16 datasets found
  1. Average undergraduate budgets U.S. 2024/25, by expense and institution type

    • statista.com
    Updated Mar 10, 2025
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    Statista (2025). Average undergraduate budgets U.S. 2024/25, by expense and institution type [Dataset]. https://www.statista.com/statistics/236015/undergraduate-budgets-in-the-us-2011-12-by-expense-and-institution-type/
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    Dataset updated
    Mar 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In a public two-year institution for commuters, the total undergraduate budget for the 2024/2025 academic year in the United States was 20,570 U.S. dollars, including 4,050 U.S. dollars for tuition and fees. For private, nonprofit four-year institutions where students lived on campus, the total estimated budget clocked in at 62,990 U.S. dollars, making it the most expensive option for undergraduates.

  2. Cost of International Education

    • kaggle.com
    Updated May 7, 2025
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    Adil Shamim (2025). Cost of International Education [Dataset]. https://www.kaggle.com/datasets/adilshamim8/cost-of-international-education/versions/4
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 7, 2025
    Dataset provided by
    Kaggle
    Authors
    Adil Shamim
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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

    ColumnTypeDescription
    CountrystringISO country name where the university is located (e.g., “Germany”, “Australia”).
    CitystringCity in which the institution sits (e.g., “Munich”, “Melbourne”).
    UniversitystringOfficial name of the higher-education institution (e.g., “Technical University of Munich”).
    ProgramstringSpecific course or major (e.g., “Master of Computer Science”, “MBA”).
    LevelstringDegree level of the program: “Undergraduate”, “Master’s”, “PhD”, or other certifications.
    Duration_YearsintegerLength of the program in years (e.g., 2 for a typical Master’s).
    Tuition_USDnumericTotal program tuition cost, converted into U.S. dollars for ease of comparison.
    Living_Cost_IndexnumericA normalized index (often based on global city indices) reflecting relative day-to-day living expenses (food, transport, utilities).
    Rent_USDnumericAverage monthly student accommodation rent in U.S. dollars.
    Visa_Fee_USDnumericOne-time visa application fee payable by international students, in U.S. dollars.
    Insurance_USDnumericAnnual health or student insurance cost in U.S. dollars, as required by many host countries.
    Exchange_RatenumericLocal currency units per U.S. dollar at the time of data collection—vital for currency conversion and trend analysis if rates fluctuate.

    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!

  3. f

    Model summary.

    • plos.figshare.com
    xls
    Updated Aug 14, 2025
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    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan (2025). Model summary. [Dataset]. http://doi.org/10.1371/journal.pone.0328742.t005
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    xlsAvailable download formats
    Dataset updated
    Aug 14, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Understanding public finance and budget processes has become increasingly important for the younger generation in recent years. This knowledge enables Generation Z to participate more effectively in democratic life as informed citizens. However, there is limited research on Generation Z’s awareness of public budgets in the existing literature. Therefore, the study addressed a significant gap in the public finance literature. We aimed to examine the determinants influencing the state budget awareness of Generation Z undergraduates by using the survey: “Citizens’ Budget Awareness and Effective Factors”. Data was collected from 3,972 undergraduates across all disciplines enrolled in four Turkish state universities between December 2023 and April 2024. We conducted a multiple linear regression analysis to examine the data. The main results showed that being informed about allocated public revenues for which public services, the constitutional power of the purse, budgeting processes and budget-related transactions were the determinants that most influenced the budget awareness of the students. On the contrary, being informed about the connection between taxes and public services, the Public Financial Management and Control Law No. 5018, and the amounts of public revenues within the state budget were determined as the lowest determinants influencing their awareness. Based on our results, we mainly suggested that (i) comprehensive education programmes and interactive learning should be organised in universities by using digital tools, (ii) the link between public revenues and expenditures should be explained through awareness campaigns, and (iii) budget processes should be made more transparent and accessible.

  4. o

    Scholarship Schemes for Minorities - Datasets - Open Budgets India

    • openbudgetsindia.org
    Updated Jul 12, 2021
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    (2021). Scholarship Schemes for Minorities - Datasets - Open Budgets India [Dataset]. https://openbudgetsindia.org/dataset/scholarship-schemes-for-minorities
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    Dataset updated
    Jul 12, 2021
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The objective of these schemes, viz. Pre-Matric Scholarship, Post-Matric Scholarship and Merit-cum-Means based Scholarship. is to support the education of students belonging to economically weaker sections of the minority communities by awarding scholarships. Pre-Matric Scholarship covers students from Class I to Class X, Post-Matric Scholarship covers students in higher secondary school / college / university and Merit-cum-Means Scholarship covers technical and professional courses at undergraduate and post-graduate level.

  5. f

    Beta coefficients for the budget awareness and VIF values.

