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  • Governor General:Julie Payette
  • 首相:Justin Pierre James Trudeau
  • 首都:Ottawa
  • 言語:English (official) 58.7%, French (official) 22%, Punjabi 1.4%, Italian 1.3%, Spanish 1.3%, German 1.3%, Cantonese 1.2%, Tagalog 1.2%, Arabic 1.1%, other 10.5% (2011 est.)
  • 政府
  • 統計局
  • 人口、人:37,058,856 (2018)
  • 面積、平方キロメートル:9,093,510
  • 1人当たりGDP、US $:46,125 (2018)
  • GDP、現在の10億米ドル:1,709.3 (2018)
  • GINI指数:No data
  • ビジネスのしやすさランク:22
すべてのデータセット:  A B C D E F G H I L M N O P Q R S T U
  • A
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2019
      データセットを選択
      Chapter C includes indicators that are a mixture of outcome indicators, policy levers and context indicators. Internationalisation of education and progression rates are, for instance, outcome measures to the extent that they indicate the results of policies and practices at the classroom, school and system levels. But they can also provide contexts for establishing policy by identifying areas where policy intervention is necessary, for example, to address issues of inequity.
  • B
  • C
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Average undergraduate and graduate university tuition fees, full-time Canadian students, Canada and provinces. This table is included in Section B: Financing education systems: Public and private expenditure on education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Canadian graduate tuition fees are weighted averages by field of study for full-time graduate students, annual (dollars). Data is collected from publicly funded, Canadian degree-granting institutions.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      This table contains 22 series, with data for years 2006/2007 - 2017/2018 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) Level of study (2 items: Canadian undergraduate; Canadian graduate).
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      This table contains 22 series, with data for years 2006/2007 - 2017/2018 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) Level of study (2 items: Canadian undergraduate; Canadian graduate).
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Canadian undergraduate tuition fees are weighted averages by field of study for full-time undergraduate students, annual (dollars). Data is collected from publicly funded, Canadian degree-granting institutions.
    • 12月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Number of certificates granted to registered apprentices and trade qualifiers in the top ten Red Seal trades in 2014 by age group, sex and certificate type group (with or without Red Seal endorsement), Canada, provinces and territories.
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Combined public and private expenditure on education as a percentage of gross domestic product (GDP) and index of change. This table is included in Section B: Financing education systems: Total expenditure on education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Combined public and private expenditure on educational institutions, by level of education. This table is included in Section B: Financing education systems: Total expenditure on education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 10月 2018
      ソース: U.S. National Center for Education Statistics
      アップロード者: Knoema
      以下でアクセス: 10 12月, 2018
      データセットを選択
      Common Core Data For Universe surveys, School District (LEA) The primary purposes of the Local Education Agency (School District) Universe Survey are:to provide a complete listing of every education agency in the United States responsible for providing free public elementary/secondary instruction or education support services;to provide basic information about all education agencies and the students for whose education the agencies are responsible.  
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_ou_comp The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The completion rate (educ_bo_ou_comp) was computed in the framework of the UOE data collection (jointly carried out by Unesco, OECD and Eurostat), but is usually disseminated by OECD only. The methodology for estimating completion rates varies across countries. They can use three methods: the cross-section method, the true cohort method, or the synthetic cohort method (see section 11.1 below for more details). The year of reference gives the reference year for the number of graduates. The estimation assumes constant student flows at the tertiary level, owing to the need for consistency between the graduate cohort in the reference year and the entrant cohort n years before. This assumption may be an oversimplification. Results are less reliable in systems in which enrolments fluctuate markedly, or students are faced with many different options as regards the length of courses for which they may enrol or in which there are many changes in programmes between the years of admission and graduation respectively. The inclusion of foreign students in the new entrant questionnaire can have an impact on the completion rates indicator. In some countries, the proportion of foreign students represents a large part of tertiary population, and all of them are considered as new entrants in tertiary education (as advised in UOE Guidelines) whereas most of them won't be graduated at this level of education. The consequence is to underestimate the completion rates in those countries with relatively large proportions of foreign students enrolled in tertiary education.
    • 8月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 13 8月, 2019
      データセットを選択
      The country statistical profiles provide a broad selection of indicators, illustrating the demographic, economic, environmental and social developments, for all OECD members. The dataset also covers the five key partner economies with which the OECD has developed an enhanced engagement program with (Brazil, China, India, Indonesia and South Africa) ,accession countries (Colombia, Costa Rica and Lithuania) , Peru and the Russian Federation. The user can easily compare indicators across all countries. Total fertility rates - Unit of measure used: Number of children born to women aged 15 to 49
  • D
  • E
    • 12月 2015
      ソース: United Nations Development Programme
      アップロード者: Misha Gusev
      データセットを選択
      Calculated using Mean Years of Schooling and Expected Years of Schooling.
    • 8月 2019
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 02 8月, 2019
      データセットを選択
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Education Statistics Publication: https://datacatalog.worldbank.org/dataset/education-statistics License: http://creativecommons.org/licenses/by/4.0/   The World Bank EdStats All Indicator Query holds over 4,000 internationally comparable indicators that describe education access, progression, completion, literacy, teachers, population, and expenditures. The indicators cover the education cycle from pre-primary to vocational and tertiary education.
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2019
      データセットを選択
      This indicator presents internationally comparable data regarding the labour force status and the educational attainment level by the National Educational Attainment Categories (NEAC) as reported by the labour force survey (LFS) and published in OECD Education at a Glance 2017. For trend data, the Education at a Glance Database includes data from 1981 to 2016 (or years with available data).
    • 5月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 07 5月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national official sources. Definition:Educational attainment is defined as the highest level successfully completed by the person, in the educational system of the country where the education was received. The levels of education are defined according to the International Standard Classification of Education (ISCED): - Primary: ISCED level 1 - Lower secondary: ISCED level 2 - Upper and post secondary non-tertiary: ISCED levels 3-4 - Tertiary: ISCED 1997 levels 5-6 or ISCED 2011 levels 5-8. In this table the upper secondary level includes post-secondary non-tertiary education. For most countries the transition from ISCED 1997 to ISCED 2011 is from the scool year 2013-2014. For more details see Country Footnotes. .. - data not available Country: Armenia Change in definition (1980 - 1990): Level of education ?not stated? includes population without education attainment. Country: Armenia Reference period (1980): Data refer to 1979 Country: Armenia Reference period (1990): Data refer to 1989 Country: Austria Break in methodology (2004): In 2014 a new weighting procedure for the LFS was introduced. Following this change in the weighting procedure, data was revised back to 2004. Country: Austria ISCED-11 (2014 onwards): Break in series due to the reclassification of a programme spanning levels: the qualification acquired upon successful completion of higher technical and vocational colleges is allocated in ISCED 2011 to ISCED level 5; under ISCED 1997 the same qualification was reported on ISCED level 4, but earmarked as equivalent to tertiary education Country: Austria Change in definition (1980 - 2000): Data before 2000 do not comply with ISCED97 as regards distinction between upper secondary and tertiary. ISCED97 5B mainly included in Upper Secondary. Country: Austria Change in definition (2004 - 2015): Data include ISCED Level 3c short in lower secondary level. Country: Azerbaijan Reference period (1980 - 2013): Data refer to end of year. Country: Belarus Additional information (1990 - 2013): Total includes population without education. Country: Belarus Break in methodlogy (1990): Data refer to 1989 census Country: Belarus Break in methodlogy (2000): Data refer to 1999 census Country: Belgium 2010: break in series: change in methodology. Measurement: Persons , Country: Bosnia and Herzegovina Population by educational attainment, educational level not stated refers to the population with no primary schooling and some primary. Country: Bulgaria Break in methodlogy (1980): Data are from 1985 census Country: Bulgaria Break in methodlogy (1990): Data are from 1992 census Country: Bulgaria Break in methodlogy (2001): Data are from 2001 census Country: Bulgaria Reference period (1995 - 2002): Data refer to June of respective year Country: Canada Additional information (1990 - onwards): Data cover non-institutionalized population in the 10 provinces, i.e. excluding the three Territories. Country: Croatia Change in definition (1980 - 1990): Data refer to population with permanent residence irrespective of actual residence and duration. "Education level-not stated" comprises persons with unknown education level as well as persons with no school at all. Country: Croatia Change in definition (2001 - 2013): "Education level-not stated" comprises persons with unknown education level as well as persons with no school at all. Country: Croatia Reference period (1980): Data refer to 1981 Country: Croatia Reference period (1990): Data refer to 1991 Country: Cyprus Change in definition (1990): Lower secondary level is included in upper secondary level Country: Cyprus Reference period (1990): Data refer to 1989 Country: Cyprus Reference period (1995): Data refer to 1992 Country: Cyprus Data cover only government controlled area Country: Cyprus From 2014, data compiled using ISCED 2011 classification. Country: Cyprus From 2000, persons who have not attended or finished primary education also included in primary education level. Country: Estonia Change in definition (1980 - 2000): Data are from censuses and refer to population aged 25+ Data for primary level attainment include persons who have not completed the primary level education. Country: Estonia Change in definition (2001 - 2013): Age group 25+ refers to 25-74, age group 50+ refers to 50-74. Data for primary level attainment include persons who have not completed the primary level education. Country: Estonia Change in definition (2012): Data is from census 2011. Data refer to 31.december 2011 Data for primary level attainment include persons who have not completed