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 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.

School enrollment data are used to assess the socioeconomic condition of school-age children. Government agencies also require these data for funding allocations and program planning and implementation.

Data on school enrollment and grade or level attending were derived from answers to Question 10 in the 2015 American Community Survey (ACS). People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to “include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree.” Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

School enrollment is only recorded if the schooling advances a person toward an elementary school certificate, a high school diploma, or a college, university, or professional school (such as law or medicine) degree. Tutoring or correspondence schools are included if credit can be obtained from a public or private school or college. People enrolled in “vocational, technical, or business school” such as post secondary vocational, trade, hospital school, and on job training were not reported as enrolled in school. Field interviewers were instructed to classify individuals who were home schooled as enrolled in private school. The guide sent out with the mail questionnaire includes instructions for how to classify home schoolers.

Enrolled in Public and Private School – Includes people who attended school in the reference period and indicated they were enrolled by marking one of the questionnaire categories for “public school, public college,” or “private school, private college, home school.” The instruction guide defines a public school as “any school or college controlled and supported primarily by a local, county, state, or federal government.” Private schools are defined as schools supported and controlled primarily by religious organizations or other private groups. Home schools are defined as “parental-guided education outside of public or private school for grades 1-12.” Respondents who marked both the “public” and “private” boxes are edited to the first entry, “public.”

Grade in Which Enrolled – From 1999-2007, in the ACS, people reported to be enrolled in “public school, public college” or “private school, private college” were classified by grade or level according to responses to Question 10b, “What grade or level was this person attending?” Seven levels were identified: “nursery school, preschool;” “kindergarten;” elementary “grade 1 to grade 4” or “grade 5 to grade 8;” high school “grade 9 to grade 12;” “college undergraduate years (freshman to senior);” and “graduate or professional school (for example: medical, dental, or law school).”

In 2008, the school enrollment questions had several changes. “Home school” was explicitly included in the “private school, private college” category. For question 10b the categories changed to the following “Nursery school, preschool,” “Kindergarten,” “Grade 1 through grade 12,” “College undergraduate years (freshman to senior),” “Graduate or professional school beyond a bachelor’s degree (for example: MA or PhD program, or medical or law school).” The survey question allowed a write-in for the grades enrolled from 1-12.

Question/Concept History – Since 1999, the ACS enrollment status question (Question 10a) refers to “regular school or college,” while the 1996-1998 ACS did not restrict reporting to “regular” school, and contained an additional category for the “vocational, technical or business school.” The 1996-1998 ACS used the educational attainment question to estimate level of enrollment for those reported to be enrolled in school, and had a single year write-in for the attainment of grades 1 through 11. Grade levels estimated using the attainment question were not consistent with other estimates, so a new question specifically asking grade or level of enrollment was added starting with the 1999 ACS questionnaire.

Limitation of the Data – Beginning in 2006, the population universe in the ACS includes people living in group quarters. Data users may see slight differences in levels of school enrollment in any given geographic area due to the inclusion of this population. The extent of this difference, if any, depends on the type of group quarters present and whether the group quarters population makes up a large proportion of the total population. For example, in areas that are home to several colleges and universities, the percent of individuals 18 to 24 who were enrolled in college or graduate school would increase, as people living in college dormitories are now included in the universe.

Abstract (en): The American College Catalog Study Database (CCS) contains academic data on 286 four-year colleges and universities in the United States. CCS is one of two databases produced by the Colleges and Universities 2000 project based at the University of California-Riverside. The CCS database comprises a sampled subset of institutions from the related Institutional Data Archive (IDA) on American Higher Education (ICPSR 34874). Coding for CCS was based on college catalogs obtained from College Source, Inc. The data are organized in a panel design, with measurements taken at five-year intervals: academic years 1975-76, 1980-81, 1985-86, 1990-91, 1995-96, 2000-01, 2005-06, and 2010-11. The database is based on information reported in each institution's college catalog, and includes data regarding changes in major academic units (schools and colleges), departments, interdisciplinary programs, and general education requirements. For schools and departments, changes in structure were coded, including new units, name changes, splits in units, units moved to new schools, reconstituted units, consolidated units, departments reduced to program status, and eliminated units. The American College Catalog Study Database (CCS) is intended to allow researchers to examine changes in the structure of institutionalized knowledge in four-year colleges and universities within the United States. For information on the study design, including detailed coding conventions, please see the Original P.I. Documentation section of the ICPSR Codebook. The data are not weighted. Dataset 1, Characteristics Variables, contains three weight variables (IDAWT, CCSWT, and CASEWEIGHT) which users may wish to apply during analysis. For additional information on weights, please see the Original P.I. Documentation section of the ICPSR Codebook. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Response Rates: Approximately 75 percent of IDA institutions are included in CCS. For additional information on response rates, please see the Original P.I. Documentation section of the ICPSR Codebook. Four-year not-for-profit colleges and universities in the United States. Smallest Geographic Unit: state CCS includes 286 institutions drawn from the IDA sample of 384 United States four-year colleges and universities. CCS contains every IDA institution for which a full set of catalogs could be located at the initiation of the project in 2000. CCS contains seven datasets that can be linked through an institutional identification number variable (PROJ_ID). Since the data are organized in a panel format, it is also necessary to use a second variable (YEAR) to link datasets. For a brief description of each CCS dataset, please see Appendix B within the Original P.I. Documentation section of the ICPSR Codebook.There are date discrepancies between the data and the Original P.I. Documentation. Study Time Periods and Collection Dates reflect dates that are present in the data. No additional information was provided.Please note that the related data collection featuring the Institutional Data Archive on American Higher Education, 1970-2011, will be available as ICPSR 34874. Additional information on the American College Catalog Study Database (CCS) and the Institutional Data Archive (IDA) database can be found on the Colleges and Universities 2000 Web site.