    • plos.figshare.com
    xls
    Updated Aug 14, 2025
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    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan (2025). Beta coefficients for the budget awareness and VIF values. [Dataset]. http://doi.org/10.1371/journal.pone.0328742.t007
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    xlsAvailable download formats
    Dataset updated
    Aug 14, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Beta coefficients for the budget awareness and VIF values.

  6. Budget planned for organizing a bachelor party in Poland 2025

    • statista.com
    Updated Aug 19, 2025
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    Statista (2025). Budget planned for organizing a bachelor party in Poland 2025 [Dataset]. https://www.statista.com/statistics/1621482/poland-budget-for-a-bachelor-party/
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    Dataset updated
    Aug 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Poland
    Description

    In 2025, around ** percent of Polish respondents stated that they would spend up to 1,000 zloty per person on organizing a bachelor party.

  7. f

    Data from: Budget Dilemma: The quest for Stability in the Context of...

    • scielo.figshare.com
    • datasetcatalog.nlm.nih.gov
    jpeg
    Updated Jun 1, 2023
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    Camila Henriques de Paula; Wânia Candida Silva; Magnus Luiz Emmendoerfer; Luiz Antonio Abrantes (2023). Budget Dilemma: The quest for Stability in the Context of Retraction [Dataset]. http://doi.org/10.6084/m9.figshare.7483148.v1
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    jpegAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELO journals
    Authors
    Camila Henriques de Paula; Wânia Candida Silva; Magnus Luiz Emmendoerfer; Luiz Antonio Abrantes
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Abstract UniCaso is a Brazilian federal university located in the interior that participated in the organizational expansion program promoted by the government of Brazil. In this program, education is recognized constitutionally as a right of all and as a duty of the state and the family. However, after ten years, the program has not been consolidated and the government has difficulties maintaining and creating new financial conditions to support it, leading to a reduction in investments for higher education. Thus, the head managers of UniCaso faced the need to make decisions regarding the university budget and financial adjustments to minimize the negative impact on the ongoing teaching, research, and extension activities. Therefore, this case presents the dilemma from the perspective of the university's dean: what is the best way to ensure the financial stability of UniCaso in a scenario of reduced public investments? The case triggers a discussion on budgetary management and strategic planning in undergraduate and postgraduate courses of University Management, Public Management, and Accounting Sciences.

  8. Student loan forecasts, England: 2017 to 2018

    • gov.uk
    Updated Jun 28, 2018
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    Department for Education (2018). Student loan forecasts, England: 2017 to 2018 [Dataset]. https://www.gov.uk/government/statistics/student-loan-forecasts-england-2017-to-2018
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    Dataset updated
    Jun 28, 2018
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Description

    This publication contains forecasts for higher education and further education student loans in England. These include forecasts for:

    • student loan outlay
    • student loan repayments
    • student numbers
    • the proportion of student loan outlay that is subsidised by the government, known as the Resource Accounting and Budgeting (RAB) charge
    • the proportion of loan borrowers expected to fully repay their loans
    • the size of the student loan book
  9. f

    Demographic profile of participants and descriptive statistics.

    • plos.figshare.com
    xls
    Updated Aug 14, 2025
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    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan (2025). Demographic profile of participants and descriptive statistics. [Dataset]. http://doi.org/10.1371/journal.pone.0328742.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Aug 14, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Demographic profile of participants and descriptive statistics.

  10. e

    Student Income and Expenditure Survey, 2007-2008 - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Oct 20, 2023
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    (2023). Student Income and Expenditure Survey, 2007-2008 - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/9470543e-438f-5376-a5c2-2f73bb258b22
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    Dataset updated
    Oct 20, 2023
    Description

