In the Midocean University in Comoros, ** percent of students were international students, making it the university in the world with the highest share of foreign students. Some of these universities have a clear focus on remote learning, making it far easier for international students to register and study there. . See here for an overview of the highest ranked universities in the world.

Context

More international students are flocking to China than ever before. According to a report, over 540,000 foreigners studied in China in 2018 – marking a 40 percent increase from 2012. China attracts more international students than any other Asian power and ranks third globally, behind the United States and the United Kingdom.

Content

In 2018 there were a total of 492,185 international students from 196 countries/areas pursuing their studies in 1,004 higher education institutions in China’s 31 provinces/autonomous regions/provincial-level municipalities, marking an increase of 3,013 students or 0.62% compared to 2017. International students in Hong Kong, Macau and Taiwan are not included in the datasets. The datasets contain three CSV files (Continent, Country, Province) with different data about international students in China.

Columns Description

@Continent (Number/percent of international students by continent) Continent- The name of continent Number - The number of total international students Deaths- The percentage of total international students

@Country (Number of international students by country of origin) Rank- The rank of the country based on total students in China Country- The name of the country Number- The number of total international students

@Province (The top provinces/cities with the largest number of international students) Province- The name of the city/province Number- The number of total international students

Acknowledgements

This data collected from moe.gov.cn.

Inspiration

Currently, I'm studying at a Chinese university. Every year many international students come to China for their higher study, and the ratio of international students is growing steadily. This data will help us to understand the ratio of international students in China.

Colleges and universities in the United States are still a popular study destination for Chinese students, with around 277 thousand choosing to take courses there in the 2023/24 academic year. Although numbers were heavily affected by the coronavirus pandemic, China is still the leading source of international students in the U.S. education market, accounting for 24.6 percent of all incoming students. The education exodus Mathematics and computer science courses led the field in terms of what Chinese students were studying in the United States, followed by engineering and business & management programs. The vast majority of Chinese students were self-funded, wth the remainder receiving state-funding to complete their overseas studies. Tuition fees can run into the tens of thousands of U.S. dollars, as foreign students usually pay out-of-state tuition fees. What about the local situation? Although studying abroad attracts many Chinese students, the country itself boasts the largest state-run education system in the world. With modernization of the national tertiary education system being a top priority for the Chinese government, the country has seen a significant increase in the number of local universities over the last decade. Enrolments in these universities exceeded 37 million in 2023, and a record of more than ten million students graduated in the same year, indicating that China's education market is still expanding.

In 2022, Canada had the greatest amount of international students compared to their entire higher education population with nearly 40 percent of students being international. Australia followed with a share of 31 percent of the students being international, while the United Kingdom ranked third.

This dataset is about universities in Columbus. It has 1 row. It features 3 columns: country, and international students.

Japan No. of International Students: Sweden data was reported at 525.000 Person in 2017. This records a decrease from the previous number of 534.000 Person for 2016. Japan No. of International Students: Sweden data is updated yearly, averaging 212.000 Person from Apr 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 572.000 Person in 2014 and a record low of 116.000 Person in 2005. Japan No. of International Students: Sweden data remains active status in CEIC and is reported by Japan Student Services Organization. The data is categorized under Global Database’s Japan – Table JP.G009: Survey on Internation Students: Number of International Students in Japan.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

Abstract

“What is important for citizens to know and be able to do?” That is the question that underlies the triennial survey of 15-year-old students around the world known as the Programme for International Student Assessment (PISA). PISA assesses the extent to which students near the end of compulsory education have acquired key knowledge and skills that are essential for full participation in modern societies. The assessment, which focuses on reading, mathematics, science and problem solving, does not just ascertain whether students can reproduce knowledge; it also examines how well students can extrapolate from what they have learned and apply that knowledge in unfamiliar settings, both in and outside of school. This approach reflects the fact that modern economies reward individuals not for what they know, but for what they can do with what they know. All 34 OECD member countries and 31 partner countries and economies participated in PISA 2012, representing more than 80% of the world economy.

