Oktatási és Képzési Figyelő 2020

Oktatási és Képzési Figyelő 2020

Adatok

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Figure 1 – Variation in computer and information literacy scores across and within countries, 2013 [.xls] IEA, ICILS 2013.
Figure 2 – Variation in computer and information literacy scores across and within countries, 2018 [.xls] IEA, ICILS 2018.
Figure 3 – Distribution of computer and information literacy scores across achievement scale levels, 2013 and 2018 [.xls] IEA, ICILS 2018 & ICILS 2013.
Figure 4 – Underachievement in computer and information literacy, 2013 and 2018 [.xls] IEA, ICILS 2018 & ICILS 2013.
Figure 5 – Variation in computational thinking scores across and within countries, 2018 [.xls] IEA, ICILS 2018.
Figure 6 – Digital competence areas addressed in terms of learning outcomes in national curricula (ISCED 2), 2018/19 [.xls] European Commission/EACEA/Eurydice (2019). Digital Education at School in Europe. Annex 1b
Figure 7 – Persons who cannot afford a computer, by group of country of birth, 2018 [%] [.xls] Eurostat, EU-SILC. Special extraction.
Figure 8 – Percentage of school principals who report that the following shortages of resources hinder the school’s capacity to provide quality instruction ‘quite a bit’ or ‘a lot’ [.xls] OECD, TALIS 2018 Database, Table I.3.63.
Figure 9 – Percentage of teachers who reported investing in ICT to be of ‘high importance’ [.xls] OECD, TALIS 2018 Database, Table I.3.66.
Figure 10 – Percentage of teachers for whom use of ICT for teaching was included in their formal education, by year of completion [.xls] OECD, TALIS 2018 Database, Table I.4.13.
Figure 11 – Percentage of teachers who felt ‘well prepared’ or ‘very well prepared’ for the use of ICT for teaching, by year of completion [.xls] OECD, TALIS 2018 Database, Table I.4.20.
Figure 12 – Percentage of teachers reporting a high level of need of professional development in ICT skills for teaching [.xls] OECD, TALIS 2018 Database, Table I.5.21.
Figure 13 – Percentage of teachers who reported that they ‘frequently’ or ‘always’ let pupils in the target class use ICT for projects or class work in their class [.xls] OECD, TALIS 2018 Database, Table I.2.1.
Figure 14 – Percentage of teachers who reported that they ‘frequently’ or ‘always’ let pupils use ICT for projects or class work in their class, change from 2013 to 2018 [.xls] OECD, TALIS 2018 Database, Table I.2.4.
Figure 15 – Change in the rate of early school leavers from education and training, 2009-2019 [.xls] Eurostat, EU Labour Force Survey. Online data code: [edat_lfse_14].
Figure 16 – Early leavers from education and training by sex, country of birth and degree of urbanisation, 2019 [%] [.xls] Eurostat, EU Labour Force Survey 2019. Online data code: [edat_lfse_14], [edat_lfse_02] and [edat_lfse_30].
Figure 17 – Evolution of the ELET and completion rates in the EU-27 (2009-19) [.xls] Eurostat, EU Labour Force Survey. Online data code: [edat_lfse_14] and [edat_lfse_03]
Figure 18 – ELET rate versus completion rate (2019) [.xls] European Commission, DG EAC.
Figure 19 – Contextual factors influencing ELET: value of the regression coefficients [.xls] DG EAC calculations.
Figure 20 – Urban-rural divide in tertiary educational attainment (30-34) by country, 2019 [%] [.xls] Eurostat, EU Labour Force Survey. Online data code: [edat_lfs_9913].
Figure 21 – TEA rate (30-34 year-olds) by country and sex, 2019 [%] [.xls] Eurostat, EU Labour Force Survey. Online data code: [edat_lfse_03].
Figure 22 – TEA rate (30-34 year-olds) by country, 2009, 2019 and national targets [%] [.xls] Eurostat, EU Labour Force Survey. Online data code: [edat_lfse_03].
Figure 23 – Average annual increase of TEA rate in 1999-2009 and 2009-2019 in groups of countries above and below the EU-target in 2009 (pps) [.xls] Eurostat, EU Labour Force Survey, special data extraction, 2020.
Figure 24 – Participation in ECEC by children between 4-years-old and the starting age of compulsory education, 2017 and 2018 [%] [.xls] Eurostat, educ_uoe_enra10
Figure 25 – Participation in ECE by children between 4-years-old, respectively 3-years-old, and the starting age of compulsory education, 2018 (%) [.xls] Eurostat, educ_uoe_enra10 and educ_UOE_enra21.
Figure 26 – Participation in ECE of children from birth to the starting age of compulsory primary education, 2018 [%] [.xls] Eurostat calculation from educ_uoe_enra02 on 2018 data (demo_pjan)
Figure 27 – Underachievement rate in reading, 2018 [%] [.xls] PISA 2018, OECD.
Figure 28 – Long-term change in underachievement rate in reading, 2009-2018 [%] [.xls] PISA 2018 and 2009, OECD.
Figure 29 – Underachievement rate in mathematics, 2018 [%] [.xls] PISA 2018, OECD.
Figure 30 – Change in underachievement rate in mathematics, 2015-2018 [pps] [.xls] PISA 2018 and 2015, OECD.
Figure 31 – Underachievement rate in science in 2018 [%] [.xls] PISA 2018, OECD.
Figure 32 – Top performers in reading, 2018 and 2015 [%] [.xls] PISA 2018 and 2015, OECD.
Figure 33 – Top performers in mathematics, 2018 and 2015 [%] [.xls] Eurostat, EU-SILC. Special extraction, PISA 2018, OECD.
Figure 34 – Top performers in science, 2018 and 2015 [%] [.xls] PISA 2018, OECD.
Figure 35 – Underachievement rates of boys and girls in reading, 2018 [%] [.xls] PISA 2018, OECD.
Figure 36 – Underachievement rates of boys and girls in mathematics, 2018 [%] [.xls] PISA 2018, OECD.
Figure 37 – Underachievement rates of boys and girls in science, 2018 [%] [.xls] PISA 2018, OECD.
Figure 38 – Underachievers in reading [%] by socio-economic status (ESCS), 2018 [.xls] PISA 2018, OECD.
Figure 39 – Underachievers in reading [%] by migrant background, 2018 [.xls] PISA 2018, OECD.
Figure 40 – The employment rate of recent graduates, 2010-2019 [.xls] Eurostat, LFS, online data code: [edat_lfse_24]
Figure 41 – The employment rate premium of recent graduates by level and orientation of education compared to the average employment rate of young adults aged 20-34 who are not in further education or training, 2019 [.xls] Eurostat, LFS, online data code: [edat_lfse_24]
Figure 42 – Absolute change in employment rates of recent graduates by level and orientation of education, 2014-2019 [.xls] Eurostat, LFS, online data code: [edat_lfse_24]
Figure 43 – Full-time equivalent gross monthly wage by educational attainment (2018) age group 16-34 [.xls] -
Figure 44 – Full-time equivalent gross monthly wage by type of secondary education: vocational v general (2018), age group 16- [.xls] Eurostat, EU-SILC. Special extraction
