Dataset

This dataset was created by Zergham Warraich

Contents

The average for 2021 based on 41 countries was 111.6 index points. The highest value was in Luxembourg: 422.59 index points and the lowest value was in Turkey: 10.85 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

Iceland had the highest inequality-adjusted education index score worldwide, amounting to **** out of one on the index. Germany followed with an index score of ****. The inequality-adjusted education index is the education index in the Human Development Index adjusted for inequality.

The Times Higher Education Latin America University Rankings is based on the same 13 rigorous performance indicators that underpin the THE World University Rankings, but the weightings differ to reflect the characteristics of Latin America’s universities. We evaluate universities across all their core missions: teaching, research, knowledge transfer and international outlook. The 2021 ranking includes 177 institutions across 13 countries, up from 166 institutions last year.

The average for 2021 based on 44 countries was 4.56 percent. The highest value was in Kiribati: 14.2 percent and the lowest value was in Nigeria: 0.38 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

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This data is gathered from United Nations databases, the following links below is been used.

https://rankedex.com/society-rankings/education-index https://en.wikipedia.org/wiki/Education_Index https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/WESP2022_ANNEX.pdf

This data can be used to measure the influence of education or income or both on any variable or vector, for example, ANOVA models.

The Income classification is for year 2021 and the education index is for 2019 to 2023.

The education index (EI) is one of the parameters that is used to calculate the Human Development Index (HDI). It is calculated by this formula: Education Index = (MYS Index + EYS Index) / 2 where MYS is Mean Years of Schooling and EYS is Expected Years of Schooling.

In this data it is assumed that : 1-Countries EI below 0.4 have Very Low Educated population 2-Countries EI between 0.4 and 0.6 have Low to Moderate Educated population 3-Countries EI between 0.6 and 0.8 have High to Moderate Educated population 4-Countries EI above 0.8 have Very Educated Educated population

This dataset tracks annual overall school rank from 2021 to 2023 for Newark School Of Global Studies

Context

The Expected Years of Schooling (EYS) is a pivotal educational metric aimed at evaluating the anticipated years of formal education an individual is expected to receive in a given country or region. EYS serves as a crucial component in understanding educational development and disparities across the world, shedding light on the differences in access to and quality of education for various populations. It offers insights into the opportunities and educational prospects available to individuals, making it an essential indicator in the realm of global education assessment.

Content

This dataset presents a comprehensive historical record of Expected Years of Schooling data on a global scale. It encompasses vital columns such as ISO3 (the ISO3 code for each country/territory), Country (the name of the country or territory), Continent (the continent where the country is located), Hemisphere (the hemisphere in which the country is situated), Human Development Groups, UNDP Developing Regions, HDI Rank (2021) denoting the Human Development Index Rank for the year 2021 and Expected Years of Schooling values spanning from 1990 to 2021. This dataset provides valuable insights into the evolution and disparities in educational prospects across the world.

Dataset Glossary (Column-wise)

• ISO3 - ISO3 code for the Country/Territory
• Country - Name of the Country/Territory
• Continent - Name of the Continent
• Hemisphere - Name of the Hemisphere
• Human Development Groups - Human Development Groups
• UNDP Developing Regions - UNDP Developing Regions
• HDI Rank (2021) - Human Development Index Rank for 2021
• Expected Years of Schooling (1990 to 2021) - Expected Years of Schooling data spanning from 1990 to 2021

Data Dictionary

• UNDP Developing Regions:
  • SSA - Sub-Saharan Africa
  • LAC - Latin America and the Caribbean
  • EAP - East Asia and the Pacific
  • AS - Arab States
  • ECA - Europe and Central Asia
  • SA - South Asia

Structure of the Dataset

https://i.imgur.com/L9ZZwwl.png" alt="">

Acknowledgement

This Dataset is created from Human Development Reports. This Dataset falls under the Creative Commons Attribution 3.0 IGO License. You can check the Terms of Use of this Data. If you want to learn more, visit the Website.