With mathematics as its primary focus, the PISA 2012 assessment measured 15-year-olds’ capacity to reason mathematically and use mathematical concepts, procedures, facts and tools to describe, explain and predict phenomena, and to make the wellfounded judgements and decisions needed by constructive, engaged and reflective citizens. Literacy in mathematics defined this way is not an attribute that an individual has or does not have; rather, it is a skill that can be acquired and used, to a greater or lesser extent, throughout a lifetime.

The PISA assessment provides three main types of outcomes: - basic indicators that provide a baseline profile of students’ knowledge and skills; - indicators that show how skills relate to important demographic, social, economic and educational variables; and - indicators on trends that show changes in student performance and in the relationships between student-level and school-level variables and outcomes.

Geographic coverage

PISA 2012 covered 34 OECD countries and 31 partner countries and economies. All countries attempted to maximise the coverage of 15-year-olds enrolled in education in their national samples, including students enrolled in special educational institutions.

Analysis unit

To better compare student performance internationally, PISA targets a specific age of students. PISA students are aged between 15 years 3 months and 16 years 2 months at the time of the assessment, and have completed at least 6 years of formal schooling. They can be enrolled in any type of institution, participate in full-time or part-time education, in academic or vocational programmes, and attend public or private schools or foreign schools within the country. Using this age across countries and over time allows PISA to compare consistently the knowledge and skills of individuals born in the same year who are still in school at age 15, despite the diversity of their education histories in and outside of school.

Kind of data

Sample survey data [ssd]

Sampling procedure

The accuracy of any survey results depends on the quality of the information on which national samples are based as well as on the sampling procedures. Quality standards, procedures, instruments and verification mechanisms were developed for PISA that ensured that national samples yielded comparable data and that the results could be compared with confidence.

Most PISA samples were designed as two-stage stratified samples (where countries applied different sampling designs. The first stage consisted of sampling individual schools in which 15-year-old students could be enrolled. Schools were sampled systematically with probabilities proportional to size, the measure of size being a function of the estimated number of eligible (15-year-old) students enrolled. A minimum of 150 schools were selected in each country (where this number existed), although the requirements for national analyses often required a somewhat larger sample. As the schools were sampled, replacement schools were simultaneously identified, in case a sampled school chose not to participate in PISA 2012.

Experts from the PISA Consortium performed the sample selection process for most participating countries and monitored it closely in those countries that selected their own samples. The second stage of the selection process sampled students within sampled schools. Once schools were selected, a list of each sampled school's 15-year-old students was prepared. From this list, 35 students were then selected with equal probability (all 15-year-old students were selected if fewer than 35 were enrolled). The number of students to be sampled per school could deviate from 35, but could not be less than 20.

Around 510 000 students between the ages of 15 years 3 months and 16 years 2 months completed the assessment in 2012, representing about 28 million 15-year-olds in the schools of the 65 participating countries and economies.

Mode of data collection

Face-to-face [f2f]

Research instrument

Paper-based tests were used, with assessments lasting two hours. In a range of countries and economies, an additional 40 minutes were devoted to the computer-based assessment of mathematics, reading and problem solving.

Test items were a mixture of questions requiring students to construct their own responses and multiple-choice items. The items were organised in groups based on a passage setting out a real-life situation. A total of about 390 minutes of test items were covered, with different students taking different combinations of test items.

Students answered a background questionnaire, which took 30 minutes to complete, that sought information about themselves, their homes and their school and learning experiences. School principals were given a questionnaire, to complete in 30 minutes, that covered the school system and the learning environment. In some countries and economies, optional questionnaires were distributed to parents, who were asked to provide information on their perceptions of and involvement in their child’s school, their support for learning in the home, and their child’s career expectations, particularly in mathematics. Countries could choose two other optional questionnaires for students: one asked students about their familiarity with and use of information and communication technologies, and the second sought information about their education to date, including any interruptions in their schooling and whether and how they are preparing for a future career.

Cleaning operations

Software specially designed for PISA facilitated data entry, detected common errors during data entry, and facilitated the process of data cleaning. Training sessions familiarised National Project Managers with these procedures.

Response rate

Data-quality standards in PISA required minimum participation rates for schools as well as for students. These standards were established to minimise the potential for response biases. In the case of countries meeting these standards, it was likely that any bias resulting from non-response would be negligible, i.e. typically smaller than the sampling error.

