) DKI Jakarta 412 (7.0) 83 (4.9) 288 (6.3) 310 (4.6) 352 (5.6) 404 (6.5) 468 (11.0) 528 (15.6) 562 (18.6) Kazakhstan Akmola region 395 (4.5) 78 (2.0) 271 (6.0) 294 (6.1) 339 (6.0) 394 (5.6) 449 (6.6) 498 (6.2) 528 (7.7) Aktobe region 381 (4.3) 69 (2.2) 278 (6.9) 298 (5.4) 332 (4.7) 376 (5.1) 422 (5.4) 470 (6.0) 503 (9.7) Almaty 424 (7.8) 86 (4.5) 296 (6.8) 320 (7.0) 363 (7.8) 416 (8.1) 479 (10.3) 542 (16.1) 579 (16.1) Almaty region 360 (4.4) 67 (2.2) 254 (5.6) 273 (5.6) 312 (5.4) 359 (5.4) 402 (5.7) 449 (7.7) 479 (9.3) Astana 428 (7.4) 81 (3.3) 302 (8.2) 327 (8.7) 371 (7.4) 422 (8.6) 480 (10.1) 538 (10.3) 570 (12.4) Atyrau region 344 (4.4) 68 (2.8) 241 (5.3) 261 (5.2) 295 (5.6) 340 (5.4) 385 (5.1) 430 (6.2) 461 (8.5) East-Kazakhstan region 405 (6.4) 78 (3.7) 285 (11.2) 306 (10.3) 351 (8.4) 401 (6.0) 456 (8.3) 509 (9.3) 539 (11.4) Karagandy region 422 (6.8) 84 (3.2) 298 (8.7) 321 (6.2) 363 (6.2) 415 (7.8) 477 (10.2) 538 (12.1) 573 (11.1) Kostanay region 417 (5.1) 77 (2.2) 296 (8.8) 317 (7.8) 363 (6.6) 415 (6.3) 469 (6.1) 521 (5.6) 549 (5.5) Kyzyl-Orda region 366 (2.8) 59 (2.1) 277 (4.7) 295 (4.7) 326 (4.1) 363 (3.9) 402 (3.6) 442 (5.0) 468 (5.8) Mangistau region 361 (5.8) 70 (3.2) 259 (9.1) 280 (6.8) 313 (5.7) 353 (6.2) 399 (7.2) 455 (11.9) 492 (12.6) North-Kazakhstan region 413 (5.0) 78 (2.2) 289 (7.0) 313 (5.5) 359 (5.7) 411 (5.7) 464 (7.1) 512 (6.5) 545 (9.6) Pavlodar region 391 (6.5) 82 (2.4) 265 (9.0) 288 (7.8) 331 (7.5) 386 (7.8) 446 (7.6) 501 (8.3) 533 (9.3) South-Kazakhstan region 368 (3.5) 64 (2.3) 266 (6.2) 288 (5.9) 326 (5.2) 367 (4.2) 408 (4.1) 447 (5.8) 472 (6.8) West-Kazakhstan region 378 (4.9) 71 (2.3) 269 (6.6) 291 (5.3) 328 (5.4) 373 (5.8) 423 (6.2) 474 (8.0) 506 (9.5) Zhambyl region 369 (3.6) 63 (2.2) 277 (5.5) 295 (4.3) 325 (3.3) 363 (4.0) 406 (4.8) 451 (7.0) 483 (8.8) Russia Moscow region* 486 (4.7) 92 (2.1) 327 (8.4) 364 (7.9) 424 (6.2) 488 (5.3) 552 (4.4) 604 (4.6) 632 (4.8) Republic of Tatarstan* 463 (3.1) 91 (1.6) 313 (4.8) 345 (3.8) 399 (3.6) 462 (3.5) 526 (3.5) 581 (4.4) 613 (5.2) * PISA adjudicated region. 1Note: See Table I.B1.4 for national data. 2http://dx.doi.org/10.1787/888934029109

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 257 Results for regions within countries Annex B2 Table I.B2.10 [1/2] Mean score and variation in mathematics performance, by region Mean score Standard deviation Percentiles 5th 10th 25th Median (50th) 75th 90th 95th Mean S.E. S.D. S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. OECDBelgium Flemish Community* 518 (3.3) 96 (2.3) 350 (6.3) 384 (6.0) 450 (5.5) 525 (3.6) 589 (3.0) 638 (3.6) 665 (3.9) French Community 495 (2.8) 93 (2.0) 338 (5.4) 368 (4.5) 427 (4.0) 500 (3.6) 564 (3.6) 614 (4.6) 639 (5.2) German-speaking Community 505 (5.2) 79 (3.9) 363 (12.7) 396 (11.8) 452 (7.5) 510 (7.0) 564 (7.3) 604 (9.3) 626 (13.0) Canada Alberta 511 (5.1) 91 (2.9) 356 (9.1) 392 (8.3) 450 (7.0) 513 (5.6) 575 (5.7) 626 (5.9) 655 (7.4) British Columbia 504 (5.2) 94 (2.6) 350 (7.9) 382 (6.8) 441 (6.0) 505 (5.6) 569 (5.7) 624 (6.9) 657 (7.8) Manitoba 482 (3.7) 88 (1.9) 337 (7.1) 368 (5.3) 421 (4.5) 483 (4.5) 542 (4.2) 594 (5.9) 624 (6.1) New Brunswick 491 (5.7) 92 (2.6) 338 (8.3) 373 (7.2) 428 (6.4) 492 (6.4) 555 (7.2) 609 (9.2) 638 (10.8) Newfoundland and Labrador 488 (6.5) 85 (2.4) 351 (10.4) 382 (8.7) 431 (5.9) 487 (6.5) 546 (8.4) 599 (10.6) 629 (11.4) Nova Scotia 494 (6.3) 88 (2.2) 349 (8.3) 380 (8.3) 433 (6.7) 494 (6.3) 555 (6.7) 608 (8.9) 640 (11.2) Ontario 513 (4.4) 91 (2.0) 361 (5.9) 394 (5.2) 450 (4.7) 513 (5.2) 577 (5.5) 629 (5.2) 660 (6.7) Prince Edward Island 487 (11.1) 91 (4.4) 332 (23.0) 369 (16.4) 423 (11.6) 491 (11.7) 551 (14.2) 601 (15.2) 630 (18.1) Québec 532 (3.6) 93 (2.2) 374 (6.8) 411 (6.2) 472 (4.8) 536 (4.0) 596 (4.1) 648 (4.2) 679 (5.2) Saskatchewan 485 (5.0) 82 (2.2) 348 (6.5) 378 (5.4) 430 (5.8) 487 (5.8) 543 (5.4) 589 (5.7) 618 (6.9) Colombia Bogotá 430 (5.0) 81 (2.8) 301 (5.7) 326 (5.2) 372 (5.2) 428 (5.2) 484 (7.3) 536 (8.0) 567 (9.8) Italy Bolzano 521 (3.4) 84 (2.1) 378 (7.5) 410 (5.7) 465 (5.0) 525 (4.5) 582 (4.8) 626 (5.6) 652 (6.2) Sardegna 467 (4.0) 84 (2.3) 331 (7.5) 358 (6.2) 409 (5.1) 468 (4.7) 526 (5.1) 576 (4.9) 602 (5.4) Toscana 496 (4.3) 85 (2.1) 350 (6.4) 382 (6.1) 437 (5.3) 501 (5.7) 556 (5.5) 602 (5.7) 629 (5.6) Trento 518 (2.8) 85 (2.1) 374 (9.2) 406 (5.6) 461 (4.6) 520 (4.2) 578 (3.9) 627 (5.3) 653 (5.8) Spain Andalusia 467 (4.2) 88 (2.1) 318 (6.4) 353 (6.4) 408 (4.7) 470 (5.0) 529 (5.9) 580 (7.3) 609 (6.0) Aragon 497 (5.9) 89 (2.1) 343 (9.9) 377 (7.0) 437 (6.7) 501 (6.4) 560 (5.8) 607 (7.3) 634 (8.4) Asturias 491 (5.0) 88 (2.1) 340 (9.2) 375 (7.2) 431 (5.3) 494 (4.8) 554 (6.0) 602 (6.0) 629 (6.5) Balearic Islands 483 (5.2) 84 (1.9) 340 (8.7) 371 (7.2) 426 (6.2) 487 (5.6) 541 (5.3) 587 (5.6) 614 (6.1) Basque Country 499 (3.5) 85 (1.6) 350 (5.5) 385 (5.1) 443 (4.7) 505 (3.9) 560 (3.8) 604 (3.9) 630 (4.7) Canary Islands 460 (4.5) 85 (2.1) 321 (6.5) 349 (7.1) 400 (5.7) 461 (4.9) 520 (5.6) 571 (7.3) 600 (5.8) Cantabria 499 (7.6) 85 (2.5) 354 (10.1) 387 (8.6) 444 (8.7) 503 (7.5) 558 (7.9) 605 (8.4) 631 (9.4) Castile and León 502 (4.7) 88 (2.1) 349 (10.4) 385 (8.3) 445 (6.4) 508 (5.2) 566 (4.7) 612 (5.3) 637 (6.7) Castile-La Mancha 479 (5.1) 88 (1.6) 332 (7.3) 362 (6.8) 416 (6.0) 482 (5.9) 544 (5.9) 591 (5.3) 617 (6.1) Catalonia 490 (3.9) 88 (2.4) 340 (8.4) 374 (5.9) 430 (5.0) 492 (4.6) 552 (5.4) 601 (6.3) 630 (7.9) Ceuta 411 (12.2) 84 (3.7) 282 (16.5) 308 (14.7) 352 (16.5) 407 (12.9) 467 (13.4) 525 (12.4) 557 (17.9) Comunidad Valenciana 473 (4.6) 84 (1.8) 333 (6.1) 365 (6.3) 417 (4.5) 475 (5.4) 532 (5.4) 581 (5.7) 608 (7.5) Extremadura 470 (6.6) 86 (2.1) 323 (10.0) 357 (7.4) 412 (7.1) 472 (7.5) 530 (6.6) 578 (8.3) 605 (8.3) Galicia 498 (4.3) 87 (2.3) 344 (10.3) 381 (7.1) 442 (5.3) 504 (4.5) 560 (4.3) 606 (6.2) 631 (6.7) La Rioja 497 (9.8) 92 (3.5) 338 (10.1) 374 (10.7) 437 (8.6) 502 (11.0) 562 (11.7) 613 (11.9) 643 (14.0) Madrid 486 (3.2) 89 (1.5) 334 (6.2) 367 (5.0) 425 (4.1) 490 (3.5) 549 (3.6) 598 (3.8) 626 (3.9) Melilla 432 (10.4) 85 (4.4) 299 (17.4) 323 (13.3) 371 (11.7) 428 (12.1) 492 (15.2) 548 (12.9) 572 (17.5) Murcia 474 (5.7) 92 (2.2) 319 (8.8) 353 (7.7) 410 (7.2) 477 (6.0) 539 (7.0) 592 (7.2) 618 (7.7) Navarre 503 (8.4) 87 (2.5) 355 (9.0) 387 (8.4) 444 (9.5) 506 (9.0) 564 (9.0) 612 (9.6) 640 (10.6) United Kingdom England 504 (3.0) 93 (1.7) 347 (5.1) 383 (4.9) 441 (3.4) 506 (3.2) 569 (3.6) 623 (3.7) 654 (4.5) Northern Ireland 492 (4.2) 85 (2.5) 343 (7.8) 377 (6.4) 434 (5.5) 496 (4.4) 553 (5.6) 600 (5.3) 626 (6.8) Scotland* 489 (3.9) 95 (2.9) 331 (9.0) 367 (6.0) 425 (4.9) 490 (4.3) 556 (4.7) 610 (5.7) 642 (6.7) Wales 487 (3.9) 82 (1.5) 350 (5.5) 381 (5.4) 431 (4.2) 488 (4.4) 545 (4.3) 592 (4.4) 619 (5.5) * PISA adjudicated region. 1Note: See Table I.B1.5 for national data. 2http://dx.doi.org/10.1787/888934029109