the primary level education. Country: Estonia Reference period (1980): Data refer to 1979 Country: Estonia Reference period (1990): Data refer to 1989 Country: Finland Data for lower secondary level include primary level. Country: Georgia Change in definition (1980 - 2013): Level of education ?not stated? includes population without education attainment Country: Georgia Reference period (1980): Data refer to 1979 Country: Georgia Reference period (1990): Data refer to 1989 Country: Germany Data from 1990 to 1998 are classified according to ISCED-76, data from 1999 to 2013 according to ISCED 97, data from 2014 on are classified according to ISCED 2011. Country: Greece Break in methodology (2000): From 2000, data refer to population residing in private households Country: Greece Change in definition (2001 - 2013): "Primary" includes also persons that did not completed ISCED 1 programs Country: Greece Data refer to annual averages. From 2014, estimates use ISCED-2011 classification. Country: Hungary Break in methodlogy (1995): Before 1995, data are from population censuses. From 2000, from Country: Hungary Change in definition (2000 - 2008): Data refer to population aged 25-74. Country: Iceland Break in methodology (2003): Change in data collection procedure. Data classified according to ISCED 2011. Country: Iceland Reference period (1990): 1990 refers to 1991 Country: Ireland From 2000, data refer to age group 25-64. From 2014, data are compiled according to ISCED-2011. As a result data breakdown by education level not fully comparable with previous years. Country: Ireland Reference period (1980): Data refer to1981 Country: Ireland Reference period (1990): Data refer to 1991 Country: Ireland Reference period (1995): Data refer to 1996 Country: Israel Break in methodlogy (2001): Changes in the weighting method. Country: Israel Break in methodlogy (2009): Transition to the 2008 Population Census estimates. Country: Israel Break in methodlogy (2012): Transitiom from a quarterly to a monthly LFS. Country: Israel From 2012, using ISCED-2011. Totals include population by educational attainment, pre-primary. Country: Italy Break in methodology (2004): Change in data collection procedure. From 2014, data classified by ISCED 2011. Country: Italy Change in definition (1980 - 1990): Data for primary level attainment include persons who have not completed the primary level education Country: Kyrgyzstan Break in methodlogy (2000): Data refer to 1999 Census Country: Kyrgyzstan Break in methodlogy (2009): Data refer to 2009 Census Country: Kyrgyzstan Reference period (1990): Data refer to 1989 Census Country: Latvia Change in definition (1995 - 2001): Population aged 15+. Data for primary level refers to level 0 and 1 of ISCED 1997 classification. Country: Latvia Change in definition (2002 onward): Population 15-74 age group. For 2002-2013, data for primary level refers to level 0 and 1 of ISCED 1997 classification. From 2014, data for primary level refers to level 0 and 1 of ISCED 2011 classification. Country: Latvia Reference period (1995): Data refer to 1996 Country: Luxembourg Additional information (1990 - onwards): Data for age group 25+ refer to 25-74. Country: Luxembourg Break in methodlogy (2003): Switch from a face-to-face to a telephone survey Country: Luxembourg Break in methodlogy (2009): Random Digit Dialing has replaced the register-based sampling Country: Luxembourg Change in definition (1990 - 2012): The categroy `Lower secodnary` also includes persons who have at most attained the primary level Country: Luxembourg Reference period (1990): Data refer to 1992 Country: Malta Some data not shown due to lack of reliability. Country: Moldova, Republic of Territorial change (2000 onward): Data exclude the territory of the Transnistria and municipality of Bender Country: Netherlands Since 2003, ''Primary'' includes also ISCED level 0 (persons who have not successfully completed ISCED 1 programs). Country: Norway Break in methodology (2007): As of 2007, the results of a survey on education completed abroad before immigration to Norway is included. As a result , the proportion of & 39;educational level not stated& 39; was reduced. All data compiled according ISCED 2011. Country: Poland Change in definition (1990 - 2002): Upper secondary level includes lower secondary level. Country: Poland Reference period (1990): Data refer to 1988 Country: Portugal Data from 2011 onwards are not directly comparable with data for the previous years due to new data collection methods used in the Portuguese Labour Force Survey series. Data from 2014 onward are compiled according to ISCED-2011. Data for ''educational level not stated'' refer to individuals who have not successfully completed ISCED level 1. Country: Romania Break in methodology (2002): Data series of 2002-2012 are not perfectly comparable with data series of previous years. For years 2014 onward data were estimated using the resident population. For year 2013 data were estimated based on revised population figures (resident population) in accordance to the 2011 Census results. Starting with year 2014 educational attainment collected according to ISCED 2011. Educational level not stated includes persons without any formal education graduated. Country: Serbia Data for education level not stated include population without education attainment. Country: Slovakia Change in definition (1995): data for total of education levels include only secondary and tertiary levels. Country: Slovakia Change in definition (2001 - 2011): data on primary education according to ISCED 97, level 1 is not available Country: Slovenia From 2014 data are compiled according to ISCED-2011 and persons with ISCED level 0 are excluded. Country: Spain Data are annual averages of the four quarters of the year. From 2014 data are compiled according to ISCED-2011 Country: Sweden Break in methodlogy (2002): Quality improvement and change in classification from ISCED 1976 to ISCED 1997. Country: Sweden Change in definition (1990 - 2013): Data refer to population aged 25-74 Country: Switzerland Break in methodlogy (2010): Major changes in data collection procedures (quaterly data instead of annual data). Country: Switzerland Change in definition (1990 - 2001): Lower sedondary education includes primary education Country: Switzerland Change in definition (2002): Change in definition of educational attainment levels Country: Switzerland Reference period (1990): Data refer to 1991 Country: Switzerland Since 2014, data are compiled according to ISCED-2011 Country: United States Change in definition (1980): Primary refers to grades 5-8, Lower Secondary refers to grade 9 in High School, no diploma, Upper Secondary refers to High School, college graduate, Tertiary refers to people who have completed Associate& 39;s degree through Doctorate degree, Not stated refers to people who didn& 39;t complete any schooling through 4th grade. Data based on completed schooling years. Country: United States Change in definition (1990 - 2015): Primary refers to grades 5-8, Lower Secondary refers to grade 9 in High School, no diploma, Upper Secondary refers to High School, college graduate, Tertiary refers to people who have completed Associate`s degree through Doctorate degree, Not stated refers to people who did not complete any schooling through 4th grade. Data based on degrees.
    • 9月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Educational attainment in the population aged 25 to 64, off-reserve Aboriginal, non-Aboriginal and total population, Canada and jurisdictions. This table is included in Section D: Postsecondary education: Educational attainment of the population aged 25 to 64 of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Educational attainment of the population aged 25 to 64, by age group and sex, Organisation for Economic Co-operation and Development (OECD), Canada, provinces and territories. This table is included in Section D: Postsecondary education: Educational attainment of the population aged 25 to 64 of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 29 4月, 2019
      データセットを選択
      The nature of expenditure distinguishes between current and capital expenditure. The resource category refers to service provider (public institutions, government-dependent private institutions, and independent private institutions, i.e. both educational and other institutions). These expenditure figures are intended to represent the total cost of services provided by each type of institution, without regard to sources of funds (whether they are public or private).
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      All entities that provide funds for education, either initially or as final payers, are classified as either governmental (public) sources or non-governmental (private) sources, the sole exception being "international agencies and other foreign sources", which are treated as a separate category. There are three types of financial transactions: Direct expenditure on educational institutions; Transfers to students or households and to other private entities; and Households' expenditure on education outside educational institutions.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      These indicators on expenditure on education are published in chapter C of Education at a Glance, which covers financial and human resources invested in education.They are either policy levers or provide context information on education systems, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.The data set “educational finance indicators” provides the main indicators computed for three levels of education : primary, secondary and post-secondary non-tertiary levels combined; tertiary level; and primary to tertiary levels combined. Other datasets provide more breakdowns for each specific indicator.
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 02 7月, 2019
      データセットを選択
      The classification of personnel is based on functions and organises staff into four main functional categories: 1) Instructional Personnel; including two sub-groups: A. Classroom Teachers (ISCED 0-4) and Academic Staff (ISCED 5-6); and B. Teacher Aides (ISCED 0-4) and Teaching / Research Assistants (ISCED 5-6); 2) Professional Support for Students; including two sub-groups: A. Pedagogical Support (ISCED 0-4) and Academic Support (ISCED 5-6); B. Health and Social Support (ISCED 0-6); 3) Management/Quality Control/Administration; including four subgroups: A. School Level Management (ISCED 0-6); B. Higher Level Management (ISCED 0-6); C. School Level Administrative Personnel (ISCED 0-6); and D. Higher Level Administrative Personnel (ISCED 0-6); 4) Maintenance and Operations Personnel.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      This dataset presents the average number of teachers by sex and age.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      This dataset presents the average number of teachers by sex and type of institution.
    • 9月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 17 9月, 2019
      データセットを選択
      Number of students enrolled in different education programmes by age and sex.
    • 5月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 21 5月, 2019
      データセットを選択
      This dataset presents the number of students enrolled in different education programmes by field and sex.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      This indicator examines the share of students by gender, programme orientation and mode of study over the total number of students.
    • 8月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 06 8月, 2019
      データセットを選択
      Number of students enrolled in different education programmes by type of institution and sex.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      Number of students by level of education, adjusted to the financial year. When financial year, school year and calendar year differs, adjustments are made to ease comparison.
    • 3月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 15 3月, 2019
      データセットを選択
      This dataset presents the number of students enrolled in different education programmes by country of origin and sex.