A minimum response rate of 85% was required for the schools initially selected. Where the initial response rate of schools was between 65% and 85%, however, an acceptable school response rate could still be achieved through the use of replacement schools. This procedure brought with it a risk of increased response bias. Participating countries were, therefore, encouraged to persuade as many of the schools in the original sample as possible to participate. Schools with a student participation rate between 25% and 50% were not regarded as participating schools, but data from these schools were included in the database and contributed to the various estimations. Data from schools with a student participation rate of less than 25% were excluded from the database.

PISA 2012 also required a minimum participation rate of 80% of students within participating schools. This minimum participation rate had to be met at the national level, not necessarily by each participating school. Follow-up sessions were required in schools in which too few students had participated in the original assessment sessions. Student participation rates were calculated over all original schools, and also over all schools, whether original sample or replacement schools, and from the participation of students in both the original assessment and any follow-up sessions. A student who participated in the original or follow-up cognitive sessions was regarded as a participant. Those who attended only the questionnaire session were included in the international database and contributed to the statistics presented in this publication if they provided at least a description of their father’s or mother’s occupation.

Number of Students: Higher Education: ytd: Malaysia: Queensland data was reported at 1,174.000 Person in Dec 2024. This stayed constant from the previous number of 1,174.000 Person for Nov 2024. Number of Students: Higher Education: ytd: Malaysia: Queensland data is updated monthly, averaging 1,615.500 Person from Jan 2002 (Median) to Dec 2024, with 276 observations. The data reached an all-time high of 2,204.000 Person in Dec 2010 and a record low of 675.000 Person in Jan 2022. Number of Students: Higher Education: ytd: Malaysia: Queensland data remains active status in CEIC and is reported by Department of Education. The data is categorized under Global Database’s Australia – Table AU.G120: Education Statistics: Number of Enrolments.

The dataset contains the quarterly country-wise statistics of international traffic in the category of passengers.

Poland PL: Over-Age Students: Primary: Female: % of Female Enrollment data was reported at 0.582 % in 2016. This records a decrease from the previous number of 0.714 % for 2015. Poland PL: Over-Age Students: Primary: Female: % of Female Enrollment data is updated yearly, averaging 0.925 % from Dec 1999 (Median) to 2016, with 18 observations. The data reached an all-time high of 1.183 % in 2000 and a record low of 0.582 % in 2016. Poland PL: Over-Age Students: Primary: Female: % of Female Enrollment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Poland – Table PL.World Bank: Education Statistics. Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.; ; UNESCO Institute for Statistics; ;

ABOUT

The Global Population Growth Dataset provides a comprehensive record of population trends across various countries over multiple decades. It includes detailed information such as the country name, ISO3 country code, year-wise population data, population growth, and growth rate. This dataset is valuable for researchers, demographers, policymakers, and data analysts interested in studying population dynamics, demographic trends, and economic development.

Key features of the dataset:

✅ Covers multiple countries and regions worldwide
✅ Includes historical and recent population data
✅ Provides year-wise population growth and growth rate (%)
✅ Categorizes data by country and decade for better trend analysis

This dataset serves as a crucial resource for analyzing global population trends, understanding demographic shifts, and supporting socio-economic research and policy-making.

FILE INFORMATION

The dataset consists of structured records related to country-wise population data, compiled from official sources. Each file contains information on yearly population figures, growth trends, and country-specific data. The structured format makes it useful for researchers, economists, and data scientists studying demographic patterns and changes. The file type is CSV.

COLUMNS DESCRIPTION

• Country – The name of the country.
• ISO3 – The three-letter ISO code of the country.
• Year – The year corresponding to the population data, useful for trend analysis.
• Population – The total population of the country for the given year.
• Population Growth – The absolute increase in population compared to the previous year.
• Growth Rate (%) – The percentage change in population compared to the previous year.
• Decade – The decade classification (e.g., 1990s, 2000s) for grouping long-term trends.