258 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex B2 Results for regions within countries Table I.B2.10 [2/2] Mean score and variation in mathematics performance, by region Mean score Standard deviation Percentiles 5th 10th 25th Median (50th) 75th 90th 95th Mean S.E. S.D. S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. PartnersArgentina CABA* 434 (4.7) 80 (2.4) 300 (7.7) 331 (6.7) 380 (6.1) 435 (5.7) 490 (4.9) 537 (5.4) 565 (6.4) Córdoba* 400 (4.5) 80 (2.8) 269 (6.7) 296 (5.7) 345 (5.3) 400 (4.8) 456 (5.6) 504 (6.8) 532 (8.7) PBA* 387 (5.1) 84 (2.3) 254 (6.7) 282 (5.7) 330 (6.0) 384 (5.7) 443 (7.2) 498 (6.8) 529 (6.9) Tucumán* 364 (5.1) 81 (2.7) 237 (5.6) 262 (5.7) 308 (5.0) 362 (5.9) 418 (6.8) 472 (7.8) 502 (10.3) Brazil North 366 (7.1) 83 (4.5) 240 (10.1) 266 (9.1) 309 (7.0) 359 (7.3) 415 (10.0) 478 (12.3) 519 (21.4) Northeast 363 (3.7) 86 (3.5) 236 (4.7) 261 (4.2) 303 (4.2) 356 (4.1) 417 (5.1) 478 (7.1) 515 (11.3) South 401 (5.3) 87 (3.0) 266 (8.4) 293 (7.0) 338 (6.4) 396 (7.1) 460 (7.8) 520 (8.1) 554 (8.4) Southeast 392 (3.1) 86 (2.2) 260 (3.6) 286 (3.4) 332 (3.9) 387 (3.3) 448 (4.2) 506 (5.7) 542 (7.0) Middle-West 396 (8.4) 92 (7.0) 258 (10.8) 284 (9.3) 332 (8.2) 389 (8.9) 451 (10.9) 517 (16.4) 562 (26.5) Indonesia DI Yogyakarta 430 (6.5) 86 (3.6) 293 (6.7) 322 (6.0) 370 (6.6) 426 (7.4) 488 (9.0) 545 (10.6) 575 (12.7) DKI Jakarta 421 (7.7) 87 (5.2) 290 (5.7) 315 (4.5) 359 (4.7) 415 (8.9) 478 (11.5) 536 (15.7) 574 (20.0) Kazakhstan Akmola region 411 (6.5) 87 (3.1) 271 (9.7) 301 (8.3) 352 (8.3) 411 (7.1) 470 (7.8) 522 (8.8) 556 (10.8) Aktobe region 420 (6.2) 80 (3.2) 286 (12.4) 319 (8.4) 366 (8.0) 421 (6.6) 474 (7.1) 522 (7.3) 550 (6.8) Almaty 448 (7.3) 90 (3.4) 302 (10.8) 334 (9.0) 386 (8.0) 447 (8.6) 508 (9.0) 567 (11.0) 603 (12.4) Almaty region 399 (5.2) 80 (2.4) 268 (8.3) 297 (6.9) 345 (5.9) 399 (5.7) 453 (6.7) 502 (7.2) 530 (9.5) Astana 450 (7.7) 89 (3.5) 309 (10.7) 339 (9.5) 390 (9.0) 447 (8.5) 509 (9.4) 568 (10.1) 602 (10.8) Atyrau region 382 (7.1) 80 (3.0) 251 (11.5) 281 (9.3) 330 (7.7) 382 (7.8) 434 (7.9) 481 (9.4) 513 (9.2) East-Kazakhstan region 437 (7.3) 88 (4.2) 293 (14.1) 327 (11.0) 379 (8.9) 438 (7.4) 495 (8.5) 549 (10.8) 580 (11.4) Karagandy region 446 (7.4) 90 (4.3) 307 (8.2) 335 (7.3) 384 (7.1) 442 (7.9) 503 (8.6) 562 (13.3) 602 (16.5) Kostanay region 448 (6.6) 86 (4.1) 303 (14.2) 338 (11.3) 391 (9.3) 450 (7.7) 506 (6.5) 557 (7.0) 585 (7.6) Kyzyl-Orda region 419 (8.3) 81 (3.8) 284 (13.5) 316 (11.6) 366 (9.8) 421 (9.3) 474 (8.4) 520 (10.8) 550 (11.7) Mangistau region 391 (9.1) 84 (3.6) 255 (12.1) 285 (9.5) 335 (10.0) 388 (9.3) 445 (10.7) 501 (14.6) 535 (13.1) North-Kazakhstan region 433 (5.4) 83 (2.6) 298 (9.6) 328 (7.3) 378 (5.6) 431 (5.9) 488 (7.5) 540 (8.2) 571 (10.5) Pavlodar region 438 (5.9) 82 (3.3) 304 (8.9) 332 (9.3) 381 (7.1) 438 (7.1) 493 (7.9) 543 (7.3) 573 (8.8) South-Kazakhstan region 401 (5.6) 83 (2.8) 267 (10.6) 297 (7.5) 348 (6.6) 401 (5.9) 454 (6.1) 506 (8.4) 539 (10.6) West-Kazakhstan region 418 (6.5) 82 (2.4) 283 (11.1) 313 (8.3) 362 (8.6) 418 (7.3) 474 (7.4) 524 (8.5) 554 (8.9) Zhambyl region 456 (6.0) 74 (2.8) 331 (9.9) 360 (8.7) 406 (6.2) 456 (6.5) 507 (6.5) 550 (7.7) 576 (8.1) Russia Moscow region* 495 (4.2) 81 (2.0) 360 (7.1) 388 (7.2) 439 (5.4) 496 (4.9) 552 (4.1) 598 (4.6) 625 (6.1) Republic of Tatarstan* 475 (3.1) 84 (1.8) 337 (4.3) 367 (3.8) 417 (3.4) 475 (3.4) 533 (3.5) 584 (4.5) 614 (5.6) * PISA adjudicated region. 1Note: See Table I.B1.5 for national data. 2http://dx.doi.org/10.1787/888934029109

