This Cost of International Education dataset compiles detailed financial information for students pursuing higher education abroad. It covers multiple countries, cities, and universities around the world, capturing the full tuition and living expenses spectrum alongside key ancillary costs. With standardized fields such as tuition in USD, living-cost indices, rent, visa fees, insurance, and up-to-date exchange rates, it enables comparative analysis across programs, degree levels, and geographies. Whether you’re a prospective international student mapping out budgets, an educational consultant advising on affordability, or a researcher studying global education economics, this dataset offers a comprehensive foundation for data-driven insights.

Description

Potential Uses

• Budget Planning Prospective students can filter by country, program level, or university to forecast total expenses and compare across destinations.
• Policy Analysis Educational policymakers and NGOs can assess the affordability of international education and design support programs.
• Economic Research Economists can correlate living-cost indices and tuition levels with enrollment rates or student demographics.
• University Benchmarking Institutions can benchmark their fees and ancillary costs against peer universities worldwide.

Notes on Data Collection & Quality

• Currency Conversions All monetary values are unified to USD using contemporaneous exchange rates to facilitate direct comparison.
• Living Cost Index Derived from reputable city-index publications (e.g., Numbeo, Mercer) to standardize disparate cost-of-living metrics.
• Data Currency Exchange rates and fee schedules should be periodically updated to reflect market fluctuations and policy changes.

Feel free to explore, visualize, and extend this dataset for deeper insights into the true cost of studying abroad!

Share of Students Studying Abroad by Country

Study Abroad Ratios by Country and Year

By Dennis Kao [source]

About this dataset

The Share of Students Studying Abroad dataset provides comprehensive information on the inbound and outbound mobility ratios of students by country and year. The dataset includes data on the share of students from abroad studying in different countries, represented as a percentage of the total tertiary enrollment in each country. Additionally, it also presents information on the share of students studying abroad from a particular country, calculated as a percentage of the total tertiary enrollment in that country.

Inbound Mobility Ratio is defined as the number of foreign students studying in a specific country, expressed as a percentage of the total tertiary enrollment in that same country. This ratio highlights how attractive certain countries are for international students seeking education opportunities.

On the other hand, Outbound Mobility Ratio represents the number of local or domestic students studying abroad from a given country relative to its total tertiary enrolment. This ratio sheds light on how many students are opting to pursue education outside their home countries.

The dataset further provides details such as region or continent to which each country belongs and includes unique code identifiers for both regions/countries and years mentioned.

This insightful collection aims to facilitate an understanding of global student mobility trends over time, allowing researchers and policymakers to identify patterns and gain valuable insights into educational preferences across different nations. The data source for this dataset is derived from trusted sources such as The World Bank.

By leveraging this dataset's various metrics and indicators related to inbound and outbound student mobility rates, researchers can explore potential factors influencing student choice when it comes to pursuing higher education abroad or attracting international scholars to specific regions or countries

How to use the dataset

• Understanding the Columns:

  The dataset contains several columns, including:

  • Region or Country: The name of the region or country for which the data is provided.
  • Code: The code representing the region or country.
  • Year: The year for which the data is provided.
  • Inbound mobility rate, both sexes (%): The percentage of students from abroad studying in a given region or country, out of the total tertiary enrollment in that region or country.
  • Outbound mobility ratio, all regions, both sexes (%): The percentage of students from a given country studying abroad.

• Identifying Regions and Countries:

  You can use this dataset to explore different regions and countries around the world and analyze their inbound/outbound mobility trends. By examining individual countries or groups based on their regions/continents (e.g., Asia, Europe), you can gain insights into international education patterns.

• Comparing Inbound and Outbound Mobility Rates:

  Compare and contrast inbound mobility rates (students coming from abroad) with outbound mobility rates (students going abroad) within specific years or across multiple years. This will help you understand how countries participate in global education exchange.

• Exploring Trends Over Time:

  Analyze changes over time by investigating multiple years available in this dataset. Look for any notable trends or shifts in international student enrollment patterns over specific periods.

• Country-level Analysis:

  Conduct an analysis on specific countries to understand their individual outbound and inbound mobility. Choose a country of interest, examine its outbound mobility ratio to see how many students from that country are studying abroad. Also, analyze the inbound mobility rate to observe how many international students are studying in that country.

• Regional Analysis:

  Investigate regions or continents using the Region of Country column and analyze the relative proportions of inbound and outbound mobility within those regions.

• Visualization:

  Utilize visualization tools like charts, graphs, or maps to present your findings effectively. Visual representation can help identify patterns, trends, and relationships

Research Ideas

• Analyzing trends in international student mobility: This dataset can be used to analyze the trends in international student mobility over time, both in terms of inbound and outbound mob...