El Salvador SV: Over-Age Students: Primary: % of Enrollment data was reported at 14.469 % in 2016. This records a decrease from the previous number of 15.506 % for 2015. El Salvador SV: Over-Age Students: Primary: % of Enrollment data is updated yearly, averaging 16.400 % from Dec 1970 (Median) to 2016, with 18 observations. The data reached an all-time high of 25.837 % in 1998 and a record low of 14.469 % in 2016. El Salvador SV: Over-Age Students: Primary: % of Enrollment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank: Education Statistics. Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.; ; UNESCO Institute for Statistics; ;

In 2024, Netflix reported a revenue of nearly 17 billion U.S. dollars in the United States and Canada, up from around 15 billion in the previous year. The revenue generated in the North American countries was more than triple the amount brought in from Latin America and Asia Pacific. Netflix faces challenge to keep growing While the EMEA (Europe, Middle East, and Africa) region is Netflix’s second largest market in terms of revenue, the subscriber base in this region surpassed that in the U.S. and Canada for the first time in 2022. These countries experienced the most substantial combined subscriber loss when Netflix struggled to continue to grow in the same year as the service’s price has increased significantly over the past few years, leading audiences to switch to more affordable entertainment options. However, after this reported drop, the streaming giant seems to be back on track, adding around 30 million net subscribers in only one year. Consumers’ perception of Netflix Netflix has long been the SVOD market leader worldwide, despite rising competition. However, the perception of the streaming giant has taken a hit in the last few years. While the share of customers who were satisfied with Netflix amounted to 90 percent in 2021, the satisfaction rate declined below the 80 percent mark. Moreover, a survey asking users about eight different streaming services revealed that Netflix saw the highest year-over-year drops in the share of subscribers who were likely to keep the platform between 2021 and 2023.

Indonesia Number of Student: Higher Education: East Kalimantan data was reported at 94,209.000 Person in 2018. This records a decrease from the previous number of 98,406.000 Person for 2017. Indonesia Number of Student: Higher Education: East Kalimantan data is updated yearly, averaging 42,661.500 Person from Mar 1995 (Median) to 2018, with 24 observations. The data reached an all-time high of 100,020.000 Person in 2015 and a record low of 15,789.000 Person in 1996. Indonesia Number of Student: Higher Education: East Kalimantan data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GAC003: Number of Student: by Province.

In March 2003, banks and selected Registered Financial Corporations (RFCs) began reporting their international assets, liabilities and country exposures to APRA in ARF/RRF 231 International Exposures. This return is the basis of the data provided by Australia to the Bank for International Settlements (BIS) for its International Banking Statistics (IBS) data collection. APRA ceased the RFC data collection after September 2010.

The IBS data are based on the methodology described in the BIS Guide on International Financial Statistics (see http://www.bis.org/statistics/intfinstatsguide.pdf; Part II International banking statistics). Data reported for Australia, and other countries, on the BIS website are expressed in United States dollars (USD).

Data are recorded on an end-quarter basis.

This statistical table contains two data worksheets - one presenting data expressed in Australian dollar (AUD) terms and the other in USD terms.

There are two sets of IBS data: locational data, which are used to gauge the role of banks and financial centres in the intermediation of international capital flows; and consolidated data, which can be used to monitor the country risk exposure of national banking systems. Only consolidated data are reported in this statistical table.

‘Total banks and RFCs’ is also reported in USD equivalent amounts, using the end-quarter AUD/USD exchange rate from statistical table F11.

The consolidated data reported in this statistical table are on the international exposures of banks (and RFCs between March 2003 and September 2010) operating in Australia. The types of assets included here are consistent with the locational data in statistical table B12.1. However, the consolidated data differ from the locational data in three key ways: foreign currency positions with Australian residents are excluded (whereas they are included in the locational data); claims between different offices of the same institution (e.g. between the head office and its subsidiary) are netted (whereas positions, including intra-group positions, are reported on a gross basis in the locational data); and on-balance sheet derivatives are not included in international claims or foreign claims, but are included separately under ‘Derivatives’ in statistical table B13.2. Foreign-owned reporting entities report on an unconsolidated basis.

The consolidated data are split by type of exposure. ‘International claims’ refers to all cross-border claims plus foreign offices’ local claims on residents in foreign currencies; foreign claims refers to all cross-border claims plus foreign offices’ local claims on residents in both local and foreign currencies; immediate risk claims (expressed by the BIS as claims on an immediate borrower basis) cover claims based on the country where the immediate counterparty resides; and ultimate risk claims cover immediate exposures adjusted (via guarantees and other risk transfers) to reflect the location of the ultimate counterparty/risk.