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 259 Results for regions within countries Annex B2 Table I.B2.11 [1/2] Mean score and variation in science performance, by region Mean score Standard deviation Percentiles 5th 10th 25th Median (50th) 75th 90th 95th Mean S.E. S.D. S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. OECDBelgium Flemish Community* 510 (3.3) 100 (2.1) 334 (6.6) 370 (5.9) 439 (5.3) 518 (4.3) 584 (3.4) 635 (3.4) 663 (3.9) French Community 485 (2.8) 95 (1.7) 322 (5.5) 354 (5.7) 418 (4.2) 491 (3.6) 554 (3.1) 605 (3.9) 633 (4.0) German-speaking Community 483 (7.4) 86 (3.2) 335 (11.4) 363 (12.2) 425 (10.1) 487 (8.8) 544 (9.2) 596 (11.9) 621 (9.9) Canada Alberta 534 (4.4) 96 (2.4) 369 (7.6) 404 (6.3) 468 (5.8) 538 (4.8) 602 (5.0) 654 (6.3) 684 (7.6) British Columbia 517 (5.4) 101 (2.6) 346 (9.1) 383 (7.5) 446 (5.7) 519 (6.2) 589 (6.6) 647 (6.9) 679 (7.4) Manitoba 489 (3.7) 95 (1.7) 337 (7.2) 366 (5.6) 423 (5.1) 489 (4.4) 556 (4.8) 612 (4.0) 645 (6.4) New Brunswick 492 (5.7) 96 (2.8) 336 (9.8) 369 (8.5) 427 (7.0) 493 (6.8) 559 (6.4) 617 (7.6) 650 (10.3) Newfoundland and Labrador 506 (6.4) 94 (2.7) 354 (11.2) 387 (9.4) 442 (7.2) 505 (7.4) 569 (6.5) 628 (9.6) 663 (10.5) Nova Scotia 508 (4.7) 94 (2.1) 349 (7.9) 383 (7.2) 444 (6.3) 510 (4.8) 574 (5.1) 629 (6.6) 662 (8.3) Ontario 519 (4.0) 95 (1.7) 361 (5.8) 395 (4.9) 453 (5.2) 519 (5.1) 587 (4.9) 641 (5.0) 672 (5.5) Prince Edward Island 502 (8.9) 97 (4.4) 335 (16.5) 369 (16.6) 436 (12.2) 508 (10.7) 571 (10.5) 625 (16.5) 654 (15.7) Québec 522 (3.7) 91 (1.9) 365 (7.2) 401 (6.0) 461 (4.5) 526 (4.1) 585 (4.3) 635 (4.0) 663 (5.4) Saskatchewan 501 (3.9) 91 (2.2) 346 (7.7) 382 (6.4) 440 (5.3) 502 (4.3) 564 (4.2) 617 (6.0) 647 (6.9) Colombia Bogotá 451 (4.9) 84 (2.6) 316 (6.4) 343 (5.9) 391 (5.9) 449 (6.0) 509 (6.4) 560 (7.0) 590 (7.4) Italy Bolzano 498 (4.2) 84 (1.9) 354 (7.0) 385 (5.8) 440 (5.5) 502 (5.0) 559 (5.0) 605 (6.1) 630 (6.0) Sardegna 452 (3.9) 83 (1.9) 318 (6.9) 345 (5.4) 393 (4.9) 451 (4.9) 509 (4.8) 560 (5.3) 589 (6.2) Toscana 475 (4.2) 85 (2.4) 327 (8.3) 359 (7.2) 418 (5.9) 479 (5.5) 536 (4.9) 582 (5.0) 608 (5.5) Trento 495 (2.1) 84 (1.7) 353 (6.1) 383 (5.0) 437 (2.9) 497 (3.8) 554 (3.7) 605 (4.6) 633 (6.0) Spain Andalusia 471 (4.4) 90 (2.3) 324 (6.8) 353 (5.1) 406 (5.8) 471 (5.6) 535 (5.8) 589 (5.6) 619 (7.2) Aragon 493 (5.3) 89 (1.8) 340 (8.7) 373 (6.8) 433 (5.8) 498 (5.8) 557 (5.3) 606 (5.8) 635 (7.4) Asturias 496 (4.8) 89 (2.2) 348 (7.3) 379 (6.9) 433 (5.4) 500 (5.1) 561 (5.6) 609 (6.2) 636 (8.3) Balearic Islands 482 (5.2) 84 (1.7) 339 (8.0) 371 (7.5) 425 (5.8) 483 (5.7) 542 (5.7) 591 (6.7) 618 (7.0) Basque Country 487 (4.2) 85 (1.5) 344 (5.4) 374 (5.2) 429 (5.0) 490 (4.4) 547 (4.6) 595 (5.1) 624 (6.1) Canary Islands 470 (4.5) 87 (1.7) 326 (8.3) 357 (5.7) 410 (5.3) 470 (4.9) 530 (5.0) 582 (5.8) 612 (6.0) Cantabria 495 (9.2) 86 (2.3) 351 (10.3) 381 (9.4) 436 (9.4) 498 (9.9) 556 (10.4) 606 (10.2) 633 (11.1) Castile and León 501 (5.0) 88 (1.9) 348 (8.0) 383 (7.5) 443 (6.9) 506 (5.5) 563 (5.0) 611 (5.8) 639 (5.6) Castile-La Mancha 484 (6.1) 88 (1.7) 339 (8.0) 369 (7.4) 422 (7.0) 485 (6.5) 549 (6.1) 598 (6.9) 625 (8.1) Catalonia 489 (4.7) 91 (2.3) 337 (7.8) 368 (8.0) 427 (5.7) 492 (5.5) 554 (5.2) 604 (5.6) 632 (6.0) Ceuta 415 (6.6) 83 (3.7) 290 (11.0) 314 (10.4) 354 (10.0) 410 (8.7) 470 (10.2) 528 (12.5) 563 (12.2) Comunidad Valenciana 478 (4.4) 86 (1.9) 336 (7.6) 367 (6.5) 418 (4.5) 479 (5.2) 538 (5.4) 588 (6.0) 615 (6.5) Extremadura 473 (5.9) 87 (1.7) 331 (9.1) 362 (7.5) 414 (7.1) 473 (6.0) 534 (6.3) 587 (5.8) 617 (6.6) Galicia 510 (4.0) 89 (2.3) 357 (9.3) 392 (6.5) 452 (4.9) 515 (4.2) 574 (5.0) 622 (6.2) 650 (7.5) La Rioja 487 (7.9) 90 (2.0) 335 (8.0) 367 (8.1) 425 (7.7) 489 (8.2) 550 (8.7) 600 (8.6) 629 (9.0) Madrid 487 (3.0) 89 (1.6) 338 (4.5) 369 (4.7) 425 (4.4) 489 (3.4) 550 (3.3) 600 (3.4) 628 (3.6) Melilla 439 (7.6) 86 (4.5) 301 (18.5) 332 (14.0) 378 (9.2) 435 (9.1) 499 (12.9) 555 (12.4) 584 (20.5) Murcia 479 (5.7) 93 (2.3) 324 (8.1) 355 (8.0) 413 (6.9) 482 (6.2) 547 (5.9) 598 (7.1) 627 (7.3) Navarre 492 (6.0) 87 (2.4) 347 (8.0) 377 (7.3) 432 (6.5) 494 (6.7) 554 (6.3) 603 (7.2) 632 (8.9) United Kingdom England 507 (3.0) 100 (1.6) 340 (5.6) 375 (4.6) 439 (3.8) 509 (3.2) 578 (3.6) 635 (3.8) 667 (4.3) Northern Ireland 491 (4.6) 92 (2.1) 337 (6.8) 370 (5.7) 428 (5.5) 494 (5.4) 558 (5.9) 609 (6.2) 637 (7.4) Scotland* 490 (4.0) 98 (2.9) 332 (7.5) 366 (5.7) 422 (4.8) 490 (5.0) 558 (4.7) 617 (5.9) 650 (5.8) Wales 488 (3.8) 89 (1.5) 340 (5.5) 371 (5.3) 426 (4.4) 490 (4.5) 552 (4.3) 603 (4.6) 632 (5.3) * PISA adjudicated region. 1Note: See Table I.B1.6 for national data. 2http://dx.doi.org/10.1787/888934029109

260 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex B2 Results for regions within countries Table I.B2.11 [2/2] Mean score and variation in science performance, by region Mean score Standard deviation Percentiles 5th 10th 25th Median (50th) 75th 90th 95th Mean S.E. S.D. S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. Score S.E. PartnersArgentina CABA* 455 (5.4) 88 (2.1) 308 (6.7) 339 (6.7) 393 (6.8) 456 (6.3) 517 (6.3) 569 (5.4) 598 (6.7) Córdoba* 427 (4.6) 86 (2.5) 286 (6.6) 316 (5.8) 366 (5.0) 426 (5.1) 488 (6.3) 542 (6.5) 569 (8.4) PBA* 413 (5.5) 89 (2.4) 273 (7.3) 302 (6.5) 350 (6.5) 410 (6.7) 476 (7.1) 531 (6.9) 562 (7.1) Tucumán* 391 (5.1) 87 (2.5) 256 (6.2) 283 (6.0) 329 (4.8) 385 (5.8) 449 (7.4) 507 (7.6) 541 (8.4) Brazil North 384 (6.0) 81 (2.8) 263 (8.0) 285 (7.8) 327 (6.6) 378 (7.4) 435 (7.5) 494 (10.2) 530 (9.9) Northeast 383 (3.7) 88 (3.1) 254 (5.3) 278 (4.9) 319 (3.5) 372 (4.0) 440 (5.6) 504 (6.5) 542 (9.9) South 419 (5.9) 90 (3.2) 282 (9.0) 308 (5.8) 354 (6.9) 414 (6.9) 480 (8.6) 542 (8.4) 574 (8.3) Southeast 414 (3.0) 89 (1.8) 276 (3.7) 301 (3.4) 348 (2.9) 408 (3.6) 475 (4.7) 534 (5.4) 569 (6.8) Middle-West 415 (8.1) 95 (6.5) 278 (10.6) 302 (9.3) 346 (9.3) 406 (9.0) 473 (9.7) 547 (17.3) 593 (27.3) Indonesia DI Yogyakarta 439 (5.2) 74 (2.9) 322 (4.7) 346 (3.9) 386 (5.5) 437 (6.1) 491 (6.9) 537 (9.2) 564 (9.6) DKI Jakarta 428 (6.4) 76 (4.5) 314 (5.7) 335 (4.9) 373 (5.1) 422 (6.6) 477 (9.0) 530 (14.3) 563 (17.3) Kazakhstan Akmola region 401 (5.0) 77 (2.8) 278 (9.0) 304 (7.1) 348 (6.1) 399 (5.8) 453 (6.8) 501 (6.3) 529 (8.0) Aktobe region 389 (5.1) 68 (2.5) 286 (8.6) 308 (6.3) 344 (4.9) 384 (4.9) 428 (5.5) 474 (8.8) 509 (10.2) Almaty 431 (8.4) 84 (4.5) 303 (8.6) 327 (9.1) 370 (7.8) 423 (9.9) 485 (12.1) 547 (15.7) 583 (14.8) Almaty region 380 (4.6) 66 (2.7) 276 (8.6) 298 (6.5) 336 (5.3) 378 (5.0) 423 (5.1) 465 (8.2) 494 (9.1) Astana 428 (7.6) 83 (4.4) 301 (11.3) 326 (8.7) 369 (8.3) 423 (8.6) 482 (10.1) 537 (10.9) 570 (12.0) Atyrau region 361 (5.4) 64 (3.0) 263 (9.4) 282 (8.4) 319 (6.9) 358 (5.6) 399 (5.9) 440 (7.1) 469 (9.8) East-Kazakhstan region 413 (5.6) 75 (3.4) 297 (9.2) 320 (7.8) 361 (6.3) 408 (6.6) 463 (8.3) 516 (8.4) 543 (7.7) Karagandy region 428 (7.3) 83 (4.2) 304 (6.8) 328 (6.1) 370 (6.2) 419 (7.2) 481 (10.8) 543 (14.6) 576 (13.3) Kostanay region 426 (5.9) 75 (2.4) 305 (10.3) 330 (7.7) 373 (7.0) 425 (7.4) 476 (7.1) 526 (6.9) 553 (6.8) Kyzyl-Orda region 374 (4.8) 60 (2.9) 280 (9.6) 302 (7.8) 335 (6.5) 372 (5.6) 411 (5.1) 450 (6.3) 477 (6.3) Mangistau region 365 (4.9) 66 (2.6) 267 (6.0) 288 (5.5) 320 (4.4) 359 (5.9) 403 (6.5) 450 (10.1) 484 (11.2) North-Kazakhstan region 419 (5.2) 76 (2.7) 298 (8.8) 325 (6.4) 368 (5.4) 417 (5.8) 469 (6.6) 517 (8.2) 549 (10.6) Pavlodar region 413 (6.0) 77 (3.1) 295 (8.6) 317 (6.9) 358 (7.4) 408 (6.6) 465 (8.0) 518 (8.4) 547 (8.9) South-Kazakhstan region 373 (3.7) 65 (2.3) 271 (7.4) 293 (5.7) 331 (4.7) 372 (4.2) 412 (4.8) 453 (4.8) 482 (7.0) West-Kazakhstan region 391 (5.1) 71 (2.8) 283 (7.2) 306 (5.5) 342 (5.6) 385 (5.7) 436 (6.6) 484 (7.8) 514 (10.0) Zhambyl region 397 (4.5) 63 (2.1) 304 (6.2) 322 (6.0) 355 (5.4) 392 (5.4) 434 (5.5) 480 (6.3) 511 (8.0) Russia Moscow region* 485 (4.1) 81 (2.3) 353 (6.9) 380 (5.9) 428 (5.8) 485 (4.6) 543 (4.4) 590 (4.2) 616 (5.8) Republic of Tatarstan* 464 (2.8) 80 (1.5) 337 (3.4) 362 (3.4) 407 (3.3) 461 (3.3) 517 (3.2) 568 (4.2) 600 (5.3) * PISA adjudicated region. 1Note: See Table I.B1.6 for national data. 2http://dx.doi.org/10.1787/888934029109 Annex B2 List of tables available on line https://doi.org/10.1787/888934029109 WEB Table I.B2.1 Percentage of students at each proficiency level in reading, by region WEB Table I.B2.2 Percentage of students at each proficiency level in mathematics, by region WEB Table I.B2.3 Percentage of students at each proficiency level in science, by region WEB Table I.B2.4 Percentage of students at each level on the cognitive process subscale of reading “locate information”, by region WEB Table I.B2.5 Percentage of students at each level on the cognitive process subscale of reading “understand”, by region WEB Table I.B2.6 Percentage of students at each level on the cognitive process subscale of reading “evaluate and reflect”, by region WEB Table I.B2.7 Percentage of students at each level on the text structure subscale of reading “single”, by region WEB Table I.B2.8 Percentage of students at each level on the text structure subscale of reading “multiple”, by region WEB Table I.B2.12 Mean score and variation in the cognitive process subscale of reading “locate information”, by region WEB Table I.B2.13 Mean score and variation in the cognitive process subscale of reading “understand”, by region WEB Table I.B2.14 Mean score and variation in the cognitive process subscale of reading “evaluate and reflect”, by region WEB Table I.B2.15 Mean score and variation in the text structure subscale of reading “single”, by region WEB Table I.B2.16 Mean score and variation in the text structure subscale of reading “multiple”, by region WEB Table I.B2.17 Mean reading performance, 2015 through 2018, by region WEB Table I.B2.18 Mean mathematics performance, 2015 through 2018, by region WEB Table I.B2.19 Mean science performance, 2015 through 2018, by region