🧑‍🎓 Indian International Students in the US — Education, Jobs, and Visas 📚💼

Dataset Overview

This dataset provides a detailed and realistic simulation of Indian international students studying in the United States, their educational paths, job outcomes after graduation, university information, and visa approval statistics.

It can be used for:

• Education data analysis 📊
• Employment trends for international graduates 👩‍💻
• Machine learning projects (classification, regression) 🤖
• Visa trend analysis 📈
• Career planning studies for international students 🎯

📂 Files Included | File Name| Description | | --- | --- | | indian_international_students_us.csv | Profiles of 10,000 Indian international students, including university, major, degree level, and study status. | |job_outcomes_indian_students_us.csv | Job outcomes for students who graduated, including job title, company, salary, visa status, and time to first job. | |universities_info_us.csv | Information about major US universities, including acceptance rates, GRE/TOEFL averages, and international student percentages. | | visa_approval_stats.csv | Yearly visa approval and denial rates for F1, OPT, and H1B visa types from 2015 to 2023. |

✨ Potential Project Ideas 1. Predict job offer chances based on major, degree, and university. 2. Analyze salary distributions by major, company, and visa status. 3. Visualize visa approval trends over time. 4. Build a career advisory tool for international students.

✨ SQL Potential Project 1. List all students studying in "Computer Science" major. 2. Count how many students are currently enrolled vs graduated. 3. Find top 5 universities with the highest number of students. 4. Get the list of all students whose degree level is "Masters". 5. Find average salary of students who received a job offer. 6. List all companies that hired at least one student.

1. Find universities with an acceptance rate below 20%.
2. Calculate the percentage of students in each degree level (Bachelors, Masters, PhD).
3. Find top 10 job titles offered to Indian students.
4. List universities where average GRE score is above 320.
5. Rank students based on salary who got a job.

6. Find visa approval rate for each visa type (F1, OPT, H1B) over the years.

7. Build a report showing: University Name Number of students Number of students who got jobs Average salary Job offer rate (%)

8. Identify majors with the highest average salaries after graduation.

9. Compare visa approval trends: How have F1, OPT, and H1B approval rates changed from 2015 to 2023?

10. Create a view showing: Students with highest probability of getting a job based on major, university, and degree level.

11. Predict (with SQL logic): If a new student graduates from [University X] with [Major Y] and [Degree Level Z], what is their expected salary range?

12. Cohort Analysis: Analyze students who graduated in a particular year, how many got jobs within 6 months.

⚡ Important Note This dataset is synthetic but designed to be realistic based on trends among Indian students studying abroad. No real personal information is included. Great for educational, research, and portfolio purposes.

🔖 Acknowledgment Generated by Pushkar Joshi using simulated data sources. Inspired by real-world patterns and publicly available educational statistics.

🏷️ Suggested Tags

education, #students, #international-students, #jobs, #visas, #synthetic-data, #data-science, #kaggle-datasets

This dataset provides the number of students on scholarships abroad, categorized by country of study, scientific degree (Doctorate, Masters, Bachelor, Other), and gender (Male, Female). It offers insights into international student distribution for various academic levels and across different countries. This data is essential for understanding trends in global academic mobility and gender representation in higher education abroad.

Indian Students Abroad

Country-wise Statistics

By Harish Kumar Garg [source]

About this dataset

This dataset is about the number of Indian students studying abroad in different countries and the detailed information about different nations where Indian students are present. The data has been complied from the Ministry Of External Affairs to answer a question from the Member of Parliament regarding how many students from India are studying in foreign countries and which country. This dataset includes two fields, Country Name and Number of Indians Studying Abroad as of Mar 2017, giving a unique opportunity to track student mobility across various nations around the world. With this valuable data about student mobility, we can gain insights into how educational opportunities for Indian students have increased over time as well as look at trends in international education throughout different regions. From comparison among countries with similar academic opportunities to tracking regional popularity among study destinations, this dataset provides important context for studying student migration patterns. We invite everyone to explore this data further and use it to draw meaningful conclusions!

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How to use the dataset

How to use this dataset?

The data has two columns – Country Name and Number of Indians studying there as of March 2017. It also includes a third column, Percentage, which gives an indication about the proportion of Indian students enrolled in each country relative to total number enrolled abroad globally.

To get started with your exploration, you can visualize the data against various parameters like geographical region or language speaking as it may provide more clarity about motives/reasons behind student’s choice. You can also group countries on basis of research opportunities available, cost consideration etc.,to understand deeper into all aspects that motivate Indians to explore further studies outside India.

Additionally you can use this dataset for benchmarking purpose with other regional / international peer groups or aggregate regional / global reports with aim towards making better decisions or policies aiming greater outreach & support while targeting foreign universities/colleges for educational promotion activities that highlights engaging elements aimed at attracting more potential students from India aspiring higher international education experience abroad!

