The Institutional Data Archive on American Higher Education (IDA) contains academic data on 384 four-year colleges and universities in the United States. The IDA is one of two databases produced by the Colleges and Universities 2000 project based at the University of California, Riverside. This release, the third compilation of the IDA, is updated through academic year 2010-2011, and includes longitudinal and cross-sectional data from multiple sources. The collection is organized into nine datasets based on the unit of analysis and whether identifiers linking the data to particular institutions are present; seven of the datasets can be linked by a common identifier variable (PROJ_ID), and two cannot be linked due to confidentiality agreements. The seven identifiable datasets contain information on institutions, university systems, programs and academic departments, earned degrees, graduate schools, medical schools, and institutional academic rankings over time. Data regarding student enrollments, average SAT and ACT scores, and tuition and fees has been recorded, as well as institutional information concerning libraries, research activity, revenue and expenditures, faculty salaries, and quality rankings for program faculty. The identifiable datasets also include census information for neighborhoods surrounding IDA colleges and universities. The two non-identifiable datasets contain confidential survey responses from IDA institution presidents, chancellors, provosts, and academic vice presidents; survey questions pertained to governance structures, institutional goals and achievements, and solicited opinions on current and future issues facing the respondent's institution and higher education in general.

HEA Higher Education Student and Graduate Data. Published by Higher Education Authority. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).This data comes from the HEA's Student Record System (SRS). These are annual returns submitted to the HEA by each of the HEA-funded higher education institutions in Ireland. For further information, please visit www.hea.ie/statistics....

This study contains data obtained from one-third of a national sample of college and university faculty surveyed under the sponsorship of the Carnegie Commission on Higher Education (see CARNEGIE COMMISSION NATIONAL SURVEY OF HIGHER EDUCATION: FACULTY STUDY, 1969 [ICPSR 7501]). The original data were collected by the Survey Research Center, University of California at Berkeley, while the subsample was provided by the Social Science Data Center at the University of Connecticut. The subsample for the present study was randomly drawn and the 20,008 selected respondents were weighted to 148,372. The variables provide information on the faculty's social and educational backgrounds and professional activities, their views on a wide range of social and political issues, and opinions on educational policy. Demographic data cover age, sex, race, marital status, number of children, religion, income, and parents' levels of education and occupations. In addition to the original survey data, this study includes a number of derived measures in the form of indexes and scales.

There were approximately 18.58 million college students in the U.S. in 2022, with around 13.49 million enrolled in public colleges and a further 5.09 million students enrolled in private colleges. The figures are projected to remain relatively constant over the next few years.

What is the most expensive college in the U.S.? The overall number of higher education institutions in the U.S. totals around 4,000, and California is the state with the most. One important factor that students – and their parents – must consider before choosing a college is cost. With annual expenses totaling almost 78,000 U.S. dollars, Harvey Mudd College in California was the most expensive college for the 2021-2022 academic year. There are three major costs of college: tuition, room, and board. The difference in on-campus and off-campus accommodation costs is often negligible, but they can change greatly depending on the college town.

The differences between public and private colleges Public colleges, also called state colleges, are mostly funded by state governments. Private colleges, on the other hand, are not funded by the government but by private donors and endowments. Typically, private institutions are  much more expensive. Public colleges tend to offer different tuition fees for students based on whether they live in-state or out-of-state, while private colleges have the same tuition cost for every student.

Higher Education Load, Enrolments and Completions, 2004 onwards For data prior to 2003 please contact university-statistics@dese.gov.au Higher Education Load, Enrolments and Completions, 2004 onwards For data prior to 2003 please contact university-statistics@dese.gov.au

The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.

There is no description for this dataset.