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.

Analysis of ‘U.S. News and World Report’s College Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/flyingwombat/us-news-and-world-reports-college-data on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Statistics for a large number of US Colleges from the 1995 issue of US News and World Report.

Content

A data frame with 777 observations on the following 18 variables.

Private A factor with levels No and Yes indicating private or public university

Apps Number of applications received

Accept Number of applications accepted

Enroll Number of new students enrolled

Top10perc Pct. new students from top 10% of H.S. class

Top25perc Pct. new students from top 25% of H.S. class

F.Undergrad Number of fulltime undergraduates

P.Undergrad Number of parttime undergraduates

Outstate Out-of-state tuition

Room.Board Room and board costs

Books Estimated book costs

Personal Estimated personal spending

PhD Pct. of faculty with Ph.D.’s

Terminal Pct. of faculty with terminal degree

S.F.Ratio Student/faculty ratio

perc.alumni Pct. alumni who donate

Expend Instructional expenditure per student

Grad.Rate Graduation rate

Source

This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.

The dataset was used in the ASA Statistical Graphics Section’s 1995 Data Analysis Exposition.

--- Original source retains full ownership of the source dataset ---

The dataset is related to student data, from an educational research study focusing on student demographics, academic performance, and related factors. Here’s a general description of what each column likely represents:

Sex: The gender of the student (e.g., Male, Female). Age: The age of the student. Name: The name of the student. State: The state where the student resides or where the educational institution is located. Address: Indicates whether the student lives in an urban or rural area. Famsize: Family size category (e.g., LE3 for families with less than or equal to 3 members, GT3 for more than 3). Pstatus: Parental cohabitation status (e.g., 'T' for living together, 'A' for living apart). Medu: Mother's education level (e.g., Graduate, College). Fedu: Father's education level (similar categories to Medu). Mjob: Mother's job type. Fjob: Father's job type. Guardian: The primary guardian of the student. Math_Score: Score obtained by the student in Mathematics. Reading_Score: Score obtained by the student in Reading. Writing_Score: Score obtained by the student in Writing. Attendance_Rate: The percentage rate of the student’s attendance. Suspensions: Number of times the student has been suspended. Expulsions: Number of times the student has been expelled. Teacher_Support: Level of support the student receives from teachers (e.g., Low, Medium, High). Counseling: Indicates whether the student receives counseling services (Yes or No). Social_Worker_Visits: Number of times a social worker has visited the student. Parental_Involvement: The level of parental involvement in the student's academic life (e.g., Low, Medium, High). GPA: The student’s Grade Point Average, a standard measure of academic achievement in schools.

This dataset provides a comprehensive look at various factors that might influence a student's educational outcomes, including demographic factors, academic performance metrics, and support structures both at home and within the educational system. It can be used for statistical analysis to understand and improve student success rates, or for targeted interventions based on specific identified needs.

Data product is provided by ASL Marketing. It contains current college students who are attending colleges and universities nationwide. Connect with this market by: Class Year Field of Study Home/School address College Attending Ethnicity School Type Region Sports Conference Gender eSports Email

In 2022, about **** million male students were enrolled in degree-granting postsecondary institutions as undergraduates. This is compared to **** million female undergraduate students who were enrolled in that same year. By 2031, these figures are projected to increase to **** million and *** million respectively.