Cover Photo by: Image by pch.vector on Freepik

Thumbnail by: Education icons created by Freepik - Flaticon

This dataset tracks annual overall school rank from 2021 to 2023 for Hill Country College Prep High School

In 2022, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college. Demographics Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult. Earnings White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

This dataset tracks annual science proficiency from 2021 to 2022 for Lake Country School vs. Wisconsin and Lake Country School District

In 2022, Luxembourg was the OECD country that spent the highest amount on higher education per student, reaching roughly 35,000 U.S. dollars. This was even though it was the country that spent the lowest amount in terms of share of gross domestic product. The United States stood at 11th place, with the United Kingdom at 30th place. On the other hand, Greece was the OECD country in which the lowest amount was spent per full-time student in higher education.

The average for 2021 based on 11 countries was 52.4 index points. The highest value was in Uruguay: 93.71 index points and the lowest value was in Colombia: 20.23 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

Tribhuvan University in Nepal had approximately *** thousand full-time students in 2021. This was unquestionably the highest number of students of any Asia Pacific university, leaving Chinese and Thai universities lagging behind in terms of university student numbers. Despite the huge influx of students enrolled in Tribhuvan University, Australia still saw a dramatic surge in the number of Nepalese international students from 2015 onwards. This alludes to the fact that an international tertiary education was just as favorable as a domestic one. Interestingly, most of the universities which made the ranking for the highest number of students were situated in China. An Asia Pacific education Universities across the Asia Pacific region are experiencing a dramatic rise in student population. As a home to powerful and developing economies, it appears more students are eager to secure places in the higher education sectors which boast huge economic potential. China stands as the most popular country for international students in Asia and third most popular for international students globally. The large majority of international students in China are not reliant on Chinese governmental funding from scholarships and are self-funded. Therefore, huge investments are put into the Chinese economy. Other countries such as Thailand are too experiencing increased GDP contributions from the education sector. Despite the growing number of international students deciding to complete their higher education in China, many of the domestic Chinese students choose to study elsewhere in the Asia Pacific region. This is prevalent in the great influx of Chinese students arriving in Australia to study. Qualifications As a higher education in the Asia Pacific region is becoming more popular, initiatives have been set up to ensure qualifications are recognized throughout the many countries across Asia Pacific. The Tokyo Convention – an agreement made between Japan, South Korea, Australia, China and New Zealand – is designed to enable student and academic mobility. Simultaneously, the convention endorses the recognition of higher education qualifications throughout the Asia Pacific region. This in turn appears to encourage more domestic and international students to consider tertiary education in Asia Pacific, as their qualification will likely be recognized in their home countries and elsewhere in the region.

In 2021, the Gender Parity Index (GPI) for primary education enrollment in Bhutan and Hong Kong was ****. This indicator is calculated by dividing the female gross enrollment ratio in primary education by the male gross enrollment ratio in primary education. A GPI of less than * suggests that girls are more disadvantaged than boys in learning opportunities, while a GPI of greater than * suggests that boys are more disadvantaged than girls in learning opportunities.

Context

In today's interconnected world, the issue of inequality in education stands as a stark reminder of the disparities that persist across countries and communities. While strides have been made to improve access to education, a significant proportion of children still lack the opportunity to learn, particularly in low-income and conflict-affected regions. Quality of education also diverges, with well-equipped schools in affluent areas contrasting with under-resourced institutions in marginalized settings. Gender inequality further compounds the problem, as cultural norms and economic factors often impede girls' education in certain societies. Tackling inequality in education isn't just a matter of fairness; it's a critical step towards building equitable societies and empowering individuals to contribute meaningfully to their own development and that of their nations.

Content

This dataset contains historical data covering a range of indicators pertaining to educational inequality on a global scale. The dataset's prominent components include: ISO3, Country, Human Development Groups, UNDP Developing Regions, HDI Rank (2021), and Inequality in Education spanning the years 2010 to 2021.