Collaboratory is a software product developed and maintained by HandsOn Connect Cloud Solutions. It is intended to help higher education institutions accurately and comprehensively track their relationships with the community through engagement and service activities. Institutions that use Collaboratory are given the option to opt-in to a data sharing initiative at the time of onboarding, which grants us permission to de-identify their data and make it publicly available for research purposes. HandsOn Connect is committed to making Collaboratory data accessible to scholars for research, toward the goal of advancing the field of community engagement and social impact.Collaboratory is not a survey, but is instead a dynamic software tool designed to facilitate comprehensive, longitudinal data collection on community engagement and public service activities conducted by faculty, staff, and students in higher education. We provide a standard questionnaire that was developed by Collaboratory’s co-founders (Janke, Medlin, and Holland) in the Institute for Community and Economic Engagement at UNC Greensboro, which continues to be closely monitored and adapted by staff at HandsOn Connect and academic colleagues. It includes descriptive characteristics (what, where, when, with whom, to what end) of activities and invites participants to periodically update their information in accordance with activity progress over time. Examples of individual questions include the focus areas addressed, populations served, on- and off-campus collaborators, connections to teaching and research, and location information, among others.The Collaboratory dataset contains data from 37 institutions beginning in March 2016and continues to grow as more institutions adopt Collaboratory and continue to expand its use. The data represent over 3,600 published activities (and additional associated content) across our user base.Please cite this data as:Medlin, Kristin and Seto, Matthew. Dataset on Higher Education Community Engagement and Public Service Activities, 2016-2021. Collaboratory [producer], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-11-01. doi: _v1.When you cite this data, please also include: ORIGINS PAPER CITATION

These data were generated as part of a two-and-a-half-year ESRC-funded research project examining the digitalisation of higher education (HE) and the educational technology (Edtech) industry in HE. Building on a theoretical lens of assetisation, it focused on forms of value in the sector, and governance challenges of digital data. It followed three groups of actors: UK universities, Edtech companies, and investors in Edtech. The researchers first sought to develop an overview of the Edtech industry in HE by building three databases on Edtech companies, investors in Edtech, and investment deals, using data downloaded from Crunchbase, a proprietary platform. Due to Crunchbase’s Terms of Service, only parts of one database are allowed to be submitted to this repository, i.e. a list of companies with the project’s classification. A report offering descriptive analysis of all three databases was produced and is submitted as well. A qualitative discursive analysis was conducted by analysing seven documents in depth. In the second phase, researchers conducted interviews with participants representing three groups of actors (n=43) and collected documents on their organisations. Moreover, a list of documents collected from Big Tech (Microsoft, Amazon, and Salesforce) were collected to contextualise the role of global digital infrastructure in HE. Due to commercial sensitivity, only lists of documents collected about investors and Big Tech are submitted to the repository. Researchers then conducted focus groups (n=6) with representatives of universities (n=19). The dataset includes transcripts of focus groups and outputs of writing by participants during the focus group. Finally, a public consultation was held via a survey, and 15 participants offered qualitative answers.

The higher education (HE) sector has been marketised for decades; but the speed, scope, and extent of marketisation has led key education scholars to conceptualise it as a global industry (Verger, Lubienski, & Steiner-Khamsi, 2016). Further, the use of technology to transform teaching and learning, as well as the profound digitalisation of universities more broadly, has led universities to collect and process an unprecedented amount of digital data. Education technology (EdTech) companies have become one of the key players in the HE industry and the UK has made EdTech one of its key pillars in its recent international education strategy (HM Government, 2019). EdTech companies are reporting unprecedented growth. In 2019, Coursera became a 'unicorn' (i.e. a company worth over $1 billion), while British-based FutureLearn secured £50 million investment by selling 50% shares of the company. Investment in EdTech is growing at an impressive rate and reached $16.3bn in 2018 (ET, 2019). While EdTech start-up companies strive to become 'unicorns' and profit from HE, so too might universities increasingly look for new ways of profiting from the wealth of digital data they produce.

The study of HE markets has so far focused on service-commodities. However, data and data products do not act like commodities. Commodities are consumed once used, but data is reproducible at almost zero marginal cost. New products and services can be created from data and monetised through subscription fees, an app, or a platform that does not transfer ownership, control, or reproduction rights to the user. Furthermore, data use creates yet more data, and the network effects increase the value of these platforms. Therefore, there is a new quality at play in the monetisation and marketisation of these digital HE products and services: 'assetization'. We are witnessing a widespread change from creating value via market exchange towards extracting value via the ownership and control of assets.