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 08 10月, 2019
      データセットを選択
      Enrolment rate per age is the percentage of students enrolled in each type of institution over the total of students
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 22 4月, 2019
      データセットを選択
      UNECE Statistical Database, compiled from national and international (UNESCO Institute for Statistics) official sources. The net enrollment ratio is the number of students of the official school-age group (defined by each country) enrolled in secondary-level education per 100 persons of the same age group. The gross enrollment ratio is the number of students enrolled in secondary level education (regardless of their age) per 100 persons of the official school-age group corresponding to secondary-level education. The secondary level consists of lower and upper secondary levels of ISCED 2011. .. - data not availableMeasurement: Gross enrollment ratio , Country: ArmeniaSince the school year 2013-2014, the data have been compiled according ISCED 2011.Country: AustriaChange in definition (1995 - 2012): NER: data include ISCED level 4 programmes and refer to official school age group assumed to be 10-17 years.Country: AustriaBreak in series (2013): From school year 2013-2014 onwards use of ISCED 2011.Country: BulgariaNER data refer to students aged 11-20 and include a small number of ISCED level 4 students aged 19 to 20.Country: CroatiaNER data refer to students aged 11-18.Country: CyprusData cover only government controlled area. Data refer to level 3 of ISCED 1997 only. 1980/1981, 1990/1991, 1995/1996: data refer to ISCED 1976 classification. 2000/2001: data refer to 1999/2000.Country: CzechiaChange in definition (1995 - 2012): Data refer to full-time study only and exclude part-time studyCountry: EstoniaNER data refer to students aged 13-17.Country: Finland 1990/1991: data refer to ISCED 1976 classification.Country: GeorgiaData refer to beginning of the school year.Country: Germany Data cover the territory of Germany after reunification. 1980/1981, 1990/1991, 1995/1996: data refer to ISCED 1976 classification. For school years 2000/2001 - 2013/2014: data refer to ISCED 1997 classification. Data on students refer to beginning of the school year and data on population refer to beginning of the calendar year.Country: Hungary2000/2001: data refer to 1999/2000. NER data refer to students aged 14-17. Data refer to levels 3 and 4 of ISCED classification.Country: Iceland1980/1981-1995/1996: data refer to ISCED 1976 classification.Country: Ireland 1995/1996: data refer to ISCED 1976 classification. From 2000/2001: data refer to levels 2,3 and 4 of ISCED 1997 classification. Data refer to students aged 11-19.Country: IsraelData refer to level 3 of ISCED classification. 2000/2001: data exclude students registered in Ministry of Religious Affairs.Country: ItalyData refer to level 3 of ISCED classification and refer to the school year.Country: LatviaBreak in methodology (2006): Changes in national education classification. Started from school year 2006/2007 level 2 includes grades 1-6, level 3 includes grades 7-12.Country: LithuaniaData refer to 1 January of the school year. NER data refer to students aged 11-18.Country: Moldova, Republic ofAdditional information (2006 - 2012): Stable population used during the enrollment rates calculation, because the actual population does not reflect the real situation of migration.Country: Moldova, Republic ofChange in definition (1990 - 2005): Data refer to age group 11-17 years.Country: Moldova, Republic ofChange in definition (2006 - 2012): Data refer to age group 11-18 years.Country: MontenegroData refer to level 3 of ISCED classification.Country: Netherlands1990/1991: data do not include special secondary education.Country: PolandData refer to level 3 of ISCED 1997.Country: RomaniaData refer to 1 July of the school year.Country: SerbiaTerritorial change (2003 - 2012): The Statistical Office of the Republic of Serbia has no available data on the AP Kosovo and Metohija.Country: SloveniaData refer to 15 September of the school year.Country: Spain2000/2001: data refer to 1999/2000. 1990/1991: NER data refer to students aged 11-18. From 1995: NER data refer to students aged 12-18. Data refer to October - September of the school year.Country: The former Yugoslav Republic of MacedoniaBreak in methodology (2010): From 2010/2011 implementation of the Law on Primary and Lower Secondary educationCountry: TurkeyChange in definition (2000 onwards): From 1997/1998: compulsory education was expanded to 8 years by law.
    • 9月 2017
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Estimated average scores and percent distribution of 15-year-old students, science, by proficiency level, Programme for International Student Assessment (PISA), Canada, provinces and participating countries, Council of Ministers of Education Canada (CMEC). This table is included in Section C: Elementary-secondary education: Student achievement of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2017
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Estimated average scores of 15-year-old students, reading, mathematics and science, Programme for International Student Assessment (PISA), Canada, provinces and participating countries, Council of Ministers of Education Canada (CMEC). This table is included in Section C: Elementary-secondary education: Student achievement of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2017
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Estimated average scores 15-year-old students, science assessment, by science scale and science sub-scales, Programme for International Student Assessment (PISA), Canada, provinces and participating countries, Council of Ministers of Education Canada (CMEC). This table is included in Section C: Elementary-secondary education: Student achievement of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2014
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2014
      データセットを選択
      Countries report expenditures by sources of funds: Governement (central, regional, local); International agencies and other foreign sources; Households and Other private entities (including firms and religious institutions and other non-profit organisations). Three types of financial transactions can be distinguished: -direct expenditure/payments on educational institutions -Intergovernmental transfers for education -Transfers to students or households and to other private entities.
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 06 7月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_fi_ftot The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening accesseduc_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age   B. Study frameworkeduc_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education   C. Student and staff mobilityeduc_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country)   D. Effective outcomes and employabilityeduc_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A     The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities:Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • 7月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 2月, 2019
      データセットを選択
      Financial information of universities and degree-granting colleges, type of expenditures by geography, type of university or college and type of fund and function.
  • F
    • 8月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 8月, 2019
      データセットを選択
      In view of the strong demand for cross-national indicators on the situation of families and children, the OECD Family Database was developed to provide cross-national indicators on family outcomes and family policies across the OECD countries, its enhanced engagement partners and EU member states. The database brings together information from various national and international databases, both from within the OECD and from external organisations. The database classifies indicators into four main dimensions: (i) structure of families, (ii) labour market position of families, (iii) public policies for families and children and (iv) child outcomes. Detailed information on the definitions, sources and methods used in the construction of the database can be found on the OECD Family Database webpage.
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 05 7月, 2019
      データセットを選択
      Chapter B includes indicators that are either policy levers or antecedents to policy, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.
    • 9月 2014
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2014
      データセットを選択
      The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Students are classified as foreign students (non-citizens) if they are not citizens of the country in which the data are collected. While pragmatic and operational, this classification is inappropriate for capturing student mobility because of differing national policies regarding the naturalisation of immigrants. Countries that have lower propensity to grant permanent residence to its immigrant populations are likely to report second generation immigrants as foreign students. Therefore, for student mobility and bilateral comparisons, interpretations of data based on the concept of foreign students should be made with caution. Students are classified as international students if they left their country of origin and moved to another country for the purpose of study. Depending on country-specific immigration legislation, mobility arrangements, and data availability, international students may be defined as students who are not permanent or usual residents of their country of study or alternatively as students who obtained their prior education in a different country, including another EU country.
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_mo_el8i The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • 3月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Full-time educators (headcount) in public elementary and secondary schools, number and percentage distribution by sex and age group, Canada and provinces. This table is included in Section C: Elementary-secondary education: Elementary-secondary school: enrolments and educators of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
  • G
    • 2月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 06 3月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national and international official sources. Definitions: Gender pay gap is the difference between men’s and women’s average earnings from employment, shown as a percentage of men’s average earnings.The UNECE gender statistics database presents two indicators on gender pay gap, which represent two different concerns of gender equality. Gender Pay Gap in hourly wage rates refers to the gender gap in average hourly earnings. This indicator aims to capture the difference between men’s and women’s overall position in the labor market. It measures the difference between men’s and women’s wage rates independent of the number of hours worked, the type of activity or the type of occupation. Gender Pay Gap in monthly earnings refers to the gender gap in average monthly earnings. This indicator aims to capture the variance between men’s and women’s earnings over a specific period of time. It reflects differences in time worked and type of work performed, which translates into gender differences in economic autonomy. Wage rates are earnings elements meant to be measured, as stipulated by the ILO Resolution concerning an integrated system of wages statistics (ILO, 1973), in relation to an appropriate time period such as the hour, day, week, month or other customary period used for purposes of determining the wage rates concerned. In the case of these statistics, the reference time period is the hour. Wage rates should include basic wages, cost-of-living allowances and other guaranteed and regularly paid allowances, but exclude overtime payments, bonuses and gratuities, family allowances and other social security payments made by employers. Ex gratia payments in kind, supplementary to normal wage rates, are also excluded. Earnings relate to remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as for annual vacation, other paid leave or holidays. Earnings include direct wages and salaries for the time worked, or work done, remuneration for time not worked, bonuses and gratuities and housing and family allowances paid by the employer directly to his employee. Earnings exclude employers’ contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. Gross earnings refer to total earnings before any deductions are made by the employer in respect of taxes, contributions of employees to social security and pension schemes, life insurance premiums, union dues and other obligations of employees. Net earnings refer to pay allocated to the worker after deductions are made by the employer in respect of taxes, contributions of employees to social security and pension schemes, life insurance premiums, union dues and other obligations of employees. Educational attainment is defined as the highest level successfully completed by the person, in the educational system of the country where the education was received. The levels of education are defined according to the ISCED 1997 General note: Data are compiled from gross earnings and cover paid employees in all categories of activities and workers in full time and part-time employment. Any deviations from these are specified in the subsequent notes, to the extent the information is available. Gender pay gap in hourly wage: For EU member countries, the data are compiled from hourly earnings available in Eurostat’s online database devired from the Structure of Earnings Surveys. Please refer to