Dataset Glossary (Column-wise)

• ISO3 - ISO3 for the Country/Territory
• Country - Name of the Country/Territory
• Human Development Groups - Human Development Groups
• UNDP Developing Regions - UNDP Developing Regions
• HDI Rank (2021) - Human Development Index Rank for 2021
• Inequality in Education (2010) - Inequality in Education for 2010
• Inequality in Education (2011) - Inequality in Education for 2011
• Inequality in Education (2012) - Inequality in Education for 2012
• Inequality in Education (2013) - Inequality in Education for 2013
• Inequality in Education (2014) - Inequality in Education for 2014
• Inequality in Education (2015) - Inequality in Education for 2015
• Inequality in Education (2016) - Inequality in Education for 2016
• Inequality in Education (2017) - Inequality in Education for 2017
• Inequality in Education (2018) - Inequality in Education for 2018
• Inequality in Education (2019) - Inequality in Education for 2019
• Inequality in Education (2020) - Inequality in Education for 2020
• Inequality in Education (2021) - Inequality in Education for 2021

Data Dictionary

• UNDP Developing Regions:
  • SSA - Sub-Saharan Africa
  • LAC - Latin America and the Caribbean
  • EAP - East Asia and the Pacific
  • AS - Arab States
  • ECA - Europe and Central Asia
  • SA - South Asia

Structure of the Dataset

https://i.imgur.com/qX5cmUX.png" alt="">

Acknowledgement

This Dataset is created from Human Development Reports. This Dataset falls under the Creative Commons Attribution 3.0 IGO License. You can check the Terms of Use of this Data. If you want to learn more, visit the Website.

Cover Photo by: Image by storyset on Freepik

Thumbnail by: Educational Vectors by Vecteezy

This dataset tracks annual overall school rank from 2021 to 2023 for Sst Hill Country

Days-of-Inventory-On-Hand-Turnover Time Series for Adtalem Global Education Inc. Adtalem Global Education Inc., together with its subsidiaries, provides healthcare education in the United States, Barbados, St. Kitts, and St. Maarten. It operates in three segments: Chamberlain, Walden, and Medical and Veterinary. The company offers degree and non-degree programs, including bachelor's, master's, and doctoral degrees; and online certificate programs for nursing, health professions, medical, and veterinary postsecondary education, counseling, business, information technology, psychology, public health, social work and human services, public administration and public policy, and criminal justice. It also operates Chamberlain University, Walden University, American University of the Caribbean School of Medicine, Ross University School of Medicine, and Ross University School of Veterinary Medicine. The company was formerly known as DeVry Education Group Inc. and changed its name to Adtalem Global Education Inc. in May 2017. Adtalem Global Education Inc. was incorporated in 1987 and is headquartered in Chicago, Illinois.

This dataset indicates whether countries offer a single education programme that prepares individuals to practise as both nurses and midwives. It highlights integrated training pathways and dual professional roles, offering insight into how midwifery is situated within broader health systems and informing discussion on education models and workforce planning. Data Source: State of the World"s Midwifery (SoWMy) global and regional reports: https://internationalmidwives.org/resources/state-of-the-worlds-midwifery-2021/ The State of the World’s Midwifery (SoWMy) series of reports, led by ICM, UNFPA, and WHO, provides country-level data on the midwifery workforce, including national midwives" associations, education, leadership, and regulation. It highlights gaps and opportunities to strengthen midwife-led care and improve maternal and newborn health outcomes. Data were collected by the International Confederation of Midwives (ICM) in collaboration with Novametrics through a global midwifery regulatory survey. Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hub the following codes are also possible values: not reported does not apply don’t know This is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.

World University Rankings - 2021

Source: www.timeshighereducation.com

Pages (HTML FILES): * Rankings

• Scores

Files: * Rankings (universities_ranking.csv/JSON) - Contains all the information from the Rankings page * Scores (universities_scores.csv/JSON) - Contains more detailed scores from the Scores page

Information Collected

Key statistics/Rankings The data shown under key statistics are those provided by the university itself in its submission to the Times Higher Education World University Rankings. It represents data from the 2019/20 academic year, and may vary from subsequent or earlier years.

• Ranking
• Name/Title
• Country/Region
• No. of FTE Students This is the number of full-time equivalent students at the university.
• No. of Students per Staff This is the ratio of full-time equivalent students to the number of academic staff – those involved in teaching or research.
• % International Students The percentage of students originating from outside the country of the university.
• Female:Male Ratio The ratio of female to male students at the university.

Scores: * Ranking * Name/Title * Country/Region * Overall * Teaching * Research * Citators * Industry Income * International Outlook