    Abstract copyright UK Data Service and data collection copyright owner. The Student Income and Expenditure Survey, 2007-2008 (SIES) was designed to collect detailed information on income and expenditure of Higher Education students and investigated issues such as student debt or hardship. The survey covered both full-time and part-time students at higher education institutions (HEI) and further education colleges (FEC), including the Open University (OU), participating in undergraduate courses during the 2007-2008 academic year. Undergraduate courses included first degree and Higher National Diplomas/Certificates (HNDs/HNCs), or in university-based postgraduate initial teacher training courses (PGCEs). The study covered 69 institutions in England and ten institutions in Wales, plus the OU. The 2007-2008 survey is the latest in a series of surveys carried out at approximately three year intervals. The methods and interview content have been kept as similar as possible to the previous wave carried out in 2004-2005, (not currently available from the UKDA) in order to make any trend comparisons as robust as possible. Main Topics: The dataset contains individual level data pertaining to students' finances including:income (support, family and friends, work, benefits, other)expenditure (living, housing, children, participation) overall financial position (borrowing – commercial and state, savings) financial well-being (missed bills, views on how finances have affected study) student attitudes and choices (future, choice of HE course, reasons for studying) Standard Measures: Standard Occupational Classification (SOC) Likert Scale Multi-stage stratified random sample Face-to-face interview Diaries 2008 AGE ASPIRATION ATTITUDES BICYCLES BOOKS CAPITAL GAINS CARE OF DEPENDANTS CARERS BENEFITS CARS CHILD DAY CARE CHILD SUPPORT PAYMENTS CHILDREN COMPACT DISC PLAYERS COMPUTERS CONSUMER GOODS COST OF LIVING COSTS COUNCIL TAX CREDIT CARD USE DEBTS DEGREES DIGITAL GAMES DISABILITIES DISEASES DISTANCE LEARNING DOMESTIC APPLIANCES DVD PLAYERS DYSLEXIA EDUCATIONAL CERTIFI... EDUCATIONAL EXPENDI... EDUCATIONAL FEES EDUCATIONAL GRANTS EDUCATIONAL VISITS EMPLOYER SPONSORED ... ETHNIC GROUPS EXPENDITURE England and Wales FAMILY BENEFITS FIELDS OF STUDY FINANCIAL COMMITMENTS FINANCIAL DIFFICULTIES FINANCIAL EXPECTATIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FLEXIBLE WORKING TIME FREE SCHOOL MEALS FULL TIME EMPLOYMENT FURTHER EDUCATION GIFTS HEARING IMPAIRMENTS HIGHER EDUCATION HIGHER NATIONAL CER... HIRE PURCHASE HOME OWNERSHIP HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD INCOME HOUSEHOLDS HOUSING BENEFITS HOUSING FINANCE HOUSING TENURE Higher and further ... INCOME Income JOB SEEKER S ALLOWANCE LOANS MARITAL STATUS MENTAL DISORDERS MOBILE PHONES MORTGAGE ARREARS MORTGAGES MOTORCYCLES NATIONAL IDENTITY PARENT EDUCATION PARENTS PART TIME COURSES PART TIME EMPLOYMENT PENSION BENEFITS PERSONAL DEBT REPAY... PERSONAL FINANCE MA... PUBLIC SERVICES PURCHASING RELIGIOUS AFFILIATION RENTS ROAD TAX SALE OF PERSONAL PO... SANDWICH COURSES SCHOLARSHIPS SEASONAL EMPLOYMENT SELF EMPLOYED SICKNESS AND DISABI... SMALL ELECTRICAL AP... SOCIAL SECURITY BEN... SPOUSE S ECONOMIC A... SPOUSES STATE RETIREMENT PE... STATUS IN EMPLOYMENT STUDENT ATTITUDE STUDENT EMPLOYMENT STUDENT HOUSING STUDENT LOANS STUDENT TRANSPORTATION STUDENTS COLLEGE STUDY PERIODS SUPERVISORY STATUS TEACHER QUALIFICATIONS TELEPHONES TELEVISION TELEVISION LICENCES TRANSPORT FARES UNEARNED INCOME UNIVERSITY COURSES VISION IMPAIRMENTS WHEELCHAIRS WORKING CONDITIONS WRITING MATERIALS property and invest...

  11. Student loan forecasts, England: 2021 to 2022

    • gov.uk
    Updated Jul 14, 2022
    + more versions
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    Department for Education (2022). Student loan forecasts, England: 2021 to 2022 [Dataset]. https://www.gov.uk/government/statistics/student-loan-forecasts-england-2021-to-2022
    Explore at:
    Dataset updated
    Jul 14, 2022
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Area covered
    England
    Description

    This publication contains forecasts for higher education and further education student loans in England. These include forecasts for:

    • average costs for undergraduate students
    • student entrant borrower numbers
    • student loan outlay
    • student loan repayments
    • the proportion of student loan outlay that is subsidised by government, known as the resource accounting and budgeting (RAB) charge
    • the total outstanding balances on student loans
  12. e

    Capital Budgeting

    • paper.erudition.co.in
    html
    Updated Nov 4, 2020
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    Einetic (2020). Capital Budgeting [Dataset]. https://paper.erudition.co.in/makaut/bachelor-of-computer-applications/5/management-and-accounting
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    htmlAvailable download formats
    Dataset updated
    Nov 4, 2020
    Dataset authored and provided by
    Einetic
    License

    https://paper.erudition.co.in/termshttps://paper.erudition.co.in/terms

    Description

    Question Paper Solutions of chapter Capital Budgeting of Management and Accounting, 5th Semester , Bachelor of Computer Applications

  13. f

    First 12 items used in model as dependent variables.

    • plos.figshare.com
    xls
    Updated Aug 14, 2025
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    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan (2025). First 12 items used in model as dependent variables. [Dataset]. http://doi.org/10.1371/journal.pone.0328742.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Aug 14, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    First 12 items used in model as dependent variables.