the EU Structure of Earnings Survey methods and their gender pay gap in unadjusted form for further explanations. For non-EU countries, the figures are compiled from hourly earnings data provided by the countries in response to the UNECE questionnaire. Gender pay gap in monthly earnings: Figures are compiled from monthly earnings data provided by the countries in response to the UNECE questionnaire and official earnings data available in Eurostat and ILO databases. See the note ’Method and data sources for the gender pay gap in the UNECE Statistical Database’ for more information. Country: Austria Gross monthly earnings refer to the monthly amount in the main job. It includes usual paid overtime, tips and commission but excludes income from investments, assets, savings, stocks and shares. Profit share and bonuses are taken into account. Supplement payments (13th, 14th month, holiday pay...) are not included as they are not surveyed in this question, but they could be modeld (average gross monthly earning per group x14/12) under the simplified assumption that people are employed for the whole year and all receive these benefits. Country: Austria ISCED-11 is used from survey year 2014 on, before that ISCED-97. Country: Belgium For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys. Earlier data are compiled from national sources. For gender pay gap in monthly earnings, underlying average earnings data are compiled from EU Structure of Earnings Surveys. Country: Bulgaria Data cover employees only and are compiled from enterprise survey (four-yearly Structure of Earnings Survey). Overtime payments are included in average earnings. Country: Bulgaria From 2014 the educational breakdown is according to the ISCED-11. Country: Canada For GPG in hourly earnings, data covers employees only, self-employed are excluded. Country: Cyprus Data are based on the results of the Structure of Earnings Survey (SES) for years 2006 and 2010. Data for 2006 and 2010 have been revised to better reflect the definitions provided by UNECE.Hourly Wage Rate includes normal salary and regular bonuses paid to the employee (including payments for shift work). It excludes overtime payments, irregular bonuses and payments in kind.Monthly earnings include normal salary, regular bonuses paid to the employee (including payments for shift work) and payments for overtime. They exclude irregular bonuses and payments in kind.Coverage: Enterprises in all economic activities, excluding Agriculture, Fishing, Activities of Private Households and Extra-territorial Organisations. All enterprises covered had one or more employees. Self-employed are not covered.Geographical coverage: data refer to Government controlled areas only. Country: Czechia Reference period (2011 - 2012): For upper secondary and post-secondary non-tertiary education, data refer to ISCED 3 only (instead of 3-4), and fro tertiary education , data refer to ISCD 6 only (instead of 5-6). Country: Czechia Since 2011 all employees included in the sample surveys,including employees of enterprises with less than ten employees, employees of non-profit organizations, and also own-account workers that had not been measuredbefore. Country: Denmark For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys. Earlier data are compiled from national sources. For gender pay gap in monthly earnings, underlying average earnings data are compiled from EU Structure of Earnings Survey. Country: Estonia For gender pay gap in monthly earnings, data exclude self-employed persons. From 2014, breakdown by education is according to ISCED-2011. Country: Finland The method of defining part/full-timers changed in 2001. Country: Finland Data do not include irregular bonuses, housing and family allowances. Average monthly earnings data cover only full-time employees. Country: France For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys. Earlier data are compiled from national sources. For gender pay gap in monthly earnings, the underlying average earnings data for 2006 are compiled from EU Structure of Earnings Survey and cover employees in enterprises of 10 or more employees only. People working in public sector are not covered in data up to 2009. From 2014 data include overseas departments. Country: Germany For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys. Earlier data are compiled from national sources. For gender pay gap in monthly earnings, the underlying average earnings data for 2006 are compiled from EU Structure of Earnings Survey and cover employees in enterprises of 10 or more employees only. People working in public sector are not covered. From 2014 breakdown by education compiled using ISCED-2011. Country: Greece For gender pay gap in hourly earnings, data from 2002 are compiled from European Structure of Earnings Surveys. Earlier data are compiled from national sources. For gender pay gap in monthly earnings, the underlying average earnings data from 2006 on are compiled from EU Structure of Earnings Survey and cover employees in enterprises of 10 or more employees only. People working in public sector are not covered. Country: Hungary Data include only full-time employees. B-S (-O), 10 employees or more Country: Israel Change in definition (2006 - 2012): Data cover both - paid employees and self-employed Country: Israel Change in definition (2006 - 2012): Data cover both - paid employees and self-employed Country: Italy For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys (SES). The difference with the SES definition is that the SES definition contains overtime earnings and hours. Due to methodological changes, the data for 2014 might be uncomparable with the previous years. For monthly earnings, data are compiled from households surveys (EU-SILC) from 2006 to 2009 and from SES from 2010 onwards. The main difference with the SES definition is that the SES definition refers to the month of october and excludes bonuses and other items not payable each month. Due to methodological changes, the data for 2014 might be uncomparable with the previous years. Country: Latvia Additional information (2002 onward): Data by education level are calculated for enterprises with number of employees 10 and more for NACE Rev.1.1 sections C-K (excluding L) on 2002 and 2006 and for NACE Rev.2 sections B-S (excluding O) on 2010 according to the methodology of structural indicator of European Comission Gender Pay Gap (GPG). Country: Latvia Data cover paid employees only. Part-timers earnings have been equivalised to fill-time units. All data exclude remuneration of kind. Country: Lithuania The gross earnings data on which GPG in monthly earnings are based exclude housing and family allowances. From 2014 data are compiled according to ISCED-2011. Country: Luxembourg For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys. For gender pay gap in monthly earnings, data are compiled from European Structure of Earnings Surveys. Average monthly earnings are based on full-time equivalent employees, reference month is october. NACE B to S exclunding O Country: Malta For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys. Earlier data are compiled from national sources. For gender pay gap in monthly earnings, the underlying average earnings data for 2006 are compiled from EU Structure of Earnings Survey and cover employees in enterprises of 10 or more employees only. People working in public sector are not covered. Country: Norway Break in methodlogy (2005): Figures from 2005 for wages by level of education are not comparable with the figures for 2004 and earlier, due to changes in definitions. Country: Norway Change in definition (2000 onward): Data refer to full-time equivalent of paid employees only. Country: Poland Change in definition (2001 - 2004): Data cover employees only. Family allowances are not inclueded. Data refer to full-time employees only. Country: Poland Change in definition (2006 onward): Data cover employees only. Family allowances are not inclueded. Country: Portugal For gender pay gap in hourly earnings, data from 2006 are compiled from European Structure of Earnings Surveys. Earlier data are compiled from national sources. For gender pay gap in monthly earnings, the underlying average earnings data for 2006 are compiled from EU Structure of Earnings Survey and cover employees in enterprises of 10 or more employees only. People working in public sector are not covered. Country: Romania Data by education level are derived from the Structure of Earnings Survey and related to enterprises with 10+ employees. The underlying average monthly gross earnings refers to October. Country: Russian Federation Change in definition (2005 - 2013): Underlying Earnings data do not include end of year, seniority, bonus payments and other nonrecurrent payments . Data include employees worked whole October; data exclude non-regular, temporary, contractual, absent due to different reasons (maternity, sabbatical, annual leave), part-time workers and others. Country: Slovakia Additional information (2000 - 2012): The concept of Earnings in definitions, geographical coverage, reference period are in compliance with the request. Country: Slovenia Break in methodlogy (2007 - 2013): In 2007 EURO was introduced instead of the national currency SIT. Country: Slovenia Change in definition (2003 - 2013): Data refer to full-time employees only. Country: Slovenia Provisional value (2012): Country: Spain Additional information (2000): The results have been obtained as annual average of quarterly data form a wage survey. The coverage are local units with 5 or more employees. Country: Spain From 2002-2003, the coverage is local units with 10 or more employees. Since 2004, coverage has been extended to all size units. ISCED-97 is used 2002-2010 and ISCED-11 in 2014. Country: Sweden Change in definition (2000 onwards): The Data cover only employees and exlude irregular bonuses and gratuities. Country: Switzerland For monthly earnings, up to 2010 the data cover employees in private and public federal sectors. since 2012, the data concern only the private sector. Country: Switzerland The underlying average earnings data exclude overtime pay and family allowances and refer to full-time equivalents. GPG figures computed from median earnings instead of averages. Country: The former Yugoslav Republic of Macedonia For gender pay gap in monthly earnings, the underlying average earnings data are compiled from EU Structure of Earnings Survey and cover employees in enterprises of 10 or more employees only. People working in public sector are not covered
    • 11月 2019
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 06 11月, 2019
      データセットを選択
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Gender Statistics Publication: https://datacatalog.worldbank.org/dataset/gender-statistics License: http://creativecommons.org/licenses/by/4.0/
    • 12月 2018
      ソース: World Economic Forum
      アップロード者: Knoema
      以下でアクセス: 28 1月, 2019
      データセットを選択
       Data cited at: The World Economic Forum https://www.weforum.org/ Topic: The Global Gender Gap Report 2018 Publication URL: https://www.weforum.org/reports/the-global-gender-gap-report-2018 License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode   This dataset provides education and skills related indicators that present in Global Gender Gap Report
    • 1月 2019
      ソース: INSEAD
      アップロード者: Knoema
      以下でアクセス: 12 3月, 2019
      データセットを選択
      This data presents high-level way of mapping individual countries in terms of talent competitiveness consists of comparing their GTCI scores to their GDP per capita for the selected indicators.In its first year, the GTCI model covers 103 countries,representing 86.3% of the world’s population and 96.7% of the world’s GDP (in current US dollars).It is a simplified manner of acquiring a first assessment about the ways in which competitiveness relates to overall level of economic development of a nation.
    • 11月 2019
      ソース: International Monetary Fund
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      This dataset provides a comprehensive view of the functions, or socioeconomic objectives, that government aims to achieve through various kinds of expenditure, comprising detailed classifications of general public service, defense, public order and safety, economic affairs, environment protection, housing and community services, health, recreation, culture and religion, education, and social protection services.
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_mo_gr4 The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      This dataset contains the number of people who graduated from an education programme by field and sex.
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 02 7月, 2019
      データセットを選択
      Graduates are those who successfully complete an educational programme during the reference year of the data collection. One condition of a successful completion is that students should have enrolled in, and successfully completed, the final year of the corresponding educational programme, although not necessarily in the year of reference. Students who do not complete the final year of an educational programme, but later successfully complete a recognised "equivalency" examination based on knowledge learned outside of the education system, should not be counted as graduates. Successful completion is defined according to the graduation requirements established by each country: in some countries, completion occurs as a result of passing a final, curriculum-based examination or series of examinations. In other countries, completion occurs after a specific number of teaching hours has been accumulated (although completion of some or all of the course hours may also involve examinations).