Foreign offices include the overseas branches, subsidiaries and joint ventures of a bank (or RFC between March 2003 and September 2010).

Risk transfers are those transfers of risk from the country of the immediate borrower to the country of ultimate risk as a result of guarantees, collateral, and where the counterparty is a legally dependent branch of a bank headquartered in another country. The risk reallocation includes loans to Australian borrowers that are guaranteed by foreign entities and therefore represent outward risk transfers from Australia, which increase the ultimate exposure to the country of the guarantor. Similarly, foreign lending that is guaranteed by Australian entities is reported as an inward risk transfer to Australia, which reduces the ultimate exposure to the country of the foreign borrower. The risk reallocation also includes transfers between different economic sectors (banks, public sector and non-bank private sector) in the same country.

Foreign claims on an ultimate risk basis are shown for the following types of reporting entity: Australian-owned banks (i.e. those with their parent entity legally incorporated in Australia); foreign subsidiary banks; branches of foreign banks; RFCs; and Australian-owned entities (i.e. Australian-owned banks and RFCs). The RFC data are only available between March 2003 and September 2010.

‘Foreign claims (ultimate risk basis) – Aust-owned entities’ is also reported in USD equivalent amounts, using the end-quarter AUD/USD exchange rate from statistical table F11.

From 2000 until 2019, youth unemployment fluctuated between 13 and 15.5 percent, before it rose above 17 percent in 2020 during the Covid-19 pandemic. Youth unemployment Just like the general unemployment rate, youth unemployment is recorded and monitored to gauge the job market situation in a country and worldwide. Youth unemployment includes unemployed individuals aged 15 to 24, typically referring to those who have either just finished school or graduated and are looking for jobs. In order to be registered as unemployed, a person must be able to work, unemployed, and looking for a job. Usually youth unemployment is higher than adult unemployment, as many graduates do not find employment right after they have graduated. Regional breakdown The world region with the highest youth unemployment rate has been the Arab World for the past two decades, while East Asia and the Pacific has generally had the lowest rate. Apart from the sharp rise in 2020, the most notable increase came in 2009 as a result of the Great Recession; while this increase can be observed on a global scale, its impact on youth unemployment was more severely felt in more advanced economies in Europe and North America.

Austria AT: Repeaters: Primary: Male: % of Male Enrollment data was reported at 3.221 % in 2017. This records an increase from the previous number of 3.154 % for 2016. Austria AT: Repeaters: Primary: Male: % of Male Enrollment data is updated yearly, averaging 2.917 % from Dec 1971 (Median) to 2017, with 14 observations. The data reached an all-time high of 6.915 % in 1971 and a record low of 1.396 % in 2002. Austria AT: Repeaters: Primary: Male: % of Male Enrollment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Austria – Table AT.World Bank.WDI: Social: Education Statistics. Repeaters in primary school are the number of students enrolled in the same grade as in the previous year, as a percentage of all students enrolled in primary school.;UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of February 2020.;Weighted average;

Panama PA: Over-Age Students: Primary: Male: % of Male Enrollment data was reported at 9.837 % in 2015. This records an increase from the previous number of 9.393 % for 2014. Panama PA: Over-Age Students: Primary: Male: % of Male Enrollment data is updated yearly, averaging 15.787 % from Dec 1970 (Median) to 2015, with 35 observations. The data reached an all-time high of 27.313 % in 1970 and a record low of 9.347 % in 2006. Panama PA: Over-Age Students: Primary: Male: % of Male Enrollment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank: Education Statistics. Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.; ; UNESCO Institute for Statistics; ;

Estonia EE: Over-Age Students: Primary: Male: % of Male Enrollment data was reported at 4.203 % in 2015. This records a decrease from the previous number of 4.312 % for 2014. Estonia EE: Over-Age Students: Primary: Male: % of Male Enrollment data is updated yearly, averaging 3.881 % from Dec 1995 (Median) to 2015, with 20 observations. The data reached an all-time high of 5.852 % in 2003 and a record low of 1.087 % in 2013. Estonia EE: Over-Age Students: Primary: Male: % of Male Enrollment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Estonia – Table EE.World Bank: Education Statistics. Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.; ; UNESCO Institute for Statistics; ;