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 261 ANNEX B3 PISA 2018 system-level indicators System-level data that are not derived from the PISA 2018 student or school questionnaire are extracted from the OECD’s annual publication Education at a Glance for those countries and economies that participate in that periodic data collection. For other countries and economies, a special system-level data collection was conducted in collaboration with PISA Governing Board members and National Project Managers. For further information see: System-level data collection for PISA 2018: Sources, comments and technical notes.pdf at www.oecd.org/pisa/. The following tables are available on line at https://doi.org/10.1787/888934029128. 1 Expenditure Table B3.1.1 Cumulative expenditure by educational institutions per student aged 6 to 15 (2015) Table B3.1.2 Teachers’ salaries (2017) Table B3.1.3 Teachers’ salaries (2017) Table B3.1.4 GDP per capita (2015, 2016, 2017, 2018) 2 Time and human resources Table B3.2.1 Teachers’ actual teaching time (2018) Table B3.2.2 Intended instruction time in compulsory general education, by age (2018) Table B3.2.3 School support staff 3 Education system characteristics Table B3.3.1 Theoretical starting age and theoretical duration (2015) Table B3.3.2 Cut-off birthdate for eligibility to school enrolment and first day of the school year (2018) Table B3.3.3 Selecting students for different programmes (2018) 4 Accountability Table B3.4.1 School inspection at the primary level (2018) Table B3.4.2 School inspection at the lower secondary level (2018) Table B3.4.3 School inspection at the upper secondary level (2018) Table B3.4.4 School board 5 Policies and curriculum Table B3.5.1 Bullying policies Table B3.5.2 Civic education 6 School choice Table B3.6.1 Freedom for parents to choose a public school for their child(ren) (2018) Table B3.6.2 Financial incentives and disincentives for school choice (2018) Table B3.6.3 Government regulations that apply to schools at the primary and lower secondary levels (2018) Table B3.6.4 Criteria used by public and private schools when assigning and selecting students (2018) Table B3.6.5 Expansion of school choice within the public school sector over the past 10 years (2018) Table B3.6.6 Government-dependent private schools and their role in providing compulsory education at the primary and lower secondary level (2018) Table B3.6.7 Independent private schools and their role in providing compulsory education at the primary and lower secondary level (2018) Table B3.6.8 Homeschooling as a legal means of providing compulsory education at the primary and lower secondary level (2018) Table B3.6.9 Use of public resources for transporting students (2018) Table B3.6.10 Responsibility for informing parents about school choices available to them (2018) Table B3.6.11 Availability of school vouchers (or scholarships) (2018) Table B3.6.12 Extent to which public funding follows students when they leave for another public or private school (2018)

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 263 Released items from the PISA 2018 computer‑based reading assessment ANNEX C

264 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do ANNEX C Released items from the PISA 2018 computer-based reading assessment Items from Rapa Nui, the released unit from the PISA 2018 reading assessment, and items used in the assessment of reading fluency One new unit, Rapa Nui, was released from the main survey of the PISA 2018 computer-based reading assessment; the seven items from this unit are presented in this annex. Two other units, Chicken Forum and Cow’s Milk, were tested in the field trial but not used in the PISA 2018 main survey. These units, along with the untested unit The Galapagos Islands, are available on line at www.oecd.org/pisa. All four of these units were developed in accordance with the new PISA 2018 reading literacy framework. The annex concludes with sentences that illustrate those used in the reading-fluency assessment. Screenshots of the interface used in PISA 2018 are shown to give readers an understanding of how students interacted with the assessment and its items. Interactive versions of all of these units are also available at www.oecd.org/pisa. UNIT CR551: RAPA NUI Rapa Nui scenario In this unit’s scenario, the student is preparing to attend a lecture about a professor’s field work, which was conducted on the island of Rapa Nui. The situation is classified as educational because it represents a student conducting background research on Rapa Nui in preparation to attend a lecture. Rapa Nui is a multiple-source unit. It consists of three texts: a webpage from the professor’s blog, a book review, and a news article from an online science magazine. The blog is classified as a multiple-source text; dynamic (the webpage contains active links to the other texts in the unit); continuous; and narrative. The blog post is an example of a multiple-source text because the comment section at the bottom of the blog page represents different authors. Both the book review and the news article are classified as single text; static; continuous; and argumentative. Initially, the student is provided with the blog post only. Several questions are presented that focus only on the content of this blog. Once those questions have been answered, the student receives the second text – the book review. After reading the book review, the student responds to a question that focuses solely on its content. The student then receives the third text – the article from the online science magazine. The student sees questions that focus only on the article. After that, the student is given items that require integrating the information from all sources. This model was used for several of the multiple-text units in the new material developed for reading literacy. This approach was chosen because it allows the student first to demonstrate proficiency on questions that are related to one text and then to demonstrate the ability to handle information from multiple texts. This is an important design feature because there may be

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 265 Released items from the PISA 2018 computer-based reading assessment Annex C readers who can succeed with information when it is presented in a single text and even integrate information within one text, but who struggle when asked to integrate across multiple texts. Thus, this design allows students with varying levels of ability to demonstrate proficiency on at least some elements of the unit. The “Rapa Nui” unit was intended to be of moderate to high difficulty. The three texts result in a larger amount of information to work through within the unit compared to a single-text unit. In addition, the student needs to consider the way the texts are related to one another, requiring him or her to recognise whether the texts corroborate each other or whether they differ in their stances. This kind of cognitive engagement with the material and the unit overall is expected to require more effort than a unit that presents all the information within one text. Please note that the screenshot provided for released item #1 shows the full text of the blog for the purposes of this report. The student had to scroll to see the full text in the programmed version, which was programmed uniformly across language versions so that all students would have to scroll to see the full text. Rapa Nui released item #1 In this item, the student must locate the correct information within the blog post. The difficulty of the item likely stems from the existence of other time-related information within the blog, i.e. the date it was posted and the time period in which the first mystery of the moai was solved (the 1990s). Here, the correct answer is (B) Nine months ago. Item number CR551Q01 Cognitive process Accessing and retrieving information within a piece of text Response format Simple multiple choice – Computer scored Difficulty 559 – Level 4 Source type Single source

266 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex C Released items from the PISA 2018 computer-based reading assessment Rapa Nui released item #2 In this item, the student must understand that the second mystery mentioned in the blog post: what happened to the large trees that once grew on Rapa Nui and were used to move the moai? This is an open response/human coded item, and the coding guide used in the main survey is provided below. For this item, the student could provide a direct quotation from the blog (“What happened to these plants and large trees that had been used to move the moai?”) or an accurate paraphrase. This item was coded with high reliability in the main survey. Item number CR551Q05 Cognitive process Representing literal meaning Response format Open response – Human coded Difficulty 513 – Level 3 Source type Single source For full credit, responses must refer to the disappearance of the materials used to move the statues (moai). • What happened to these plants and large trees that had been used to move the moai? [Direct quotation] • There are no large trees left that could have moved the moai. • There are grasses, shrubs and some small trees, but no trees large enough to move the large statues. • Where are the large trees? [Minimal] • Where are the plants? [Minimal] • What happened to the resources that were needed to transport the statues? • She was referring to what moved the Moai because when she looked around there were no big trees or plants. She is also wondering what happened to them. [Although this response begins by referring to the wrong mystery, it contains the correct elements.] Rapa Nui released item #3 For this item, the student is presented with the second text in the unit, a book review of Collapse, which was referenced in the blog post. The student must complete a table by selecting “Fact” or “Opinion” for each row. The question asks the student to identify whether each statement from the book review is a fact or an opinion. The student must first understand the literal meaning of each statement and then decide if the content was factual or represented the perspective of the author of the review. In this way, the student must focus on the content and how it is presented rather than just the meaning. To receive full credit for this item, the student was required to get all 5 rows correct. For partial credit, students were required to get 4 out of the 5 rows correct. If students got fewer than 4 rows correct, they received no credit. The correct answers are: Fact, Opinion, Fact, Fact, Opinion.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 267 Released items from the PISA 2018 computer-based reading assessment Annex C Item number CR551Q06 Cognitive process Reflecting on content and form Response format Complex multiple choice – Computer scored Difficulty For full credit, 654 – Level 5; for partial credit, 528 – Level 3 Source type Single source For this item, the student is presented with the third text in the unit – an article from an online science magazine. Note that at this point in the unit all three texts are available to the student using a tab structure; the student can click on any tab to toggle back and forth between the texts. The item itself remains fixed on the left side of the screen during any toggling action. In this item, the student is required to locate the section of the article that contains the reference to the scientists and Jared Diamond (paragraph 2) and identify the sentence that contains the information agreed upon. While texts are available to the student, this item is not classified with a cognitive process that reflects the use of multiple sources. This is because the student can find the answer within this text, and the item instructions on the upper left corner instruct the student to refer to this article only. Rapa Nui released item #4