    • 11月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 28 11月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national and international (Eurostat and OECD) official sources. Definition: Graduates from an ISCED level are individuals who entered and successfully completed an education programme which is classified as ‘level completion’. A new version of the International Standard Classification of Education (ISCED 2011) was adopted in 2011 by experts on Education Statistics. According to ISCED-11, the graduates refer to those who successfully completed levels 6, 7 or 8 of tertiary education. Programmes at ISCED-11 level 6, or Bachelor’s or equivalent level, are often designed to provide participants with intermediate academic and/or professional knowledge, skills and competencies, leading to a first university degree or equivalent qualification. Programmes at ISCED-11 level 7, or Master’s or equivalent level, provide participants with advanced academic and/or professional knowledge, skills and competencies, leading to a second degree or equivalent qualification. Such programmes may have a substantial research component but do not yet lead to the award of an advanced research qualification. Level 8 in ISCED-11, or doctoral or equivalent level, is reserved for tertiary programmes leading to the award of an advanced research qualification. According to ISCED-97 (previously in use), the ‘level completion’ programmes include levels 5A and 6. ISCED-97 level 5A corresponds to tertiary programmes that are largely theoretically based and are intended to provide sufficient qualifications for gaining entry into advanced research programmes and professions with high skill requirements. However, these programmes do not necessary distinguish between a first and second academic degree. Level 6 in ISCED-97 corresponds to level 8 in ISCED-11. For most countries the data on graduates in this table are shown according to ISCED-97 up to 2012 and according to ISCED-11 from 2013. However, for some countries the data were recalculated by the National Statistical Organizations according to ISCED-11 for earlier periods and provided both for ISCED-11 and ISCED-97 . In these particular cases, the sum of graduates at ISCED-11 levels 6 and 7 equals graduates at ISCED-97 level 5A, and, to avoid duplication, the data for every year are shown according to ISCED-11 only. Differences between ISCED-11 and ISCED-97 may affect time series data for some countries and result in breaks in series. With some exceptions, data on graduates refer to the calendar year. General note:The joint UOE (UNESCO-UIS, OECD, EUROSTAT) 2005 data collection on graduates by fields of education and training was changed to include graduates who were awarded more than one degree in different fields (not within the same field). In previous years, these graduates were reported only once and pro-rated over the fields. This change affected data in very few countries as multiple graduations in different fields for the same reference year are negligible in most countries. .. - data not available Country: Albania Advanced research programmes do not exist. Country: Armenia The transition to ISCED-2011 is from 2013-2014 school year. From 2012 backwards, the data have been recalculated by the NSO based on ISCED-2011. Country: Bulgaria Break in methodlogy (2000): Since 1997 the three-cycle degree structure (bachelor ? master ? doctoral) has been adopted following the Bologna process (due to changes in the national legislation) Country: Bulgaria Break in methodlogy (2007): The programs for training of medical nurses and maternity nurses have completed with qualification degree & 39;Bachelor& 39; since 2007 (due to changes in the national legislation). Medical nurses and maternity nurses education has moved from ISCED 5B to ISCED 5A since 2006. Country: Canada Reference period (1995 - 2013): Data refer to calendar year. e.g. data for graduates 2004-2005 refer to calendar year 2005. Country: Croatia Data refer to calendar year. Country: Cyprus Data cover only government controlled area. Country: Czechia 1980, 1990, 1995: data refer to graduates of full-time attendance only. Country: Estonia Up to 1990: advanced research programmes were not included in regular education. Country: Georgia Break in methodlogy (2010): Change in source Country: Georgia Territorial change (1980 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Germany 1980-1995: data refer to ISCED 1976 classification. 1980-1990: data refer to the former Federal Republic of Germany. From 1995: data refer to the territory of Germany after reunification. Country: Hungary Change in definition (1980 - 2000): data refer to ISCED 1976 classification Country: Iceland 2001-2005: data refer to calender year. Country: Kyrgyzstan Change in definition (1995 - onwards): Data refer to state and non-state educational institutions. Country: Kyrgyzstan Reference period (2000 - 2012): Data refer to the beginning of academic year. Country: Kyrgyzstan Reference period (2013): Since 2013 data refer to the end of an academic year. Country: Latvia 1990, 1995: data refer to ISCED 1976 classification. Country: Lithuania Data refer to calendar year. Country: Luxembourg Data refer to population aged 25-64. Country: Moldova, Republic of As of 2005/2006 school year, higher education, except medical and pharmaceutical, is carried out in two cycles (Licentiate and Master‘s). Students downcast to 2005/2006 academic year completed training on the rules according to the Bologna Declaration. In number of the graduates at the level 5A in 2008 includes those who received a diploma of higher education (before the adoption of the Bologna Declaration) and licentiate degree, and in 2010 and those who got master‘s diploma. Before 2009 data excluded foreigners. From 2012/2013 data are classified according to ISCED-2011. Country: Moldova, Republic of Data exclude the territory of the Transnistria and municipality of Bender Country: Romania Data are not available for advanced research programmes. Country: Serbia The Statistical Office of the Republic of Serbia has no available data on the AP Kosovo and Metohija. Country: Slovakia 1995: data do not refer to ISCED 1997 classification. Country: Slovenia Data refer to calendar year. Country: Spain 2005: Provisional data Country: Sweden 1995: data refer to ISCED 1976 classification. Country: Switzerland Break in methodlogy (2005): Break in series due to the growth in some fields of studies for women such as teacher training or health in Universities of Applied Sciences. Country: Switzerland Reference period (1995): Data refer to 1997 Country: Tajikistan Reference period (2000 - 2013): Data for advanced research programmes refer to end of year. Data for theoretical oriented programmes refer to June-July of reporting year. Country: Turkey Change in definition (1990 onwards): Data for theoretical oriented programmes include open education graduates. Data for advanced research programmes include medical interns and doctorate students. Country: Turkey Reference period (1990 onwards): Data refer to end of year. Country: Ukraine From 2014 data cover the territories under the government control. Country: Ukraine Data with year T in the headings refers to the beginning of the school year T/T+1. Transition from ISCED-1997 to ISCED-2011 since the school year 2012/2013.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      Graduation/entry rates represent an estimated percentage of an age group expected to graduate/enter a certain level of education at least once in their lifetime.
  • H
    • 11月 2017
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Headcount enrolments in public school Aboriginal language programs, last five school years.
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 16 4月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national official sources Definition: A university is an institution of higher education providing facilities for learning (and usually research) and authorised to grant academic degrees. Their main focus should be on ISCED 1997 level 5A or ISCED 2011 levels 6 and 7 programmes. .. - data not available Country: Albania Change in definition (2012): Data refers to personel only in public University Country: Cyprus Reference period (2008): data refer to 2009 Country: Cyprus Territorial change (1990 onward): Government controlled area only. Country: Denmark Reference period (2011): Data refer to January 2012. Country: Georgia Change in definition (2000 onward): Data refer to institutions accredited by the Ministry of Education and Science. Country: Georgia Territorial change (2000 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Latvia Reference period (2008): Data refer to 2009. Country: Moldova, Republic of Additional information (1995 onward): Data exclude the territory of the Transnistria and municipality of Bender Country: Portugal Additional information (2013): The changes relate to the merger of two public universities located in Lisbon, thus passing from 16 to 15 members. Country: Slovakia 2015 data refer to 20 November 2015. Country: Slovenia Break in methodology (2012): The number includes heads of all public and private higher education institutions. Country: Spain Break in methodlogy (2013): The data are provided to the Women& 39;s Institute in 2014 by the Rector& 39;s Conference of the Spanish Universities Country: Switzerland Break in methodlogy (2008): Data before 2008 refers to universityies only . As of 2008 data include universities and universities of applied sciences that cover the entire ISCED-97, level 5A/ISCED-11, level 7.
    • 9月 2019
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 25 9月, 2019
      データセットを選択
      Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.
  • I
    • 9月 2015
      ソース: Pearson
      アップロード者: Knoema
      以下でアクセス: 15 10月, 2015
      データセットを選択
      The Global Index of Cognitive Skills and Educational Attainment compares the performance of 39 countries and one region (Hong Kong) on two categories of education: Cognitive Skills and Educational Attainment. The Index provides a snapshot of the relative performance of countries based on their education outputs.List of indicators   Main sourceMain year1. Cognitive Skills  1.1  Grade 8  1.1.1  Reading Literacy - PISAOECD - PISA report20091.1.2  Mathematics Literacy - PISA and TIMSSEIU based on IEA and OECD data 1.1.2.1  PISA - Mathematics LiteracyOECD - PISA report20091.1.2.2  TIMSS - Mathematics AchievementIEA - TIMSS and PIRLS International Study Center20071.1.3  Science Literacy - PISA and TIMSSEIU based on IEA and OECD data 1.1.3.1  PISA - Science LiteracyOECD - PISA report20091.1.3.2  TIMSS - Science  AchievementIEA - TIMSS and PIRLS International Study Center20071.2  Grade 4  1.2.1  PIRLS - Reading Literacy AchievementIEA - TIMSS and PIRLS International Study Center20061.2.2  TIMSS - Mathematics  AchievementIEA - TIMSS and PIRLS International Study Center20071.2.3  TIMSS - Science  AchievementIEA - TIMSS and PIRLS International Study Center20072. Educational Attainment  2.1  Literacy rate  2.1.1  Literacy rate (15 and over), %UNESCO Institute for Statistics (UIS)20102.2  Graduation rate  2.2.1  Graduation rate at upper secondary level OECD 20102.2.2  Graduation rate at tertiary level OECD 2010
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 18 10月, 2019
      データセットを選択
      This dataset presents internationally comparable data on instruction time in full-time compulsory education. It covers primary and (lower and upper) secondary general education, but excludes pre-primary education, even if compulsory. Total number of instruction hours and the distribution of hours per subject is available either by level of education or by age.