This research project aims to investigate these new processes of value creation and extraction in an HE sector that is digitalising its operations and introducing new digital solutions premised on the expansion of service fees. By introducing a focus on assets, and economic rents, this project offers a theoretically and empirically transformative approach to understand emerging HE markets and their implications for the HE sector. The assetization of HE is consequential because of the legal and technical implications for its regulation. It is also crucial to examine in any discussion about the legitimate and socially just arrangement and distribution of assets, their ownership, and their uses. The project employs an innovative, comparative, and participatory mixed-methods research design. It combines digital methods, interviews, observation, document analysis, deliberative focus groups, knowledge exchange and co-production with stakeholders, and public consultation. Data analysis will include quantitative and qualitative analysis of investment trends, comparative case studies of investors, EdTech companies and universities, and social network analysis.

The application of this...

This release includes more detail on higher education students than was published in the student statistics bulletin in January 2021.

The project uses a unique dataset collected from UK higher education institutions comprised of individual-level data on undergraduate students from the UK and EU (i.e. those potentially eligible for bursaries), including the bursary they are awarded each year, academic outcomes, prior attainment and other demographic information.

Collection consists of data from 10 English universities on bursary awards, student characteristics, and student outcomes over the period 2006-2011.
The aim is to identify the impact of bursaries on the academic outcomes of students by exploiting variation in bursary rules across institutions. This will be achieved by comparing students with similar characteristics but receiving different levels of bursary due to the institution they are attending. To account for underlying differences across universities we will exploit changes in bursary eligibility rules within a university over time. The findings should be useful for universities and policy makers when considering the role of bursaries in improving student outcomes.

Higher education bursaries and performance: annual test scores, drop out and degree outcomes Despite some £300m per year being spent on higher education bursaries in the UK, there remains no empirical research that examines the effectiveness of this element of financial aid as a means to improve student outcomes whilst at university. The aim of this project is to investigate the impact of bursaries on students’ academic outcomes – including annual test results, completion rates and degree classification.

In 2023, there were 403 institutions of higher education in the state of California. Of these 403 institutions, 250 were four-year institutions and 153 were two-year institutions. California had the most higher education institutions of any state in that year.

The dataset includes Research income and Publications data, collected from eligible higher education providers through the Higher Education Research Data Collection. The data is used to calculate …Show full descriptionThe dataset includes Research income and Publications data, collected from eligible higher education providers through the Higher Education Research Data Collection. The data is used to calculate the Research Block Grant allocations. Data is provided publicly to ensure transparency. All verified data is publicly available.

This data collection contains information on finances for a sample of postsecondary institutions in the United States. Data on financial characteristics of postsecondary institutions are taken from Finance and Consolidated surveys, collected annually. The finance data are used for reporting and projecting capital outlays of two-year and four-year colleges and universities, trends in replacements of plant assets, and performance of endowment funds. Part 1, Institutional Characteristics, includes variables on control and level of institution, religious affiliation, highest level of offering, Carnegie classification, and state FIPS codes and abbreviations. Part 2, Current Funds Revenues by Source (Part A of the survey), provides each institution's current fund revenues by source (e.g., tuition and fees, government, gifts). Part 3, Current Funds Expenditures by Function (Part B), covers expenditures for instruction, research, and plant maintenance. Part 4, Clarifying Questions (Part C), contains information on total E&G revenues and expenditures to determine what is included/excluded from reported current fund expenditures. Part 5, Clarifying Question 5 (Part C5), lists excluded financial activities by subentities. Part 6, Utility Expenditures (Part D), reports all expenditures for utilities in the operation and maintenance of the plant, auxiliary enterprises, and independent operations, excluding expenditures for hospitals. Part 7, Scholarships and Fellowship Expenditures (Part E), covers scholarships, defined as grant-in-aid, trainee stipends, tuition and fee waivers, prizes to undergraduate students, and fellowships given to graduate students. Part 8, Expenditures for Library Acquisitions (Part F), covers costs involved in acquisition of library materials. Part 9, Indebtedness on Physical Plant (Part G), reports data on indebtedness liability against the physical plant, including auxiliary enterprises facilities as well as educational and general facilities, and excluding debt issued and backed by the state government. Part 10, Details of Endowment Assets (Part H), provides information on the amounts of gross investments of endowment, term endowment, and funds functioning as endowment for the institution, and any of its foundations and other affiliated organizations. Part 11, Selected Funds Balances (Part I), includes both unrestricted and restricted funds balances. Part 12, Hospital Revenues (Part J), reports the revenues for, or generated by, major public service hospitals over which the institution has fiscal control (excluding medical schools). Part 13, Physical Plant Assets (Part K), reports the values of land, buildings, and equipment owned, rented, or used by the institution. Part 14, Consolidated Form (CN) data (Part CN), includes revenues from tuition and fees, federal, state, and local grants, contracts, and sales of educational services. It also includes instructional expenditures, scholarships, and fellowships by source of financial aid.