268 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex C Released items from the PISA 2018 computer-based reading assessment Thus, the support from the item instructions eliminates the need to consider the other sources. The difficulty of this item is likely driven by the existence of plausible (but incorrect) distracting information within the paragraph with respect to human settlement. Here, the correct answer is (B) Large trees have disappeared from Rapa Nui. Item number CR551Q08 Cognitive process Accessing and retrieving information within a piece of text Response format Simple multiple choice – Computer scored Difficulty 634 – Level 5 Source type Single source In this item, the student is required to understand what information in the text supports, or corroborates, the theory put forward by the scientists. The correct answer is (D) The remains of palm nuts show gnaw marks made by rats. Here, the student must go beyond an understanding of the text and identify which element of the text can be used as evidence to support a claim. All other items classified as detect and handle conflict require detecting a conflict between two sources or recognising that the information is in two or more sources and is corroborated. However, in discussing this item prior to the field trial, the experts felt that the act of identifying which piece of information supports the theory proposed by Carl Lipo and Terry Hunt was most appropriately identified by the cognitive process of detect and handle conflict. Furthermore, while this item could have been classified as requiring only a single source in order to be solved, the requirement for the student to first consider the theory proposed by Lipo and Hunt and then to determine which piece of evidence supports this theory is akin to working with multiple sources. Item number CR551Q09 Cognitive process Detecting and handling conflict Response format Simple multiple choice – Computer scored Difficulty 597 – Level 4 Source type Multiple source Rapa Nui released item #6 In this item, students must integrate information across the texts with respect to the differing theories put forward by Jared Diamond on the one hand and Carl Lipo and Terry Hunt on the other. The student must identify the shared effect (the disappearance of the large trees) by rejecting information presented in the blog post about where the moai were carved (in the same quarry). Further, the student must understand what each scientist believes is the cause of the disappearance. To receive credit for this item, the student was required to get all three answers correct. The correct answers are: Cause (Jared Diamond) – Humans cut down trees to clear land for agriculture and other reasons. Cause (Carl Lipo and Terry hunt) – Polynesian rats ate tree seeds and as a result no new trees could grow. Effect (shared) – The large trees disappeared from Rapa Nui. Rapa Nui released item #5

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 269 Released items from the PISA 2018 computer-based reading assessment Annex C Item number CR551Q10 Cognitive process Integrating and generating inferences across multiple sources Response format Complex multiple choice – Computer scored Difficulty 665 – Level 5 Source type Multiple source In this item, the student must integrate information from across the texts and decide which theory to support. In this way, the student must understand the theories – and that they are at odds with one another – and must present a response that contains support from the texts. To receive credit, a student could choose to support either theory or could choose neither theory as long as the explanation is focused on the need for additional research. This is an open response/human coded item, and the coding guide used in the main survey is provided below. This item was coded with high reliability in the main survey. Rapa Nui released item #7

270 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex C Released items from the PISA 2018 computer-based reading assessment Item number CR551Q11 Cognitive process Detecting and handling conflict Response format Open response – Human coded Difficulty 588 – Level 4 Source type Multiple source For full credit, at least one of the following descriptions had to be included: 1. The people cut down or used the trees (to move the moai and/or cleared the land for agriculture). 2. The rats ate the seeds of the trees (so new trees could not grow). 3. It is not possible to say exactly what happened to the large trees until further research is conducted. Sample responses that would receive full credit include: • I think the trees disappeared because people cut too many of them down to move the moai. [1] • People cleared the land for agriculture. [1] • Trees were used to move moai. [1] • People cut the trees down. [1] • It was the people’s fault because they wanted to move the moai. [1 – this response doesn’t explicitly refer to cutting down the trees, but it is acceptable because they refer to people and one reason they cut down the trees (to move the moai)] • People’s fault. They destroyed the environment. [1 – this response doesn’t explicitly refer to cutting down the trees, but it is an acceptable way of summarizing the results of cutting down the trees.] • I think the rats probably caused the most damage by eating the seeds of the trees. [2] • The rats ate the seeds. [2] • There is no proof that either one is correct, so we have to wait until there is more information. [3] • Both. The people cut down the big trees for farming, and then the rats ate the tree seeds! [1 and 2] READING FLUENCY In PISA 2018, the Reading Expert Group recommended including a measure of reading fluency to better assess and understand the reading skills of students in the lower proficiency levels. PISA defines reading fluency as the ease and efficiency with which one can read and understand a piece of text. Reading fluently requires that one can recognize words within a text accurately and automatically and can then parse and process the words into a coherent whole in order to comprehend the overall meaning of the text. When these processes are done efficiently, students’ cognitive resources are available for higher-level comprehension tasks, allowing students to engage with texts more deeply. In the PISA 2018 assessment of reading fluency, students were given three minutes to evaluate the sensibility of as many sentences as they could (i.e. Does the sentence make sense – Yes or No). The number of sentences was restricted to 21 or 22 sentences per student so that most students would be able to complete the task within the three minutes. Students were not cut off in the middle of an item or notified that they did not complete all the sentences. Instead, if a student reached the three minutes while viewing a sentence, the task ended after they completed that sentence’s sensibility judgment. This was done so that students would maintain motivation for the remaining sections of the PISA assessment. Items in this task were the easiest items in the reading-literacy assessment in PISA 2018. Difficulty information is not provided in this report for the practice items because data for these items was not analysed. However, in the assessment of reading fluency, the items fell into proficiency Level 1c and Level 1b. One item was in Level 1a. Items that did not make sense and required a “No” response were more difficult than items that made sense and required a “Yes” response. The introduction to and practice items for the reading-fluency task are provided below along with an explanation for how students were oriented to the task.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 271 Released items from the PISA 2018 computer-based reading assessment Annex C Reading fluency: Introduction In this introduction, students are given the basic instructions for what they will do in the fluency task. Students are notified that the next sentence will appear as soon as they respond so that they are prepared for this style of presentation. Reading fluency: Static examples Students are given a set of static examples so that the sensibility judgements are understood prior to interacting with dynamic practice items. Here, three example sentences are provided, two that make sense (a Yes response is correct) and one that does not make sense (a No response is correct).

272 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex C Released items from the PISA 2018 computer-based reading assessment Reading fluency: Dynamic practice The next three images show three dynamic-practice items. Students complete these dynamic-practice items prior to receiving the first fluency item so that they understand the response mode for the item. For each example, as soon as the student clicks on “Yes” or “No”, the next item appears. Reading fluency: Dynamic-practice item #1 Here, the correct answer is “Yes”. Reading fluency: Dynamic-practice item #2 Here, the correct answer is “No”.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 273 Released items from the PISA 2018 computer-based reading assessment Annex C Reading fluency: Dynamic-practice item #3 Here, the correct answer is “Yes”. Reading fluency: End of practice Students are told that they have completed the practice sentences. They are also given the time limit for the task – three minutes – and they are told to complete as many sentences as they can within the time limit. Once the student clicks on the NEXT arrow, the task begins and is carried out in the same way as the dynamic-practice items. Once students have completed the task, they are notified that the first section of the test is complete and the answers have been saved.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 275 Snapshot of trends in reading, mathematics and science performance ANNEX D

276 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do In Albania, mean performance improved, from initially low levels, across all three subjects (reading, mathematics and science). In all three subjects, improvements at the bottom of the performance distribution outpaced improvements observed at the top, resulting in narrowing performance gaps between the highest- and lowest-achieving students. Improvements in mean performance were particularly rapid in mathematics (about 20 points, on average, per 3-year period). The proportion of students who scored below Level 2 in mathematics (low-achieving students) shrank by 18 percentage points between 2012 and 2018. Improvements in performance in Albania were even more remarkable when considering that enrolment rates of 15-year-olds in grade 7 and above increased between 2009 and 2018 (Table I.A2.2). Snapshot of performance trends in ALBANIA Mean performance Reading Mathematics Science PISA 2000 349* PISA 2003 m m PISA 2006 m m m PISA 2009 385* 377* 391* PISA 2012 394* 394* 397* PISA 2015 405 413* 427* PISA 2018 405 437 417 Average 3-year trend in mean performance +10.5* +19.8* +10.7* Short-term change in mean performance (2015 to 2018) +0.2 +24.1* -10.5* Overall performance trajectory positive, but flattening (less positive over more recent years) improving improving Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2009 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +0.2 +1.5* +0.1 Percentage-point change in low-achieving students (below Level 2) -4.4 -18.3* -10.3* Variation in performance Reading (2000 to 2018) Mathematics (2009 to 2018) Science (2009 to 2018) Average trend amongst the highest-achieving students (90th percentile) +7.9* +16.7* +4.1 Average trend amongst the lowest-achieving students (10th percentile) +14.4* +24.0* +19.7* Gap in learning outcomes between the highest- and lowest-achieving students narrowing gap narrowing gap narrowing gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. ANNEX D Snapshot of trends in reading, mathematics and science performance

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 277 Snapshot of trends in reading, mathematics and science performance Annex D Mean mathematics and science performance remained stable in Argentina over the 2006-2018 period. In reading, performance improved over this period after an initial decline between 2001 and 2006. The gap between the highest- and lowest-achieving students narrowed in all three subjects. This means that in reading, mathematics and science, trends were significantly more positive at the bottom of the performance distribution (with the 10th percentile moving up by more than 5 points per 3-year period in mathematics and science) than at the top of the performance distribution (with the 90th percentile moving down by more than 4 points per 3-year period in reading and mathematics). PISA 2015 results for Argentina cannot be compared to results from previous years or to results from 2018 due to the use of an incomplete sampling frame. Indeed, PISA 2015 results represented only 55% of the country’s population of 15-year-olds, compared to about 80% in PISA 2006, 2012 and 2018. Snapshot of performance trends in ARGENTINA Mean performance Reading Mathematics Science PISA 2000 418 PISA 2003 m m PISA 2006 374* 381 391 PISA 2009 398 388 401 PISA 2012 396 388 406 PISA 2015 m m m PISA 2018 402 379 404 Average 3-year trend in mean performance -1.2 -1.0 +3.0 Short-term change in mean performance (2015 to 2018) m m m Overall performance trajectory U-shaped (more positive over more recent years) stable stable Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -0.3 +0.1 +0.0 Percentage-point change in low-achieving students (below Level 2) +0.5 +2.5 -2.8 Variation in performance Reading (2000 to 2018) Mathematics (2009 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) -4.3* -5.6* -0.0 Average trend amongst the lowest-achieving students (10th percentile) +4.4 +5.3* +8.3* Gap in learning outcomes between the highest- and lowest-achieving students narrowing gap narrowing gap narrowing gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