Figure 45 – Adult (aged 25-64) participation in learning, 4-week reference period, 2010 and 2019 [.xls] Eurostat, LFS, online data code: [trng_lfse_01].
Figure 46 – Adult (aged 25-64) participation in learning, 12-month reference period, 2011 and 2016 [.xls] Eurostat, AES, online data code: [trng_aes_100]
Figure 47 – Adult (aged 25-64) participation in learning, 12-month reference period, distinguishing guided on the job training (GOJT), 2016 [.xls] Eurostat, AES, special data extraction for DG EMPL.
Figure 48 – Adult (aged 25-64) participation in learning, 12-month reference period, changes between 2011 and 2016, distinguishing guided on the job training (GOJT) [.xls] Eurostat, AES, special data extraction for DG EMPL.
Figure 49 – Adult (aged 25-64) participation in learning by employment status and level of qualification, 12-month reference period, EU-27, 2016 [.xls] Eurostat, AES, special data extraction for DG EMPL.
Figure 50 – The structure of non-learners (aged 25-64) by employment situation and country, 12-month reference period, 2016 [.xls] Eurostat, AES, special data extraction for DG EMPL.
Figure 51 – The percentage non-learners (aged 25-64) who are employed in the private sector, by level of qualification, 12-month reference period, 2016 [.xls] Eurostat, AES, special data extraction for DG EMPL.
Figure 52 – Relative importance of adult learning determinants across countries: personal v education vs job-related characteristics [.xls] CEDEFOP, AES 2016.
Figure 53 – Relative importance of adult learning determinants across countries: personal characteristics [.xls] CEDEFOP, AES 2016.
Figure 54 – Relative importance of adult learning determinants across countries: job-related characteristics [.xls] CEDEFOP, AES 2016.
Figure 55 – Outward degree and credit mobility of graduates, 2018 [%] [.xls] Eurostat, UOE, and OECD. Online data codes: [educ_uoe_grad01], [educ_uoe_mobg02] and [educ_uoe_mobc01] for graduates, degree-mobile graduates and credit-mobile graduates in the EU, EFTA, EEA and candidate countries. Special extraction from the OECD of international graduate data for degree-mobile graduates of EU origin who graduated in non-European countries (Australia, Canada, Chile, Colombia, Israel, Japan, Korea, New Zealand, Brazil and Russia). Eurostat, UOE, data extracted on 5 June 2020 and OECD data on 11 May 2020.
Figure 56 – Outward credit mobility by type of mobility scheme, ISCED 5-8, 2018 [.xls] Eurostat, UOE. Online data code: [educ_uoe_mobc01]. Data extracted on 5 June 2020.
Figure 57 – Inward degree mobility rates for tertiary education graduates by level of education and origin, 2018 [.xls] Eurostat, UOE, and OECD. Online data codes: [educ_uoe_grad01] and [educ_uoe_mobg02] and [educ_uoe_mobc01] for graduates and degree-mobile graduates in the EU, EFTA, EEA and candidate countries. Special extraction from the OECD of international graduate data for degree-mobile graduates of EU origin who graduated in non-European countries (Australia, Canada, Chile, Colombia, Israel, Japan, Korea, New Zealand, Brazil and Russia). Eurostat, UOE, data extracted on 5 June 2020 and OECD data on 11 May 2020.
Figure 58 – Inward degree-mobile graduates (ISCED 5-8) by area of origin, 2018 [.xls] Eurostat, UOE. Online data code: [educ_uoe_mobg02]. Data extracted on 5 June 2020.
Figure 59 – Comparison of EU performance on the ET2020 targets before and after BREXIT [.xls] Eurostat, online data codes: [sdg_04_10], [sdg_04_20], [sdg_04_30], [sdg_04_40] [sdg_04_50] and [sdg_04_60].
Figure 60 – Public expenditure on education, 2015-2018 [.xls] Eurostat, General Government Expenditure by Function (COFOG), online data base: [gov_10a_exp]
Figure 61 – Public expenditure on education by level, 2018 [.xls] Eurostat, COFOG, online data base: [gov_10a_exp]
Figure 62 – Public expenditure on education by category of expenditure, 2018 [.xls] Eurostat, General Government Expenditure by Function (COFOG), online data base: [gov_10a_exp]
Figure 63 – Change in real expenditure in pre-primary and primary level, 2015-2018 [.xls] Eurostat, COFOG, online data base: [gov_10a_exp].
Figure 64 – Change in real expenditure in secondary and post-secondary (non-tertiary) level, 2015-2018 [.xls] Eurostat, COFOG, online data base: [gov_10a_exp]
Figure 65 – Change in real expenditure over time at tertiary level, 2015-2018 [.xls] Eurostat, COFOG, online data base: [gov_10a_exp]
Figure 66 – Change in number of pupils and students at various education levels, 2013-2018 [.xls] European Commission, based on Eurostat data and UOE. Online data codes: [educ_uoe_enra01].
Figure 67 – ECEC summary table 1: Legal framework, 2019/20 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 68 – ECEC summary table 2: Selected quality aspects, 2019/20 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 69 – Staff with a minimum of a Bachelor's level qualification (ISCED 6), 2019/2020 [.xls] European Commission/EACEA/Eurydice.
Figure 70 – Summary table on achievement in basic skills, 2019/2020 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 71 – Top-level guidelines on underachievement as a topic in ITE, 2019/2020 [.xls] European Commission/EACEA/Eurydice.
Figure 72 – ELET Summary table 1, 2019/2020 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 73 – ELET Summary table 2, 2019/2020 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 74 – Policies/measures encouraging the inclusion of ELET in ITE and/or CPD, 2019/2020 [.xls] European Commission/EACEA/Eurydice.
Figure 75 – Summary table on higher education, 2019/2020 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 76 – Quantitative targets for widening participation and/or attainment of under -represented groups [.xls] European Commission/EACEA/Eurydice.
Figure 77 – Summary table on graduate employability, 2019/2020 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 78 – Summary table on learning mobility, 2018/2019 [.xls] European Commission/EACEA/Eurydice (forthcoming). Structural Indicators for Monitoring Education and Training Systems in Europe – 2020.
Figure 79 – Requirements or incentives for work placements for ALL students [.xls] European Commission/EACEA/Eurydice.
Figure 80 – Measures to support the participation of disadvantaged learners in learning mobility, EU-27 countries, 2018/2019 [.xls] European Commission/EACEA/Eurydice.
All figures [.zip]