  14. e

    Budget and Budgetary Control

    • paper.erudition.co.in
    html
    Updated Sep 25, 2020
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    Einetic (2020). Budget and Budgetary Control [Dataset]. https://paper.erudition.co.in/3/bachelors-of-commerce-general/semester-iv/cost-and-management-accounting-ii
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    htmlAvailable download formats
    Dataset updated
    Sep 25, 2020
    Dataset authored and provided by
    Einetic
    License

    https://paper.erudition.co.in/termshttps://paper.erudition.co.in/terms

    Description

    Question Paper Solutions of chapter Budget and Budgetary Control of Cost and Management Accounting II, Semester IV , Bachelors of Commerce (General)

  15. f

    Descriptive analysis of independent and dependent variables.

    • plos.figshare.com
    xls
    Updated Aug 14, 2025
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    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan (2025). Descriptive analysis of independent and dependent variables. [Dataset]. http://doi.org/10.1371/journal.pone.0328742.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Aug 14, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Gonca Güngör Göksu; Erdal Eroğlu; Cihan Yüksel; Durdane Küçükaycan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Descriptive analysis of independent and dependent variables.

  16. c

    Educational Software market is valued at USD 124.38 Billion in 2022!

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Jun 15, 2024
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    Cognitive Market Research (2024). Educational Software market is valued at USD 124.38 Billion in 2022! [Dataset]. https://www.cognitivemarketresearch.com/educational-software-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jun 15, 2024
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    The Educational Software market is valued at USD 124.38 Billion in 2022 and will be USD 189.73 Billion by 2030 with a CAGR of 5.4% during the forecast period of 2023-2030. Factors Impacting the Educational Software Market

    Growing online education to support market expansion
    

    In the field of higher education, online learning has begun to accelerate significantly. The popularity of online learning platforms is primarily driven by the availability of high-speed internet, the rising use of personal computing devices, and government initiatives towards digital learning. Distance learning has accelerated online teaching in North America. Many institutions now offer fully or partially online programs. In 2019, Northeastern University reported 1.46 million students enrolled in online four-year undergraduate programs, 774,000 in two-year programs, and 869,000 in graduate-level courses.

    Growing investment in education boosts the market expansion 
    

    India's continued attempts to provide affordable internet connectivity have made it possible for businesses to communicate with the public online. To close the resource gap between education infrastructure and available resources, the education sector is also incorporating the most recent technologies. To make learning experiences for students more engaging, EdTech solutions incorporate AR and VR. The increasing adoption of AI and machine learning leads to personalized eLearning experiences. Machine learning algorithms predict outcomes based on past data, enabling learners to access content tailored to their interests. EdTech solutions use AI and ML to deliver customized eLearning content. AI can also help teachers personalize education for each student, identify and address learning gaps, and provide real-time feedback. Governments worldwide have increased their education budgets, with most countries investing 3-3.5% of their GDP in education.

    Restraint of the Educational Software market

    Growing cyber-attacks on educational institutions and businesses
    

    To build individualized student goals and to make strategic decisions ETech collects data. Insufficient network security makes it possible for hackers to gain access to sensitive data that is being transmitted. It might infringe on the person in question's privacy and put their safety in danger. While copyright laws forbid data exploitation, politicians around the world prioritize privacy concerns and address public outrage. The number of attacks on institutions of higher learning has significantly increased recently, which is limiting the expansion of the market. What is Educational Software?

    The first desktop computers practically heralded the arrival of educational software, or computer programs created for the aim of teaching and learning. Early on, educators saw this promise, and many schools bought computers before the majority of American homes did. Applications for education then significantly surged. Software for educational purposes comes in a range of shapes, prices, and uses. There are programs available to teach certain preschoolers the English alphabet, letter sounds, and grammar. Other programs focus on helping students build strong writing skills or present mathematical ideas to students of all grade levels. Programs that teach professionals the specifics of their employment include flight simulators. Still, other programs referred to as Learning Management Systems (LMSs), are created for use by certain grades in whole school districts for teaching or evaluation purposes; these frequently incorporate access to a software vendor's website for full services.

  17. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista (2025). Average undergraduate budgets U.S. 2024/25, by expense and institution type [Dataset]. https://www.statista.com/statistics/236015/undergraduate-budgets-in-the-us-2011-12-by-expense-and-institution-type/
Organization logo

Average undergraduate budgets U.S. 2024/25, by expense and institution type

Explore at:
Dataset updated
Mar 10, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

In a public two-year institution for commuters, the total undergraduate budget for the 2024/2025 academic year in the United States was 20,570 U.S. dollars, including 4,050 U.S. dollars for tuition and fees. For private, nonprofit four-year institutions where students lived on campus, the total estimated budget clocked in at 62,990 U.S. dollars, making it the most expensive option for undergraduates.

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