278 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Mean performance in Australia has been steadily declining in reading (between 2000 and 2018) and in mathematics (between 2003 and 2018), from initially high levels of performance; it has been declining in science too, at least since 2012. In reading, more rapid declines were observed amongst the country’s lowest-achieving students. In mathematics and science, performance declined to a similar extent at the top and at the bottom of the performance distribution, as well as on average. The proportion of top-performing students (scoring at Level 5 or 6) remained stable in reading (between 2009 and 2018), but decreased in mathematics (between 2012 and 2018) and in science (between 2006 and 2018). Meanwhile, the proportion of low‑achieving students (scoring below Level 2) increased in all subjects. Snapshot of performance trends in AUSTRALIA Mean performance Reading Mathematics Science PISA 2000 528* PISA 2003 525* 524* PISA 2006 513 520* 527* PISA 2009 515* 514* 527* PISA 2012 512* 504* 521* PISA 2015 503 494 510* PISA 2018 503 491 503 Average 3-year trend in mean performance -4.4* -7.2* -6.5* Short-term change in mean performance (2015 to 2018) -0.3 -2.5 -7.0* Overall performance trajectory steadily negative steadily negative increasingly negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +0.3 -4.3* -5.1* Percentage-point change in low-achieving students (below Level 2) +5.4* +2.8 +6.0* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) -2.4 -6.9* -6.0* Average trend amongst the lowest-achieving students (10th percentile) -6.2* -7.1* -7.6* Gap in learning outcomes between the highest- and lowest-achieving students widening gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 279 Snapshot of trends in reading, mathematics and science performance Annex D Snapshot of performance trends in AUSTRIA Mean performance Reading Mathematics Science PISA 2000 492 PISA 2003 491 506 PISA 2006 490 505 511* PISA 2009 m m m PISA 2012 490 506 506* PISA 2015 485 497 495 PISA 2018 484 499 490 Average 3-year trend in mean performance -1.3 -1.7 -5.5* Short-term change in mean performance (2015 to 2018) -0.5 +2.2 -5.3 Overall performance trajectory flat flat declining Proficiency levels Reading (2012 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +1.9* -1.7 -3.7* Percentage-point change in low-achieving students (below Level 2) +4.1* +2.4 +5.5* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) -1.3 -2.3 -5.1* Average trend amongst the lowest-achieving students (10th percentile) -0.9 -1.7 -4.7* Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. Austria’s mean performance in reading and mathematics remained stable, around a flat trend line, throughout the country’s participation in PISA. In science, performance has been declining since 2006; similar declines were observed amongst the country’s highest-achieving and lowest-achieving students. In PISA 2018, the proportion of top-performing students in science (students scoring at Level 5 or 6) was almost 4 percentage points smaller than in 2006.

280 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance In all three subjects, Belgium’s mean performance in PISA 2018 was not significantly different from that observed in 2015. When considering a longer period, the overall trajectory is negative in mathematics and science, and declining, at least since 2012, in reading too. The decline in mean performance in mathematics, most of which occurred in the earlier period, was mostly the result of declines amongst the highest-achieving students. The 90th percentile of the mathematics performance distribution, i.e. the level above which only 10% of students scored, moved down by about 7 points per 3-year period between 2003 and 2018. Snapshot of performance trends in BELGIUM Mean performance Reading Mathematics Science PISA 2000 507* PISA 2003 507 529* PISA 2006 501 520* 510* PISA 2009 506* 515 507 PISA 2012 509* 515 505 PISA 2015 499 507 502 PISA 2018 493 508 499 Average 3-year trend in mean performance -1.8 -4.1* -2.7* Short-term change in mean performance (2015 to 2018) -5.7 +1.1 -3.2 Overall performance trajectory hump-shaped (more negative over more recent years) negative, but flattening (less negative over more recent years) steadily negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -1.6 -3.8* -2.0* Percentage-point change in low-achieving students (below Level 2) +3.5* +0.7 +3.0 Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) -1.8 -6.8* -2.5* Average trend amongst the lowest-achieving students (10th percentile) +1.1 -1.1 -2.2 Gap in learning outcomes between the highest- and lowest-achieving students stable gap narrowing gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 281 Snapshot of trends in reading, mathematics and science performance Annex D In Brazil, mean performance in mathematics improved over the 2003-2018 period, but most of that improvement was in the early cycles. After 2009, in mathematics, as in reading and science, mean performance appeared to fluctuate around a flat trend. The positive early trends (2000-2012) were observed over a period of rapid expansion of secondary education. Between 2003 and 2012, Brazil added more than 500 000 students to the total population of 15-year-olds eligible to participate in PISA. The proportion of 15-year-olds who were covered by PISA samples increased from about 55% in 2003 to 70% in 2012. It is likely that this expansion in education opportunities dampened an even more positive underlying trend in student performance. Indeed, a simulation that assumes that the highest-scoring 25% of 15-year-olds were eligible to take the test in any given year shows a positive trend amongst this population not only in mathematics (2003-2018), but also in science (2006-2018) (Figure I.9.5). Snapshot of performance trends in BRAZIL Mean performance Reading Mathematics Science PISA 2000 396* PISA 2003 403 356* PISA 2006 393* 370* 390* PISA 2009 412 386 405 PISA 2012 407 389 402 PISA 2015 407 377 401 PISA 2018 413 384 404 Average 3-year trend in mean performance +2.6 +4.6* +2.2 Short-term change in mean performance (2015 to 2018) +5.5 +6.5 +2.9 Overall performance trajectory flat positive, but flattening (less positive over more recent years) hump-shaped (more negative over more recent years) Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +0.5 +0.2 +0.2 Percentage-point change in low-achieving students (below Level 2) +0.4 -0.2 -5.6* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +4.0* +2.6 +4.0* Average trend amongst the lowest-achieving students (10th percentile) +2.6 +7.4* +1.2 Gap in learning outcomes between the highest- and lowest-achieving students widening gap narrowing gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

282 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance In Bulgaria, mean performance in reading remained stable, around a flat trend line, throughout the country’s participation in PISA (2001-2018). In mathematics, performance improved between 2006 and 2018, but the improvement was concentrated in the early years (2006-2012). In science, performance in 2018 fell below the level observed in 2012 and 2015. The drop in mean science performance between PISA 2015 and PISA 2018 is one of the largest observed over this (short) period amongst all PISA‑participating countries and economies. Snapshot of performance trends in BULGARIA Mean performance Reading Mathematics Science PISA 2000 430 PISA 2003 m m PISA 2006 402 413* 434 PISA 2009 429 428 439 PISA 2012 436* 439 446* PISA 2015 432 441 446* PISA 2018 420 436 424 Average 3-year trend in mean performance +0.8 +5.9* -1.4 Short-term change in mean performance (2015 to 2018) -11.9 -5.1 -21.7* Overall performance trajectory flat positive, but flattening (less positive over more recent years) hump-shaped (more negative over more recent years) Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -0.4 +0.2 -1.5* Percentage-point change in low-achieving students (below Level 2) +6.1 +0.7 +3.9 Variation in performance Reading (2000 to 2018) Mathematics (2006 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +1.8 +5.4* -4.6* Average trend amongst the lowest-achieving students (10th percentile) +0.9 +6.2* +2.0 Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap narrowing gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 283 Snapshot of trends in reading, mathematics and science performance Annex D In Canada, performance declined in mathematics (since 2003) and in science (since 2006) by about 10 score points or more per decade (4.1 score points per 3-year period in mathematics, and 3.4 score points per 3-year period in science). In reading, no significant overall direction of the trend could be determined, and performance remained at least 20 points above the OECD average performance in every PISA year. However, the share of low-achieving students increased between 2009 and 2018 by 3.5 percentage points and, as is observed in mathematics too, more rapid declines were observed amongst the lowest‑achieving students than amongst the highest-achieving students, resulting in a widening of performance gaps. Snapshot of performance trends in CANADA Mean performance Reading Mathematics Science PISA 2000 534* PISA 2003 528 532* PISA 2006 527 527* 534* PISA 2009 524 527* 529* PISA 2012 523 518 525 PISA 2015 527 516 528* PISA 2018 520 512 518 Average 3-year trend in mean performance -1.7 -4.1* -3.4* Short-term change in mean performance (2015 to 2018) -6.6 -3.6 -9.7* Overall performance trajectory flat steadily negative steadily negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +2.2 -1.1 -3.1* Percentage-point change in low-achieving students (below Level 2) +3.5* +2.4 +3.4* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) -0.3 -2.9* -2.0 Average trend amongst the lowest-achieving students (10th percentile) -2.8* -5.5* -4.3* Gap in learning outcomes between the highest- and lowest-achieving students widening gap widening gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

284 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Reading performance in Chile improved since the country’s first participation in PISA (in 2001). However, most of that improvement occurred in the early period. Between 2009 and 2018, no significant trends in performance were observed in any subject. Despite stable overall performance, the proportion of students performing at Level 5 or above (top performers) in reading grew between 2009 and 2018 (+1.3 percentage points) and shrank in science between 2006 and 2018 (-0.9 of a percentage point). Snapshot of performance trends in CHILE Mean performance Reading Mathematics Science PISA 2000 410* PISA 2003 m m PISA 2006 442 411 438 PISA 2009 449 421 447 PISA 2012 441* 423 445 PISA 2015 459 423 447 PISA 2018 452 417 444 Average 3-year trend in mean performance +7.1* +1.4 +1.1 Short-term change in mean performance (2015 to 2018) -6.3 -5.3 -3.4 Overall performance trajectory positive, but flattening (less positive over more recent years) hump-shaped (more negative over more recent years) flat Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +1.3* -0.4 -0.9* Percentage-point change in low-achieving students (below Level 2) +1.2 +0.4 -4.4 Variation in performance Reading (2000 to 2018) Mathematics (2006 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +6.2* +0.9 -0.7 Average trend amongst the lowest-achieving students (10th percentile) +8.1* +0.9 +1.9 Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap narrowing gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 285 Snapshot of trends in reading, mathematics and science performance Annex D While Colombia’s performance in reading in PISA 2018 was below that observed in 2015, when considering a longer period, mean performance improved in all subjects – including reading – since the country first participated in PISA in 2006. Snapshot of performance trends in COLOMBIA Mean performance Reading Mathematics Science PISA 2000 m PISA 2003 m m PISA 2006 385* 370* 388* PISA 2009 413 381 402 PISA 2012 403 376* 399* PISA 2015 425* 390 416 PISA 2018 412 391 413 Average 3-year trend in mean performance +6.6* +5.1* +6.4* Short-term change in mean performance (2015 to 2018) -12.6* +1.3 -2.4 Overall performance trajectory positive, but flattening (less positive over more recent years) steadily positive steadily positive Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +0.4 +0.2 +0.3* Percentage-point change in low-achieving students (below Level 2) +2.8 -8.4* -9.8* Variation in performance Reading (2006 to 2018) Mathematics (2006 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +4.5* +4.9* +7.3* Average trend amongst the lowest-achieving students (10th percentile) +12.0* +7.2* +8.0* Gap in learning outcomes between the highest- and lowest-achieving students narrowing gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