Table of thematic boxes

Title Link
Box 1 – The COVID-19 crisis: school and campus closures, emergency measures, distance learning, loss of learning [link]
Box 2 – Croatian response to the COVID-19 crisis [link]
Box 3 – Computer and information literacy proficiency levels in ICILS [link]
Box 4 – Improving pupils’ digital competences in the Netherlands [link]
Box 5 – 8-Point Plan for digital learning – Austria [link]
Box 6 – Remote School – tackling digital exclusion in Poland [link]
Box 7 – Teaching computer science at primary level in Lithuania [link]
Box 8 – Consolidation of Latvia’s school network [link]
Box 9 – Integrating traditional textbooks with self-produced digital educational content in Italy [link]
Box 10 – Tackling early school leaving in Romania [link]
Box 11 – Tackling the early school leaving rate in Spain [link]
Box 12 – Measures to improve quality of higher education in Slovakia [link]
Box 13 – Policies to provide access for minority and disadvantaged children to quality early education in Germany [link]
Box 14 – Equity and inclusion – Estonia [link]
Box 15 – Irish initiatives for equality in education [link]
Box 16 – Accelerative integrated method of foreign language teaching [link]
Box 17 – Trilingual language portfolio KAJPATAJ and KLEPETO (Austria) [link]
Box 18 – Integration of recently-arrived migrant children in Greece [link]
Box 19 – DivEd, a language awareness project (Finland) [link]
Box 20 – E-Validiv, taking advantage of language diversity (Belgium) [link]
Box 21 – Grant-aided independent schools (Sweden) [link]