Research Ideas

• Using this dataset, educational institutions in India can set up international exchange programs with universities in other countries to facilitate and support Indian students studying abroad.

• Higher Education Institutions can also understand the current trend of Indian students sourcing for opportunities to study abroad and use this data to build specialized short-term courses in collaboration with universities from different countries that cater to the needs of students who are interested in moving abroad permanently or even temporarily for higher studies.

• Policy makers could use this data to assess the current trends and develop policies that aim at incentivizing international exposure among young professionals by commissioning fellowships or scholarships with an aim of exposing them to different problem sets around the world thereby making their profile more attractive while they look for better job opportunities globally

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: final_data.csv | Column name | Description | |:--------------------------|:-------------------------------------------------------------------------------------------------------------------------------| | Country | Name of the country where Indian students are studying. (String) | | No of Indian Students | Number of Indian students studying in the country. (Integer) | | Percentage | Percentage of Indian students studying in the country compared to the total number of Indian students studying abroad. (Float) |

Acknowledgements

If you use this dataset in your research, please credit ...

This dataset includes 397 observation of Vietnamese student's intention to study abroad before and during the COVID-19 pandemic. The dataset was collected through an online survey from 03 to 13 May 2020, over "Scholarship hunter", the largest community of Vietnamese overseas students on Facebook. Major variables are: (i) Students’ Demographics; (ii) The previous intention of students to study abroad before and during the Covid-19 ravaged and (iii) Their intention afterwards.

Provide the number of international students studying/undertaking research in Taiwan for each academic year.

China Number of Student Studying Abroad data was reported at 703,500.000 Person in 2019. This records an increase from the previous number of 662,100.000 Person for 2018. China Number of Student Studying Abroad data is updated yearly, averaging 20,381.000 Person from Dec 1952 (Median) to 2019, with 47 observations. The data reached an all-time high of 703,500.000 Person in 2019 and a record low of 114.000 Person in 1962. China Number of Student Studying Abroad data remains active status in CEIC and is reported by Ministry of Education. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GD: No of Student Studying Abroad and Foreign Student.

This dataset provides statistics on the number of new students who enrolled in scholarships abroad, categorized by country of study and gender. It helps track trends in international education and student mobility patterns.

This dataset contains the year and country wise number of Indian students travelled abroad for higher education as per information provided by the Bureau of Immigration (BoI)

The StudyAbroadGuide dataset is a collection of 2,190 conversational data pairs designed to assist students seeking guidance on studying abroad. It includes questions and answers about various study-abroad topics, including university selection, TOEFL requirements, application timelines, visa information, and more.

This dataset aims to provide a comprehensive, real-world conversational model that can be used to train AI chatbots, virtual assistants, and recommendation systems specifically focused on helping students navigate the study-abroad process.

Key Features:

• Total Conversations: 2,190
• Language: English
• License: Apache-2.0
• Dataset Type: Question-Answering

This dataset is well-suited for training AI models, improving study-abroad guidance chatbots, and developing personalized recommendations for students considering international education opportunities.

Studying abroad can be a life-changing experience that can help students develop skills, make friends, and gain a global perspective. Since the post-pandemic, the number of US students studying abroad has sharply increased. However, there are various barriers that hinder students from studying abroad. For Computer Science students, the lack of opportunities is believed to be the main barrier causing CS students to have some of the lowest study abroad participation rates. We aim to understand how CS Study Aboard participants overcame the barriers and challenges they faced through a series of interviews. Based on the results, we provide guidelines to motivate future CS Study Abroad experiences.In this dataset, the word code refers to labels or tags assigned to segments of qualitative data to summarize or categorize their meaning.

This dataset contains the educational loans availed by Indian students travelling abroad for higher education

The "User Survey of Norwegian Students Studying Abroad During the Second Year of Upper Secondary School (Vg2), 2016" was carried out by ideas2evidence on behalf of SIU. This file contains no information about student countries.

The background for the project was the Ministry of Education and Research's directive F02-14, where SIU was asked to carry out a user survey to increase the knowledge on students' experience of exchange abroad with the use of an approved exchange organization. The survey aimed to give information on whether or not the terms of approval still were fullfilled, and to give insight to quality of the students' experience of exchange abroad.

This dataset includes data from the first user survey, and norwegian students staying abroad during their second year of upper secondary school in 2015-16. Organizations with few answers are recoded to "99- Other organizations". A file with information on students countries is also available for downloading.

Data are freely available for downloading.

The current data set consists of information collected from PRC and other international students studying in Taiwan. A total of 1870 students participated in the study. Data collected are study abroad goals, prior study abroad experiences, the Short-term Study Abroad Situational Change Survey, a revised East Asian Acculturation Measure, Study Abroad Hassles, and overall study abroad satisfaction. Demographic data include student group, age, gender, duration of stay, and type of study abroad program. No identifying information is provided.