Abstract copyright UK Data Service and data collection copyright owner.

UNESCO is a major collector and disseminator of statistical data on education and related subjects. Its statistical activities are aimed at providing relevant, reliable and current information for development and policy-making purposes, both at the national and international levels, and the production of reliable statistical indicators for education. These indicators cover four main areas: educational population; access and participation; the efficiency and effectiveness of education; human and financial resources.
The UNESCO Education Database covers a wide range of these areas, at four main educational levels: pre-primary, primary, secondary and tertiary, in accordance with the International Standard Classification of Education (ISCED) system. This system provides standard definitions for each of the four levels of education examined. UNESCO collects and collates education data according to these definitions from approximately 200 countries, and compiles them into the Education Database time series, which is published annually.

Main Topics:

Tertiary' education is defined by UNESCO as education above secondary (school) level, and is referred to asthird' level education, according to ISCED (International Standard Classification of Education). Education at this ISCED level includes both further and higher education, and generally takes place at institutions other than schools. These educational institutions are classified in three categories: universities and equivalent degree granting institutions, distance learning' universities (similar to the <i>Open University</i> in the United Kingdom), and other third level educational institutes. <br> Topics covered in this data collection include: numbers of students and teachers, students' field of study (subject group), students and teachers by institution type (as per three categories above), andforeign' students (see also Foreign Students Statistics, SN:3698). All data are definable by gender.

The Higher Education General Information Survey (HEGIS) series was designed to provide comprehensive information on various aspects of postsecondary education in the United States and its territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands) and Department of Defense schools outside the United States. The HEGIS Fall Enrollment Component for 1973 sought enrollment data from 3,015 institutions of higher education both public and nonpublic (2-and 4-year) which is the only survey giving a national count of the numbers of students enrolled in these institutions. The data collected from the 50 states, District of Columbia, and outlying territories give counts of total enrollments by class level, sex, race, calendar system, type of accreditation, attendance status (full time vs. part time) and enrollments of first time students. All of these data are acquired in terms of head counts and full time equivalents, by state.

This dataset shows broad performance metrics for education for Maryland as a whole, from School Years 2005/2006 to 2013/2014. Data are provided by the Maryland State Department of Education (MSDE) and were originally submitted to the Governor's Office.

This dataset represents an inventory of research data services at 120 US colleges and universities. The data was collected using a systematic web content analysis process in late 2019. This dataset underlies the following report: Jane Radecki and Rebecca Springer, "Research Data Services in US Higher Education: A Web-Based Inventory," Ithaka S+R, Nov. 2020, https://doi.org/10.18665/sr.314397.

We defined research data services as any concrete, programmatic offering intended to support researchers (including faculty, postdoctoral researchers, and graduate students) in working with data, and identified services within the following campus units: library, IT department/research computing, independent research centers and facilities, academic departments, medical school, business school, and other professional schools. We also recorded whether the institution offered local high performance computing facilities. For detailed definitions, exclusions, and data collection procedures, please see the report referenced above.

Presents an overview of all aspects of higher education in the UK. It draws together data on students, staff and institutional finance, applicants via the Universities and Colleges Admission Service (UCAS), graduates and graduate destinations, student support, and international comparisons. Source agency: Business, Innovation and Skills Designation: National Statistics Language: English Alternative title: Higher Education Statistics for the United Kingdom