286 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Costa Rica first participated in PISA in 2010. While mean performance in mathematics remained stable over the 2010-2018 period, it declined in both reading and science. More specifically, while performance in reading and science was similar between 2009 and 2012, it declined in 2015 and stayed at roughly the same level in 2018. The decline in performance was most acute amongst the lowest-achieving students. The average trend amongst these students was negative and significant in all three subjects (reading, mathematics and science). However, these decreases in performance took place in the context of an increase in the coverage of the 15-year-old population in Costa Rica, from between 50% and 53% in 2010 and 2012, respectively, to 63% in 2015 and 2018. The inclusion of more 15‑year‑olds in the assessed population often involves the inclusion of weaker students who would not have been enrolled or who would not have been at the appropriate grade level in earlier rounds of PISA. Once changes in coverage were accounted for, the average trend amongst the median and higher percentiles of 15-year-olds were not significant, although positive. It is therefore possible that the decline in mean performance in Costa Rica was due primarily to increased coverage of the 15-year-old population. Snapshot of performance trends in COSTA RICA Mean performance Reading Mathematics Science PISA 2000 m PISA 2003 m m PISA 2006 m m m PISA 2009 443* 409 430* PISA 2012 441* 407 429* PISA 2015 427 400 420 PISA 2018 426 402 416 Average 3-year trend in mean performance -6.8* -3.0 -6.1* Short-term change in mean performance (2015 to 2018) -1.0 +2.1 -4.0 Overall performance trajectory declining stable declining Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2009 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -0.2 -0.2 -0.2 Percentage-point change in low-achieving students (below Level 2) +9.3* +0.1 +8.8* Variation in performance Reading (2009 to 2018) Mathematics (2009 to 2018) Science (2009 to 2018) Average trend amongst the highest-achieving students (90th percentile) -3.7 -1.5 -5.5 Average trend amongst the lowest-achieving students (10th percentile) -7.6* -5.0* -5.2* Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 287 Snapshot of trends in reading, mathematics and science performance Annex D In reading and mathematics, mean performance in Croatia remained stable, around a flat trend line, throughout the country’s participation in PISA (2006-2018). In science, mean performance declined over this same period by about 5 score points on average per 3-year period. Performance declines in science were particularly pronounced amongst the country’s lowest-achieving students. The proportion of students scoring below Level 2 in science increased by about 8 percentage points over that observed in PISA 2006. Snapshot of performance trends in CROATIA Mean performance Reading Mathematics Science PISA 2000 m PISA 2003 m m PISA 2006 477 467 493* PISA 2009 476 460 486* PISA 2012 485 471 491* PISA 2015 487 464 475 PISA 2018 479 464 472 Average 3-year trend in mean performance +1.4 -0.2 -5.3* Short-term change in mean performance (2015 to 2018) -7.9 +0.2 -3.0 Overall performance trajectory flat flat steadily negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +1.5* -1.8 -1.5* Percentage-point change in low-achieving students (below Level 2) -0.9 +1.3 +8.4* Variation in performance Reading (2006 to 2018) Mathematics (2006 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +2.9 +0.6 -2.9 Average trend amongst the lowest-achieving students (10th percentile) +1.4 -0.9 -7.4* Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap widening gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

288 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Cyprus participated in PISA for the third time in 2018. Mean reading performance declined over time, while mathematics performance improved between 2012 and 2018 and science performance returned close to the level observed in 2012. Snapshot of performance trends in CYPRUS Mean performance Reading Mathematics Science PISA 2000 m PISA 2003 m m PISA 2006 m m m PISA 2009 m m m PISA 2012 449* 440* 438 PISA 2015 443* 437* 433* PISA 2018 424 451 439 Average 3-year trend in mean performance -12.2* +5.7* +0.7 Short-term change in mean performance (2015 to 2018) -18.5* +13.6* +6.4* Overall performance trajectory declining improving stable Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2009 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -2.2* +0.7 -0.3 Percentage-point change in low-achieving students (below Level 2) +10.9* -5.2* +0.9 Variation in performance Reading (2009 to 2018) Mathematics (2009 to 2018) Science (2009 to 2018) Average trend amongst the highest-achieving students (90th percentile) -14.7* +5.6* +0.7 Average trend amongst the lowest-achieving students (10th percentile) -0.7 +2.6 +3.1 Gap in learning outcomes between the highest- and lowest-achieving students narrowing gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 289 Snapshot of trends in reading, mathematics and science performance Annex D In the Czech Republic, mean performance in reading in 2018 was close to the level observed in all other PISA assessments since 2000, except PISA 2009. In mathematics, performance was below that observed in 2003, but above PISA 2015 performance. In science, performance was below that observed in 2006, but not significantly different from that observed in more recent years. Snapshot of performance trends in the CZECH REPUBLIC Mean performance Reading Mathematics Science PISA 2000 492 PISA 2003 489 516* PISA 2006 483 510 513* PISA 2009 478* 493 500 PISA 2012 493 499 508* PISA 2015 487 492 493 PISA 2018 490 499 497 Average 3-year trend in mean performance +0.1 -3.7* -4.0* Short-term change in mean performance (2015 to 2018) +3.0 +7.1 +4.0 Overall performance trajectory U-shaped (more positive over more recent years) negative, but flattening (less negative over more recent years) steadily negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +3.1* -0.2 -4.1* Percentage-point change in low-achieving students (below Level 2) -2.3 -0.6 +3.2 Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +0.7 -5.9* -4.9* Average trend amongst the lowest-achieving students (10th percentile) +0.2 -2.0 -3.2 Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30.

290 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Snapshot of performance trends in DENMARK Mean performance Reading Mathematics Science PISA 2000 497 PISA 2003 492 514 PISA 2006 494 513 496 PISA 2009 495 503 499 PISA 2012 496 500* 498 PISA 2015 500 511 502* PISA 2018 501 509 493 Average 3-year trend in mean performance +1.1 -0.9 -0.4 Short-term change in mean performance (2015 to 2018) +1.3 -1.7 -9.3* Overall performance trajectory flat U-shaped (more positive over more recent years) hump-shaped (more negative over more recent years) Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +3.7* +1.7 -1.3 Percentage-point change in low-achieving students (below Level 2) +0.8 -2.3 +0.2 Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +0.7 -3.4* -1.2 Average trend amongst the lowest-achieving students (10th percentile) +2.2 +1.0 +0.2 Gap in learning outcomes between the highest- and lowest-achieving students stable gap narrowing gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. Mean performance in reading remained stable, around a flat trend line, throughout Denmark’s participation in PISA. In mathematics and science too, no overall direction of the trend could be detected; however, in mathematics, a declining trend up to 2012 was followed by a (partial) recovery over the 2012-2018 period, while in science, performance in 2018 was about 9 score points lower, on average, than in 2015. The overall trend in mathematics performance was negative amongst the highestachieving students (at the 90th percentile).

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 291 Snapshot of trends in reading, mathematics and science performance Annex D Snapshot of performance trends in the DOMINICAN REPUBLIC Mean performance Reading Mathematics Science PISA 2000 m PISA 2003 m m PISA 2006 m m m PISA 2009 m m m PISA 2012 m m m PISA 2015 358* 328 332 PISA 2018 342 325 336 Average 3-year trend in mean performance -16.1* -2.6 +4.0 Short-term change in mean performance (2015 to 2018) -16.1* -2.6 +4.0 Overall performance trajectory declining stable stable Proficiency levels Reading (2015 to 2018) Mathematics (2015 to 2018) Science (2015 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +0.0 +0.0 -0.0 Percentage-point change in low-achieving students (below Level 2) +6.9* +0.0 -0.9 Variation in performance Reading (2015 to 2018) Mathematics (2015 to 2018) Science (2015 to 2018) Average trend amongst the highest-achieving students (90th percentile) -17.5* -0.4 +2.0 Average trend amongst the lowest-achieving students (10th percentile) -9.4 -6.4 +6.2 Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. The Dominican Republic participated in PISA for the second time since 2015. While mathematics and science performance was similar to that observed in 2015, reading performance lay 16 score points below that observed in 2015.