    • 6月 2018
      ソース: Barro-Lee
      アップロード者: Knoema
      以下でアクセス: 12 12月, 2018
      データセットを選択
      Data cited at: Barro-Lee   The Barro-Lee Data set (2010) extends their previous estimates from 1950 to 2010, and provide more, improved data disaggregated by sex and and by 5-year age intervals. It provides educational attainment data for 146 countries in 5-year intervals from 1950 to 2010 as well as information about the distribution of educational attainment of the adult population over age 15 and over age 25 by sex at seven levels of schooling. Average years of schooling at all levels are also measured for each country and for regions in the world. Note: Cited at Barro, Robert and Jong-Wha Lee, April 2010, "A New Data Set of Educational Attainment in the World, 1950-2010." NBER Working Paper No. 15902
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      International graduate tuition fees are weighted averages by field of study for full-time graduate students, annual (dollars). Data is collected from publicly funded, Canadian degree-granting institutions.
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 14 7月, 2019
      データセットを選択
      This dataset contains the number of people who graduated from an education programme by country of origin and sex.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 16 4月, 2019
      データセットを選択
      This indicator reports the percentage of students of each country of origin over the total of international students.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      International undergraduate tuition fees are weighted averages by field of study for full-time foreign students, annual (dollars). Data is collected from publicly funded, Canadian degree-granting institutions.
  • L
  • M
    • 3月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Full-time male educators as a percentage of total full-time educators and part-time male educators as a percentage of total part-time educators, in public elementary and secondary schools, Canada and provinces. This table is included in Section C: Elementary-secondary education: Elementary-secondary school: enrolments and educators of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 3月 2019
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 20 3月, 2019
      データセットを選択
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Millennium Development Goals Publication: https://datacatalog.worldbank.org/dataset/millennium-development-goals License: http://creativecommons.org/licenses/by/4.0/   Relevant indicators drawn from the World Development Indicators, reorganized according to the goals and targets of the Millennium Development Goals (MDGs). The MDGs focus the efforts of the world community on achieving significant, measurable improvements in people's lives by the year 2015: they establish targets and yardsticks for measuring development results. Gender Parity Index (GPI)= Value of indicator for Girls/ Value of indicator for Boys. For e.g GPI=School enrolment for Girls/School enrolment for Boys. A value of less than one indicates differences in favor of boys, whereas a value near one (1) indicates that parity has been more or less achieved. The greater the deviation from 1 greater the disparity is.
  • N
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 08 10月, 2019
      データセットを選択
      It provides a breakdown of government expenditure according to their function. To meet this end, economic flows of expenditure must be aggregated according to the Classification of the Functions of Government (COFOG).
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Number and percentage distribution of registered apprentices by age group. This table is included in Section D: Postsecondary education: Enrolment in postsecondary education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Number and percentage distribution of registered apprentices, by sex and major trade groups. This table is included in Section D: Postsecondary education: Enrolment in postsecondary education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Number and percentage distribution of registered apprentice completions, by major trade group and sex, Canada. This table is included in Section D: Postsecondary education: Postsecondary completions and graduation rates of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 12月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Number of apprenticeship program registrations in the top eleven Red Seal trades in 2014 by age group, sex and registration status, Canada, provinces and territories.
    • 12月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Count of the all apprenticeship registrations, for Canada, provinces and territories by gender, registration status and major trade group for the most recent five years OR data is available historically since 1991.
    • 12月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Count of all certificates by age groups, sex, major trade groups, apprentice or trade qualifier indicator, red seal or non-red seal indicator for Canada, provinces and territories for the most recent five years OR data is available historically since 1991.
    • 12月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Count of the all apprenticeship completions, for Canada, provinces and territories by major trade group, age group, registration status and gender for the most recent five years OR data is available historically since 1991.
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The number of full-time and part-time educators in public elementary and secondary schools, by age group and sex, last five school years.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      This dataset contains the number of people who graduated from an education programme by age and sex.
    • 10月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 06 11月, 2019
      データセットを選択
    • 10月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 25 10月, 2019
      データセットを選択
      The number of students in regular programs for youth, public elementary and secondary schools, by age and sex, last five school years.
  • O
    • 6月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 04 6月, 2019
      データセットを選択
      The OECD Science, Technology and Industry Outlook reviews key trends in STI policies and performance in OECD countries and major emerging economies. It is published every two years and draws on a unique international policy survey conducted by the OECD - with more than 45 countries involved in 2014 - and the latest OECD work on STI policy analysis and measurement. Following an overview of the recent STI global landscape, key current policy issues are discussed across a series of thematic policy profiles. Country profiles report the STI performance of individual countries and the most recent national policy developments.
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 02 7月, 2019
      データセットを選択
      This table contains statistics on research and development (R&D) expenditure performed in the higher education and private non-profit sectors by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities) and type of costs (current expenditures, capital expenditures).
  • P
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Participation rate in education, population aged 15 to 29, by age group and type of institution attended, Canada, provinces and territories. This table is included in Section E: Transitions and outcomes: Transitions to postsecondary education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Participation rate in education, population aged 18 to 34, by age group and type of institution attended, Canada, provinces and territories. This table is included in Section E: Transitions and outcomes: Transitions to postsecondary education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Percentage of the population aged 0 to 24 in low income, by age group and type of living arrangement. This table is included in Section A: A portrait of the school-age population: Low income of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Postsecondary enrolments, by program type, credential type and International Standard Classification of Education (ISCED), annual.
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The number of enrolments by geography, institution type, registration status for age groups for 5 years (2008-2009 to 2012-2013).
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2019
      データセットを選択
      The number of enrolments by geography, institution type, registration status for CIP Primary Groupings (CIP_PG).
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 12 3月, 2019
      データセットを選択
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 12 3月, 2019
      データセットを選択
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 08 5月, 2019
      データセットを選択
      The number of postsecondary graduates, by International Standard Classification of Education (ISCED), program type, credential type and institution type.
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The number of graduates by geography, institution type, for age groups.
    • 11月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2019
      データセットを選択
      The number of graduates by geography and institution type for CIP Primary Groupings (CIP_PG).
    • 10月 2014
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Presents the proportion of children 0 to 17 years old with postsecondary savings by province.
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_fi_ffun The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      Distribution of graduates/new entrants by gender, country of origin and age as well as the proportion of each tertiary educational level over the total of first-time graduates and new entrants at tertiary level.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2019
      データセットを選択
    • 3月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 28 4月, 2019
      データセットを選択
      Proportion of students, aged 15 to 29, who were also working, by age group and type of institution attended, Canada and provinces. This table is included in Section E: Transitions and outcomes: Transitions to the labour market of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Provincial estimates of research and development expenditures in the higher education sector, by funding sector and type of science by provinces, from 2000 to today.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2019
      データセットを選択
      Financial information of public and private elementary and secondary education expenditures, by direct source of funds and geography.
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_fi_fgdp The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 06 7月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_fi_faid The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening accesseduc_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age   B. Study frameworkeduc_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education   C. Student and staff mobilityeduc_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country)   D. Effective outcomes and employabilityeduc_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A     The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities:Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
  • Q
  • R
    • 3月 2010
      ソース: International Institute for Applied Systems Analysis
      アップロード者: Knoema
      以下でアクセス: 31 10月, 2013
      データセットを選択
      Using demographic multi-state, cohort-component methods, projections for 120 countries (covering 93% of the world population in 2005) by five-year age groups, sex, and four levels of educational attainment for the years 2005-2050 are produced. Taking into account differentials in fertility and mortality by education level, the first systematic global educational attainment projections according to four widely differing education scenarios are presented. The results show the possible range of future educational attainment trends around the world, thereby contributing to long-term economic and social planning at the national and international levels, and to the assessment of the feasibility of international education goals. Samir KC et al., Projection of populations by level of educational attainment, age, and sex for 120 countries for 2005-2050, Demographic Research, 22(15), P. 383-472, 16 March 2010: http://www.demographic-research.org/Volumes/Vol22/15/.
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 14 7月, 2019
      データセットを選択
    • 12月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Financial information of community colleges and vocational schools, type of revenues by geography and type of fund.
    • 7月 2018
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 2月, 2019
      データセットを選択
      Financial information of universities and degree-granting colleges, revenues by geography, type of university or college and type of funds.
  • S
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Financial information of school board expenditures, by geography, function and classification.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Financial information of school board expenditures, by geography.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Financial information of school boards, by geography and direct source of funds.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Distribution of the school-age population, by age group and living arrangements, Canada and jurisdictions. This table is included in Section A: A portrait of the school-age population: Family Background of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Distribution of the school-age population (ages 5 to 24), by age group and by work activity of parents, Canada and jurisdictions. This table is included inSection A: A portrait of the school-age population: Family Background of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 20 9月, 2019
      データセットを選択
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 20 9月, 2019
      データセットを選択
    • 8月 2019
      ソース: Scimago Institutions Rankings
      アップロード者: Knoema
      以下でアクセス: 21 10月, 2019
      データセットを選択
      Restrictions apply: https://www.scimagojr.com/aboutus.php   Citation: SCImago, (n.d.). SJR — SCImago Journal & Country Rank [Portal]. Retrieved Date you Retrieve, from http://www.scimagojr.com   SCImago Journal Rank: It expresses the average number of weighted citations received in the selected year by the documents published in the selected journal in the three previous years, --i.e. weighted citations received in year X to documents published in the journal in years X-1, X-2 and X-3. H Index: The h index expresses the journal's number of articles (h) that have received at least h citations. It quantifies both journal scientific productivity and scientific impact and it is also applicable to scientists, countries, etc. Total Documents: Output of the selected period. All types of documents are considered, including citable and non citable documents. Total Cites (3years): Number of citations received in the seleted year by a journal to the documents published in the three previous years, --i.e. citations received in year X to documents published in years X-1, X-2 and X-3. All types of documents are considered. Self Cites: Number of journal's self-citations in the selected year to its own documents published in the three previous years, --i.e. self-citations in year X to documents published in years X-1, X-2 and X-3. All types of documents are considered. Cited Documents: Number of documents cited at least once in the three previous years, --i.e. years X-1, X-2 and X-3 Cites per Document (2 years): Average citations per document in a 2 year period. It is computed considering the number of citations received by a journal in the current year to the documents published in the two previous years, --i.e. citations received in year X to documents published in years X-1 and X-2.
