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Global International Education Costs
Education & Learning Analytics
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About
This 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 [1]. With standardised fields such as tuition in USD, living-cost indices, rent, visa fees, insurance, and up-to-date exchange rates, it enables comparative analysis across programmes, degree levels, and geographies [1]. 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 foundation for data-driven insights [1].
Columns
- Country (string): The ISO country name where the university is located, used to group and filter cost data by national context [2, 3]. Examples include "Germany" and "Australia" [2].
- City (string): The urban area or municipality hosting the university, which helps analyse cost variations within a country [2, 3]. Examples include "Munich" and "Melbourne" [2].
- University (string): The full, official name of the higher-education institution, enabling benchmarking across specific schools [2, 4]. An example is the "Technical University of Munich" [2].
- Program (string): The specific course or major, such as "Master of Computer Science" or "MBA", facilitating analysis of cost differences by academic tier [2, 5].
- Level (string): The degree level of the programme, including "Undergraduate", "Master’s", "PhD", or other certifications, which helps analyse cost differences by academic tier [2, 5].
- Duration_Years (integer): The length of the programme in years, indicating total study time for prorating annual costs or comparing shorter versus longer programmes [6, 7].
- Tuition_USD (numeric): The total academic tuition fee for the entire programme, converted into U.S. dollars [6, 7]. Tuition refers to fees charged by institutions for instruction and services [7].
- Living_Cost_Index (numeric): A normalised index reflecting relative day-to-day living expenses (food, transport, utilities), with New York City as the baseline (100) [6, 8]. This index is sourced from global cost-of-living databases [8].
- Rent_USD (numeric): The average monthly cost of student accommodation, in U.S. dollars, derived from crowdsourced housing-price datasets for consistency [6, 8].
- Visa_Fee_USD (numeric): The one-time application fee required for an international student visa, in U.S. dollars [9, 10]. Fees vary by country but generally cover processing and issuance [10].
- Insurance_USD (numeric): The annual health or student insurance cost, in U.S. dollars, as required by many host countries [9, 11]. Health insurance covers part or all medical expenses during study abroad [11].
- Exchange_Rate (numeric): The number of local currency units per one U.S. dollar at data collection time [9, 12]. Exchange rates are essential for converting local costs into USD for consistent comparison [12].
Distribution
The dataset is typically provided as a CSV file, named "International_Education_Costs.csv" [13, 14]. It has a file size of 84.11 kB and contains 12 columns [14]. The dataset includes 907 valid records across most columns [3-5, 7, 8, 10-12, 15, 16]. All monetary values are unified to USD using contemporaneous exchange rates to facilitate direct comparison [17]. The Living Cost Index is derived from reputable city-index publications (e.g., Numbeo, Mercer) to standardise disparate cost-of-living metrics [17]. Exchange rates and fee schedules should be periodically updated to reflect market fluctuations and policy changes [14].
Usage
This dataset is ideal for several applications and use cases:
- Budget Planning: Prospective students can filter by country, programme level, or university to forecast total expenses and compare across destinations [9].
- Policy Analysis: Educational policymakers and NGOs can assess the affordability of international education and design support programmes [9].
- Economic Research: Economists can correlate living-cost indices and tuition levels with enrollment rates or student demographics [17].
- University Benchmarking: Institutions can benchmark their fees and ancillary costs against peer universities worldwide [17].
Coverage
The dataset covers multiple countries, cities, and universities around the world [1]. It includes data for 71 unique countries, 556 unique cities, and 622 unique higher-education institutions [3, 4]. The time range reflects up-to-date exchange rates at the time of data collection, with a recommendation for annual updates [1, 14]. The demographic scope focuses on students pursuing higher education abroad [1].
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Prospective international students: To map out budgets and compare affordability across various study destinations [1, 9].
- Educational consultants: For advising students on the financial aspects of studying abroad [1].
- Researchers: To study global education economics and derive insights from cost data [1].
- Educational policymakers and NGOs: To assess the affordability of international education and develop support initiatives [9].
- Economists: To analyse the relationship between living costs, tuition fees, enrollment rates, and student demographics [17].
- Universities: To benchmark their fees and associated costs against other institutions globally [17].
Dataset Name Suggestions
- Global International Education Costs
- International Study Abroad Financial Data
- Worldwide University Expense Dataset
- Higher Education Global Costs
Attributes
Original Data Source: Global International Education Costs
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