292 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Snapshot of performance trends in ESTONIA Mean performance Reading Mathematics Science PISA 2000 m PISA 2003 m m PISA 2006 501* 515 531 PISA 2009 501* 512* 528 PISA 2012 516 521 541* PISA 2015 519 520 534 PISA 2018 523 523 530 Average 3-year trend in mean performance +6.3* +2.5* +0.4 Short-term change in mean performance (2015 to 2018) +3.9 +3.9 -4.1 Overall performance trajectory steadily positive steadily positive hump-shaped (more negative over more recent years) Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +7.8* +0.9 +0.7 Percentage-point change in low-achieving students (below Level 2) -2.3 -0.3 +1.1 Variation in performance Reading (2006 to 2018) Mathematics (2006 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +10.0* +2.6* +2.1 Average trend amongst the lowest-achieving students (10th percentile) +3.7* +2.2 -1.3 Gap in learning outcomes between the highest- and lowest-achieving students widening gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. Mean reading and mathematics performance in Estonia improved steadily since the country first participated in PISA in 2006. Over this same period (2006-2018), performance in science remained mostly stable (and high). The improvement in reading performance was particularly marked at the top of the performance distribution: the 90th percentile moved up on the PISA scale by about 10 points every 3 years and, between 2009 and 2018, the proportion of student scoring at Level 5 or 6 (top performers) increased by almost 8 percentage points.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 293 Snapshot of trends in reading, mathematics and science performance Annex D Snapshot of performance trends in FINLAND Mean performance Reading Mathematics Science PISA 2000 546* PISA 2003 543* 544* PISA 2006 547* 548* 563* PISA 2009 536* 541* 554* PISA 2012 524 519* 545* PISA 2015 526 511 531* PISA 2018 520 507 522 Average 3-year trend in mean performance -4.9* -9.1* -10.7* Short-term change in mean performance (2015 to 2018) -6.3 -3.8 -8.8* Overall performance trajectory steadily negative increasingly negative steadily negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -0.3 -4.1* -8.6* Percentage-point change in low-achieving students (below Level 2) +5.4* +2.7* +8.8* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) -1.5 -9.3* -7.2* Average trend amongst the lowest-achieving students (10th percentile) -8.6* -9.7* -15.5* Gap in learning outcomes between the highest- and lowest-achieving students widening gap stable gap widening gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. Mean reading, mathematics and science performance continued to decline in Finland. In all three subjects the decline began after 2006. Although PISA 2018 results were significantly lower than PISA 2015 results only in science, there was no sign of a flattening or reversing trend in any subject. In mathematics, declines were similarly rapid at all levels of the performance distribution; in reading and science, in contrast, the declining trend was particularly noticeable amongst the lowest-achieving students. The proportion of top-performing students in mathematics shrank by 4 percentage points between 2012 and 2018, while the proportion of top-performing students in science decreased by 9 percentage points between 2006 and 2018. Meanwhile, the proportion of low-achieving students in reading grew by 5 percentage points between 2009 and 2018; the proportion of low‑achieving students in mathematics grew by 3 percentage points between 2012 and 2018; and the share of low performers in science increased by 9 percentage points between 2006 and 2018.

294 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Snapshot of performance trends in FRANCE Mean performance Reading Mathematics Science PISA 2000 505* PISA 2003 496 511* PISA 2006 488 496 495 PISA 2009 496 497 498 PISA 2012 505* 495 499 PISA 2015 499 493 495 PISA 2018 493 495 493 Average 3-year trend in mean performance -0.4 -2.5* -0.8 Short-term change in mean performance (2015 to 2018) -6.7 +2.5 -2.0 Overall performance trajectory flat negative, but flattening (less negative over more recent years) flat Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -0.4 -1.9 -1.5 Percentage-point change in low-achieving students (below Level 2) +1.2 -1.1 -0.7 Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +3.0* -2.8* -1.7 Average trend amongst the lowest-achieving students (10th percentile) -4.0* -3.1* +0.7 Gap in learning outcomes between the highest- and lowest-achieving students widening gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. Mean science performance in France remained stable over the 2006-2018 period; similarly, no overall direction of change can be determined for mean reading performance over the 2000-2018 period. Mathematics performance declined between 2003 and 2018, but most of that decline was observed in earlier assessments; the recent trend is flat in mathematics too. In reading, the apparent stability hides distinct trends amongst students at different levels in the performance distribution. Amongst the lowest-achieving students, performance tended to decline (by 4 score points, on average, per 3-year period); whereas amongst the highest-achieving students, performance tended to improve (by 3 score points, on average, per 3‑year‑period). No such widening of performance gaps was observed in mathematics (where a similar decline was observed amongst the highest‑and lowest-achieving students, on average) and science.

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 295 Snapshot of trends in reading, mathematics and science performance Annex D Snapshot of performance trends in GEORGIA Mean performance Reading Mathematics Science PISA 2000 m PISA 2003 m m PISA 2006 m m m PISA 2009 374 379* 373 PISA 2012 m m m PISA 2015 401* 404 411* PISA 2018 380 398 383 Average 3-year trend in mean performance +3.5 +7.6* +5.6* Short-term change in mean performance (2015 to 2018) -21.5* -6.2 -28.5* Overall performance trajectory stable improving improving Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2009 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -0.1 m -0.1 Percentage-point change in low-achieving students (below Level 2) +2.4 m -1.2 Variation in performance Reading (2009 to 2018) Mathematics (2009 to 2018) Science (2009 to 2018) Average trend amongst the highest-achieving students (90th percentile) +0.5 +11.2* +3.4 Average trend amongst the lowest-achieving students (10th percentile) +11.6* +5.9* +10.6* Gap in learning outcomes between the highest- and lowest-achieving students narrowing gap stable gap narrowing gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. PISA 2018 results in Georgia were significantly below those observed in 2015 in reading and science, reversing most of the gains observed between 2010 and 2015. Only mathematics results in PISA 2018 remained significantly above the level observed in 2010.

296 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Snapshot of performance trends in GERMANY Mean performance Reading Mathematics Science PISA 2000 484* PISA 2003 491 503 PISA 2006 495 504 516* PISA 2009 497 513* 520* PISA 2012 508 514* 524* PISA 2015 509 506 509 PISA 2018 498 500 503 Average 3-year trend in mean performance +3.3* -0.1 -3.6* Short-term change in mean performance (2015 to 2018) -10.8 -5.9 -6.2 Overall performance trajectory positive, but flattening (less positive over more recent years) hump-shaped (more negative over more recent years) negative, and more so over more recent years Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +3.7* -4.1* -1.8 Percentage-point change in low-achieving students (below Level 2) +2.2 +3.4* +4.2* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +1.9 -2.8* -2.6 Average trend amongst the lowest-achieving students (10th percentile) +5.8* +2.8 -4.2* Gap in learning outcomes between the highest- and lowest-achieving students stable gap narrowing gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. In Germany, mean reading and mathematics performance in 2018 returned close to levels that were last observed in 2006 or 2009, reversing most of the gains observed over the early period (up to 2012); in science, mean performance was below 2006 levels. PISA 2018 results lay significantly below PISA 2012 results in mathematics. The recent trajectory of mean reading performance could be partly related to the changing composition of the student population. It could be estimated that, if the student population in 2015 had had the same demographic profile as the population in 2018, the average score in reading would have been 505 points (Table I.B1.40), or about 5 score points below the average observed score (Table I.B1.10). However, demographic changes account only for a small part of the larger negative trends observed in mathematics and science since 2012. In mathematics, while there was no overall trend in mean performance over the full 2003-2018 period, the trend was negative amongst the highest-achieving students (those at the 90th percentile). Over the most recent period, performance trends in Germany differed by gender. Between 2015 and 2018, girls’ performance in mathematics and science remained stable, while mean score amongst boys declined by 11 points in mathematics and by 12 points in science (Tables II.B1.7.36 and II.B1.7.42 in PISA 2018 Results [Volume II]: Where All Students Can Succeed).

PISA 2018 Results (Volume I): What Students Know and Can Do » © OECD 2019 297 Snapshot of trends in reading, mathematics and science performance Annex D Snapshot of performance trends in GREECE Mean performance Reading Mathematics Science PISA 2000 474* PISA 2003 472 445 PISA 2006 460 459 473* PISA 2009 483* 466* 470* PISA 2012 477* 453 467* PISA 2015 467 454 455 PISA 2018 457 451 452 Average 3-year trend in mean performance -1.5 +0.1 -5.9* Short-term change in mean performance (2015 to 2018) -9.6 -2.3 -3.2 Overall performance trajectory hump-shaped (more negative over more recent years) hump-shaped (more negative over more recent years) steadily negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) -2.0* -0.2 -2.1* Percentage-point change in low-achieving students (below Level 2) +9.2* +0.1 +7.7* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) -1.5 -0.8 -6.4* Average trend amongst the lowest-achieving students (10th percentile) -0.8 +0.5 -5.3* Gap in learning outcomes between the highest- and lowest-achieving students stable gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. Mean science performance in Greece declined steadily since 2006, by an average of 5.9 score points per 3-year period, even though changes from one round to the next were not always statistically significant. Performance in mathematics can be described as hump-shaped, mainly due to a spike in performance in PISA 2009; performance in other years was stable. Similarly, mean reading performance can be described as hump-shaped, with a steady decline in performance since its peak in 2009. Greece performed below the OECD average in all subjects in every year it participated in PISA. The decline in science performance over the 2006-2018 period was observed across the performance distribution. Performance amongst the highest-achieving students declined by 6.4 percentage points and that amongst the lowest-achieving students fell by 5.3 percentage points per 3-year period.

298 © OECD 2019 » PISA 2018 Results (Volume I): What Students Know and Can Do Annex D Snapshot of trends in reading, mathematics and science performance Snapshot of performance trends in HONG KONG (CHINA) Mean performance Reading Mathematics Science PISA 2000 525 PISA 2003 510 550 PISA 2006 536 547 542* PISA 2009 533 555 549* PISA 2012 545* 561 555* PISA 2015 527 548 523 PISA 2018 524 551 517 Average 3-year trend in mean performance +1.6 +0.4 -7.7* Short-term change in mean performance (2015 to 2018) -2.4 +3.2 -6.6 Overall performance trajectory hump-shaped (more negative over more recent years) flat increasingly negative Proficiency levels Reading (2009 to 2018) Mathematics (2012 to 2018) Science (2006 to 2018) Percentage-point change in top-performing students (Level 5 or 6) +2.4 -4.7* -8.1* Percentage-point change in low-achieving students (below Level 2) +4.3* +0.7 +2.8* Variation in performance Reading (2000 to 2018) Mathematics (2003 to 2018) Science (2006 to 2018) Average trend amongst the highest-achieving students (90th percentile) +4.8* -1.0 -9.6* Average trend amongst the lowest-achieving students (10th percentile) -1.5 +1.6 -5.4* Gap in learning outcomes between the highest- and lowest-achieving students widening gap stable gap stable gap * indicates statistically significant trends and changes, or mean-performance estimates that are significantly above or below PISA 2018 estimates. Source: OECD, PISA 2018 Database, Tables I.B1.7–I.B1.15 and I.B1.28–I.B1.30. In Hong Kong (China), mean reading, mathematics and science performance in 2018 was close to the level observed in 2015. When considering a longer period, reading performance in 2015-2018 was below PISA 2012 levels, but not significantly different from 2009 or 2002, the previous years in which reading was the major focus of the assessment. Science performance was below the level observed over the 2006-2012 period, while mathematics performance appeared stable, fluctuating around a flat trend over the 2003-2018 period. The apparent stability in reading performance between 2002, 2009 and 2018, however, hides widening performance gaps between the highest- and the lowest-achieving students. No similar widening of performance gaps was observed in either mathematics or science. In reading, the proportion of students scoring below Level 2 (low-achieving students) increased by 4 percentage points between 2009 and 2018. In science, the proportion of top-performing students decreased by 8 percentage points between 2006 and 2018.