In recent years, international student mobility has become a key aspect of higher education. As more students consider studying abroad, universities are increasingly focused on understanding and improving international student satisfaction. This satisfaction is influenced by various factors, the host country included. This study uses in-depth qualitative interviews analyzed with MAXQDA 24 software and thematic code matrix-based heatmap analysis to explore international student satisfaction and dissatisfaction in two national contexts, at San Jose State University, U.S.A., and the University of Szeged, Hungary. The findings indicate that factors contributing to satisfaction are less specific to the country or institution, while dissatisfaction is more closely tied to local and institutional factors. The research contributes to existing literature by identifying key factors in student satisfaction and dissatisfaction, providing a foundation for future quantitative studies and offering insights for higher education policymakers.

This dataset provides information about the yearly fees for various courses offered by colleges and universities across different countries. The data is sourced from Jeduka.com, a platform known for providing detailed insights into educational opportunities abroad. The dataset consists of four key columns:

COUNTRY: The country where the course is offered. COURSE: The specific course being offered (e.g., Engineering, Medicine, Business). COURSE TYPE: The type of course (e.g., Bachelor's, Master's, Diploma). FEES: The yearly tuition fees for the course in the respective country (in local currency). This dataset is ideal for those interested in comparing study costs across countries and analyzing trends in international education expenses. It can be utilized to predict and compare fees based on various parameters, helping students make informed decisions about their study abroad options.

Research on travelling populations, indicates that geographic mobility is associated with changes in health behaviours. However, there is currently little longitudinal data recording study abroad students' health behaviours other than alcohol use, and that includes a variety of risk and protective factors related to students' demographics and their experiences abroad. The present dataset contains the original longitudinal data from a study of European study abroad students' and includes information on participants health-related behaviour: including physical exercise, diet, alcohol and drug use, and unprotected casual sex. Self-reported data were collected across three waves: on arrival in the host country, to assess pre-departure behaviour (T1), four months through the period abroad (T2), and four months after returning home (T3). Data on factors related to participants' demographics and their abroad experience, including motivations to study abroad, acculturation orientation and adjustment to the host environment, and perceptions regarding different referent peers’ drinking behaviour were also collected. Data were collected in the 2015-2016 academic year. At T1 students in 200 cities from more than 40 European countries were approached by representatives from an international student association. Participants who completed at least two surveys were included (N = 908). The T1 survey was completed by 899 students (nine students provided an e-mail address but did not complete the survey at T1), 785 (86.5%) completed T2 survey, and 438 (48.2%) the T3 survey. The data article presents tables charting variables measured by survey wave and participants' socio-demographic and study abroad experience characteristics. With an acceptable drop-out across the three waves, these data may be of interest to researchers who wish to understand factors related to changes in health behaviours in this population and develop targeted health promotion interventions. Other stakeholders such as policy makers, international offices, health professionals in counselling service, student associations may also use these data to develop communication campaigns and intervene with reference to relevant risk and protective factors.

The demand for higher education continues to grow as universities compete globally to attract students. But are students opting for private or public institutions? To what extent do they pursue their education abroad? Are women moving into fields traditionally dominated by men, such as science and computing? These are just some of the questions faced by policymakers looking to expand and diversify their national tertiary education systems. Based on its annual data collection, the UIS produces a range of indicators to track trends in tertiary education at the global, regional and national levels. These data include: enrolment and graduation ratios disaggregated by sex and type of programme; enrolment rates in private and public institutions; and graduates by field of study. The UIS has also developed a series of unique indicators to track the flows of foreign or mobile students. These data reveal the shifting demand for higher education, especially in developing countries, by showing where students go to study and where they come from.

This dataset provides information on the number of international students enrolled in NSW public schools, categorised by operational directorate.

Data notes:

• Data is sourced through the DE International Student Management System.

• International students must hold a student visa and require an Authority to Enrol (ATE) form, issued by DE International, to enrol in a NSW public school.

• Enrolment numbers are not representative of the number of students in the International Students Program, as a student may enrol in an Intensive English Centre and then proceed to a high school.

• Total enrolments include full fee-paying students in the International Students Program who complete their high school education in a NSW government school, and Study Abroad program students who enrol from one term to a maximum of one year.

• All international students and Study Abroad students are able to commence their study from Term 1 through to Term 4.

• Data has been confidentialised where necessary to suppress international student enrolments of 15 or fewer students in an operational directorate, indicated by “sp”.

• An operational directorate oversees groups of principal networks in which schools are organised. For more information, visit the most up-to-date [operational directorate list](https://education.nsw.gov.au/public-schools/going-to-a-public-school/finding-a-public-school"operational directorate list ").

Data source:

• DE International, Community Languages and International Programs, Student Support and Specialist Programs, Teaching Learning and Student Wellbeing, NSW Department of Education.