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      The percentage of students enrolled in each type of institution over the total of students.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      This indicator shows the percentage of international students in each field of education.
    • 9月 2019
      ソース: Social Progress Imperative
      アップロード者: Knoema
      以下でアクセス: 14 10月, 2019
      データセットを選択
        Data cited at: Social Progress Index https://www.socialprogress.org/download The Social Progress Index is a new way to define the success of our societies. It is a comprehensive measure of real quality of life, independent of economic indicators. The Social Progress Index is designed to complement, rather than replace, economic measures such as GDP. Each year, Social Progress Imperative conducts a comprehensive review of all indicators included in the Social Progress Index framework to check data updates (which frequently include retroactive revisions) and whether new indicators have been published that are well-suited to describing social progress concepts. Such a review necessitates a recalculation of previously published versions of the Social Progress Index, as any removal or additions of indicators to the framework or changes due to retroactive revisions in data from the original data sources prevent comparability between previously published versions of the Social Progress Index and the 2019 Social Progress Index. Therefore, using the 2019 Social Progress Index framework and methodology, we provide comparable historical data for additional five years of the Social Progress Index, from 2014 to 2018.
    • 12月 2015
      ソース: Office of National Statistics, Mauritania
      アップロード者: Knoema
      以下でアクセス: 11 1月, 2019
      データセットを選択
      Data cited at: https://mauritania.opendataforafrica.org/MRSCD2015
    • 1月 2016
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2018
      データセットを選択
      Sources of funds for expenditures on research and development (R&D) in the higher education sector, in dollars and as a percentage of total funding, Canada and provinces. This table is included in Section D: Postsecondary education: Research and Development of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_ac_el1t The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      Eurostat Dataset Id:educ_bo_mo_el8o The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • 9月 2014
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2014
      データセットを選択
      For data aligned to Finance, the year shown is the calendar year. For data aligned to personnel, the year shown is the year in which the end of the school year falls (e.g. 2002 refers to the school year 2001/2002), with the exceptions of Korea where the year refers to the year in which the school year begins and Australia and New Zealand where the school academic year corresponds to the calendar year.
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 15 10月, 2019
      データセットを選択
      Student-teacher ratio refers to the average number of students per teacher, while average class size is the average number of students in a classroom.
    • 6月 2019
      ソース: Sustainable Development Solutions Network
      アップロード者: Knoema
      以下でアクセス: 09 7月, 2019
      データセットを選択
      Data Cited at - Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., Fuller, G. (2019): Sustainable Development Report 2019. New York: Bertelsmann Stiftung and Sustainable Development Solutions Network (SDSN). The 2019 SDG Index and Dashboards report presents a revised and updated assessment of countries’ distance to achieving the Sustainable Development Goals (SDGs). It includes detailed SDG Dashboards to help identify implementation priorities for the SDGs. The report also provides a ranking of countries by the aggregate SDG Index of overall performance.
  • T
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 02 7月, 2019
      データセットを選択
      TALIS averages are based on all countries participating in the TALIS survey, including partner countries and economies. This explains the difference between the OECD average and the TALIS average. Data from the TALIS survey and Education at a Glance (EAG) may differ. See Annex E of the TALIS technical report and Annex 3 of EAG for more details about the data collections.
    • 11月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 28 11月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national and international (Eurostat and UNESCO Institute for Statistics) official sources. Definition:Teaching professionals teach the theory and practice of one or more disciplines at different educational levels, conduct research and improve or develop concepts, theories and operational methods pertaining to their particular discipline, and prepare scholarly papers and books. The number of teachers is disaggregated according to education levels of enrolment. From the academic year 2012-2013, for most countries in this table education levels are classified using the ISCED 2011 (previously ISCED 1997). Primary education corresponds to ISCED 2011 level 1, secondary education corresponds to levels 2, 3 and 4 and tertiary education corresponds to levels 5-8. In ISCED 2011 some programmes are classified at different levels than before. Such differences may affect time series data for some countries. For correspondance between ISCED 1997 and ISCED 2011 see here. .. - data not available Country: Albania Change in definition (1980 - 2008): Before 2007-2008, data on teachers in primary education refer to primary and lower secondary education and data on teachers in secondary education refer to teachers in upper secondary education only. Country: Armenia 2000: break in series; data include both public and private schools. Transition to ISCED-2011 is from the school year 2013-2014. Country: Bosnia and Herzegovina Break in series (2012): Until the school year 2011/2012 data on primary education include ISCED levels 1 and 2. Data on secondary education refer to ISCED level 3. Since the school year 2012/2013 data for primary education include only ISCED level 1, and data on secondary education include ISCED levels 2 and 3. Country: Bosnia and Herzegovina Reference period (2011/2012 backwards): Data refers to the end of the school year. Country: Bosnia and Herzegovina Reference period (2012/2013 onward): Data on teachers in primary and secondary education refer to the beginning of the school year. Country: Canada Change in definition (1990 - onwards): Data for secondary level include primary level. Data for post secondary non-tertiary education (ISCED 4 level) may include tertiary education. Groupings refer to NOC-S 2001 classification. Country: Canada Reference period (1990 - 2012): Data are averages of monthly data over the period September to April. i.e. September 2008 to April 2009 for 2008/2009. Country: Croatia Teachers teaching in both primary and secondary art schools are double counted. Teachers teaching in several schools (grammar schools, technical and industrial schools) are counted more than once. 2000/2001: data are not available by sex. Country: Cyprus Data cover only government controlled area. Country: Finland 1995/1996: data for primary level include secondary level. Country: Georgia Territorial change (1990 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Germany Before 1990/1991: data refer to the former territory of the Federal Republic of Germany. From 1995/1996: data refer to the territory of Germany after reunification. Country: Hungary 1980/1981, 1990/1991, 1995/1996: data for primary level include levels 1 and 2; data for secondary level include level 3 of ISCED 1997 classification. Country: Iceland 1980/1981-2009/2010: data for primary level include secondary level. 1995/1996-2009-2010: data for secondary level includes only upper secondary level. Country: Italy Teachers, secondary education: teachers at ISCED level 2 and 3 are included. Data at ISCED level 4 are ''missing''.From 2004-2005 to 2011-2012 at ISCED levels 1, 2 and 3 only public schools are included.Data are classified according to ISCED-11 since 2012-2013.Teachers, tertiary education: teachers at ISCED-11 level 6, 7, and 8 are included. Data at ISCED-11 level 5 are ''not applicable''. Country: Montenegro Change in definition (2000 - 2012): Data for primary level include levels 1 and 2, data for secondary level include level 3 of ISCED 1997 classification. Country: Norway 2000/2001: data for secondary level include primary level. Country: Poland 1980/1981-1995/1996: data include full-time teachers. From 2000/2001: data include full-time equivalents. 2003/2004: data for levels 1-4 and 5B (practically oriented tertiary programmes) are not available. 2004/2005: data are incomplete. Country: Portugal Data from school year 2012-2013 onwards are compiled using ISCED-11. Considering the data aggregation proposed there is no break in series to consider. Data include only those with teaching responsabilities at school (excludes personnel with administrative/management/research functions only). Country: Russian Federation Break in methodlogy (2008): As of 2008/09 school year, the total number of teachers in secondary education include teachers of educational institutions in primary special education (ISCED 4) Country: Russian Federation Break in methodlogy (2009): From the 2009/10 academic year, the total number of teachers at primary and secondary education does not include officials at managerial positions. Country: Serbia Break in methodlogy (2007 - 2012): As of 2006/07 data for primary level does not include teachers in lower- secondary education Country: Serbia Change in definition (1980 - 1990): Data for primary level include levels 1 and 2, data for secondary level include level 3 of ISCED 1997 classification, level 4 do not exist 1980/1981, 1990/1991: data for secondary level include teachers of schools for special and adult education. 1980/81-2006/07:data for primary level include teachers in lower- secondary education Country: Serbia Change in definition (1995 - 2001): Data for primary level include levels 1 and 2, data for secondary level include level 3 of ISCED 1997 classification, level 4 do not exist 1995/1996 - 2000/2001: data for secondary level include teachers of schools for special education. 1980/81-2006/07:data for primary level include teachers in lower- secondary education Country: Serbia Change in definition (2002 - 2007): Data for primary level include levels 1 and 2, data for secondary level include level 3 of ISCED 1997 classification, level 4 do not exist 1980/81-2006/07:data for primary level include teachers in lower- secondary education Country: Serbia Change in definition (2008 - 2012): Data for primary level include levels 1 and 2, data for secondary level include level 3 of ISCED 1997 classification, level 4 do not exist Country: Serbia Territorial change (1995 - 2012): The Statistical Office of the Republic of Serbia has no available data on the AP Kosovo and Metohija. Country: Slovenia 1980/1981 - 1995/1996: data for primary level include levels 1 and 2; data for secondary level include levels 3 and 4 of ISCED 1997 classification. Country: Spain The category of ''level of education not stated'' includes the ISCED 0 teachers Country: Ukraine Data prior to 2012-2013 use ISCED 1997 classification.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      This dataset presents internationally comparable data on (full-time) salaries of teachers and school heads in public institutions at pre-primary, primary and general (lower and upper) secondary education. Statutory salaries are displayed by level of education, Data also include other statistics related to salaries of teachers.
    • 10月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 15 10月, 2019
      データセットを選択
      This dataset presents internationally comparable data on teaching and working time of (full-time) teachers in public institutions at pre-primary, primary and general and vocational (lower and upper) secondary education. Data refer to formal statutory requirements and also cover actual teaching time. Teaching and working time are displayed by level of education.
    • 11月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 28 11月, 2019
      データセットを選択
      .. - data not available Source: UNECE Statistical Database, compiled from national and international (Eurostat and UNESCO Institute for Statistics) official sources. Definition: Tertiary students are those enrolled in levels 5-8 of the ISCED 2011 (previously in levels 5A, 5B and 6 of the ISCED 1997) for the academic year concerned. Levels 5, 6, 7 in ISCED 2011 together correspond to level 5 in ISCED 1997. ISCED 2011 level 5, or short-cycle tertiary education, corresponds to ISCED 1997 level 5B and captures the lowest level of tertiary education. Programmes at this level are practically based, occupationally specific and are mainly designed for participants to acquire practical skills. Programmes at ISCED 2011 level 6, or Bachelor’s or equivalent, are often designed to provide participants with intermediate academic and/or professional knowledge, skills and competencies, leading to a first degree or equivalent qualification. Programmes at ISCED 2011 level 7, or Master’s or equivalent, are designed to provide participants with advanced academic and/or professional knowledge, skills and competencies, leading to a second degree or equivalent qualification. They may have a substantial research component but do not yet lead to the award of a doctoral qualification. Programmes at ISCED 1997 level 5A are largely theoretically based and intended to provide sufficient qualifications for gaining entry into advanced research programmes and professions with high skill requirements, but do not necessarily distinguish between a first and second university degree. ISCED2011 level 8, or doctoral or equivalent, is reserved for tertiary programmes leading to the award of an advanced research qualification and corresponds to ISCED 1997 level 6. Fields of study are given based on ISCED 1997. Measurement: Students , Country: Armenia Since the school year 2013-2014, the data have been compiled according ISCED 2011. Measurement: Percent of total for both sexes , Country: Armenia Since the school year 2013-2014, the data have been compiled according ISCED 2011. Measurement: Percent of total for all fields of study , Country: Armenia Since the school year 2013-2014, the data have been compiled according ISCED 2011. Country: Croatia 2000, 2001: data for level 6 of ISCED 1997 classification are not available. 2004: break in series; due to change of reference period from calendar year to academic year. i.e. 2004 data for ISCED 6 cover January 2004 to August 2005. Country: Cyprus Data cover only government controlled area. Country: Germany Data for level 6 of ISCED 1997 classification are not available. Country: Moldova, Republic of Change in definition (2000 - 2012): For level 5B data includes programs of secondary special education (colleges). Data exclude foreigners Country: Moldova, Republic of Reference period (2000 - 2012): For levels 5A and 5B - data refer to the beginning of the of the school year, and for level 6 - data refer to the calendar year. Country: Moldova, Republic of Territorial change (2000 onward): Data exclude the territory of the Transnistria and municipality of Bender Measurement: Students , Country: Ukraine From 2014 data cover the territories under the government control. Measurement: Percent of total for both sexes , Country: Ukraine From 2014 data cover the territories under the government control. Measurement: Percent of total for all fields of study , Country: Ukraine From 2014 data cover the territories under the government control. Country: Ukraine Data prior to 2012-2013 use ISCED 1997 classification. Country: Uzbekistan 2000-2005: data do not include doctoral degree candidates.
    • 11月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 28 11月, 2019
      データセットを選択
      .. - data not available Source: UNECE Statistical Database, compiled from national and international (Eurostat and UNESCO Institute for Statistics) official sources. Definition: Tertiary students are those enrolled in levels 5-8 of the ISCED 2011. ISCED-F 2013 is a classification of fields of education and training which accompanies ISCED 2011.
    • 11月 2015
      ソース: Save the Children Federation
      アップロード者: Knoema
      以下でアクセス: 07 12月, 2015
      データセットを選択
    • 6月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 05 6月, 2019
      データセットを選択
      Chapter D includes indicators on instruction time, teachers’ working time and teachers’ salaries that not only represent policy levers that can be manipulated, but that also provide context for the quality of instruction and the outcomes of individual learners. It also presents data on the profile of teachers, the levels of government at which decisions concerning education systems are taken, and pathways and gateways to gain access to secondary and tertiary education.
    • 6月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 05 6月, 2019
      データセットを選択
      Indicators in Chapter A refer to education and learning outputs and outcomes. They describe educational attainment of different generations, measure the outputs of the education system, and provide context for education policies, including those on lifelong learning.
    • 12月 2015
      ソース: United Nations Statistics Division
      アップロード者: Sandeep Reddy
      以下でアクセス: 19 8月, 2017
      データセットを選択
      Data cited at: United Nations Statistics Division https://unstats.un.org/home/ Publication: https://unstats.un.org/unsd/gender/worldswomen.html License: https://creativecommons.org/licenses/by-nc/4.0/   The World’s Women 2015 comprises eight chapters covering critical areas of policy concern: population and families, health, education, work, power and decision-making, violence against women, environment, and poverty. In each area, a life-cycle approach is introduced to reveal the experiences of women and men during different periods of life—from childhood and the formative years, through the working and reproductive stages, to older ages. The statistics and analyses presented in the following pages are based on a comprehensive and careful assessment of a large set of available data from international and national statistical agencies. Each chapter provides an assessment of gaps in gender statistics, highlighting progress in the availability of statistics, new and emerging methodological developments, and areas demanding further attention from the international community
  • U
    • 9月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      This table contains 791 series, with data for years 2016/2017 - 2017/2018 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (68 items: Canada; Newfoundland and Labrador; St. John's; Prince Edward Island; ...) Field of study (19 items: Total field of study; Education; Visual and performing arts, and communications technologies; Humanities; ...).
    • 10月 2014
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 16 6月, 2016
      データセットを選択
    • 2月 2019
      ソース: UNESCO Institute for Statistics
      アップロード者: Knoema
      以下でアクセス: 05 9月, 2019
      データセットを選択
    • 11月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 28 11月, 2019
      データセットを選択
      .. - data not available Source: UNECE Statistical Database, compiled from national and international (Eurostat and UNESCO Institute for Statistics) official sources. Definition: Upper and post- secondary levels correspond to levels 3 and 4 of ISCED 2011 classification (and mainly to levels 3 and 4 of ISCED 1997 used previously). Tertiary level is not included. Upper secondary education (level 3) typically begins at the end of full-time compulsory education for those countries that have a system of compulsory education. The entrance age to this level is typically between ages 14 and 16 years. Post secondary education (level 4) captures programmes that are typically designed to provide individuals who completed ISCED level 3 with non-tertiary qualifications required for progression to tertiary education or for employment when their ISCED level 3 qualification does not grant such access. Level 4 programmes can, considering their content, not be regarded as tertiary programmes. They are often not significantly more advanced than programmes at level 3 but they serve to broaden the knowledge of participants who have already completed a programme at level 3. Country: Albania Up to 2011-2012 data refer to ISCED level 3. Country: Armenia Data refer to ISCED level 3. From 1995 onwards the data include pupils in private schools. Since the school year 2013-2014 the data have been compiled according to ISCED-2011. Country: Austria Up to 1990-1991: data refer to ISCED 1976 classification. 1980-1981, 1990-1991 and 1995-1996: data refer to 1979-1980, 1989-1990 and 1994-1995. Country: Bosnia and Herzegovina Data refer to ISCED level 3 Country: Canada Data refer to ISCED level 3 Country: Croatia Data refer to ISCED level 3. Country: Cyprus Up to 2012-2013 data refer to ISCED level 3. Data cover only government controlled area. Country: Finland 1990-1991: data refer to ISCED 1976 classification. Country: Germany Up to 1995-1996: data refer to ISCED 1976 classification. Country: Hungary 2000: data refer to 1999-2000. Country: Iceland Up to 1995-1996: data refer to level 3 of ISCED 1976 classification. Country: Ireland Up to 1995-1996: data refer to level 3 of ISCED 1997 classification. Country: Israel 2000-2001: data exclude pupils in schools related to the Ministry of Religious Affairs. Country: Italy 1980-1981, 1990-1991 and 1995-1996: data refer to 1979-1980, 1989-1990 and 1994-1995. Country: Latvia Up to 1995-96: data refer to level 3 of ISCED 1976 classification. Country: Moldova, Republic of Territorial change (1995 - 2012): Data exclude the territory of the Transnistria and municipality of Bender Country: Montenegro Data refer to ISCED level 3. Country: Spain Data refer to ISCED level 3. 2000-2001: data refer to 1999-2000. Country: Sweden 1990-1991: data refer to level 3 of ISCED 1976 classification. Data include adults enrolled in upper and post secondary level classes. Country: Tajikistan Data refer to ISCED level 3 Country: Turkey Up to 1995-1996: data refer to ISCED 1976 classification. Country: Ukraine 2012-2013, 2013-2014: data refer to ISCED level 3 Country: United Kingdom 2006: Break in series; data include only students participating in courses equal to or longer than a semester. From 2010 onwards data refer to ISCED level 3. Country: Uzbekistan Data refer to ISCED level 3

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