The Project Information Literacy (PIL) lifelong learning survey dataset was produced as part of a two-year federally funded study on relatively recent US college graduates and their information-seeking behavior for continued learning. The goal of the survey was to collect quantitative data about the information-seeking behavior of a sample of recent graduates—the strategies, techniques, information support systems, and best practices—used to support lifelong learning in post-college life. The dataset contains responses from 1,651 respondents to a 21-item questionnaire administered between October 9, 2014 and December 15, 2014. The voluntary sample of respondents consisted of relatively recent graduates, who had completed their degrees between 2007 and 2012, from one of 10 US colleges and universities in the institutional sample. Quantitative data are included in the dataset about the learning needs of relatively recent graduates as well as the information sources they used in three arenas of their post-college lives (i.e., personal life, workplace, and the communities in which they resided). Demographic information—including age, gender, major, GPA, employment status, graduate school attendance, and geographic proximity of current residence to their alma mater—is also included in the dataset for the respondents. "Staying Smart: How Today's Graduates Continue to Learn Once They Complete College," Alison J. Head, Project Information Literacy Research Report, Seattle: University of Washington Information School (January 5, 2016), 112 pages, 6.9 MB.

We know that students at elite universities tend to be from high-income families, and that graduates are more likely to end up in high-status or high-income jobs. But very little public data has been available on university admissions practices. This dataset, collected by Opportunity Insights, gives extensive detail on college application and admission rates for 139 colleges and universities across the United States, including data on the incomes of students. How do admissions practices vary by institution, and are wealthy students overrepresented?

Motivation

Education equality is one of the most contested topics in society today. It can be defined and explored in many ways, from accessible education to disabled/low-income/rural students to the cross-generational influence of doctorate degrees and tenure track positions. One aspect of equality is the institutions students attend. Consider the “Ivy Plus” universities, which are all eight Ivy League schools plus MIT, Stanford, Duke, and Chicago. Although less than half of one percent of Americans attend Ivy-Plus colleges, they account for more than 10% of Fortune 500 CEOs, a quarter of U.S. Senators, half of all Rhodes scholars, and three-fourths of Supreme Court justices appointed in the last half-century.

A 2023 study (Chetty et al, 2023) tried to understand how these elite institutions affect educational equality:

Do highly selective private colleges amplify the persistence of privilege across generations by taking students from high-income families and helping them obtain high-status, high-paying leadership positions? Conversely, to what extent could such colleges diversify the socioeconomic backgrounds of society’s leaders by changing their admissions policies?

To answer these questions, they assembled a dataset documenting the admission and attendance rate for 13 different income bins for 139 selective universities around the country. They were able to access and link not only student SAT/ACT scores and high school grades, but also parents’ income through their tax records, students’ post-college graduate school enrollment or employment (including earnings, employers, and occupations), and also for some selected colleges, their internal admission ratings for each student. This dataset covers students in the entering classes of 2010–2015, or roughly 2.4 million domestic students.

They found that children from families in the top 1% (by income) are more than twice as likely to attend an Ivy-Plus college as those from middle-class families with comparable SAT/ACT scores, and two-thirds of this gap can be attributed to higher admission rates with similar scores, with the remaining third due to the differences in rates of application and matriculation (enrollment conditional on admission). This is not a shocking conclusion, but we can further explore elite college admissions by socioeconomic status to understand the differences between elite private colleges and public flagships admission practices, and to reflect on the privilege we have here and to envision what a fairer higher education system could look like.

Data

The data has been aggregated by university and by parental income level, grouped into 13 income brackets. The income brackets are grouped by percentile relative to the US national income distribution, so for instance the 75.0 bin represents parents whose incomes are between the 70th and 80th percentile. The top two bins overlap: the 99.4 bin represents parents between the 99 and 99.9th percentiles, while the 99.5 bin represents parents in the top 1%.

Each row represents students’ admission and matriculation outcomes from one income bracket at a given university. There are 139 colleges covered in this dataset.

The variables include an array of different college-level-income-binned estimates for things including attendance rate (both raw and reweighted by SAT/ACT scores), application rate, and relative attendance rate conditional on application, also with respect to specific test score bands for each college and in/out-of state. Colleges are categorized into six tiers: Ivy Plus, other elite schools (public and private), highly selective public/private, and selective public/private, with selectivity generally in descending order. It also notes whether a college is public and/or flagship, where “flagship” means public flagship universities. Furthermore, they also report the relative application rate for each income bin within specific test bands, which are 50-point bands that had the most attendees in each school tier/category.

Several values are reported in “test-score-reweighted” form. These values control for SAT score: they are calculated separately for each SAT score value, then averaged with weights based on the distribution of SAT scores at the institution.

Note that since private schools typically don’t differentiate between in-...

Dataset - American University in the news

Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce.While researchers and practitioners have developed data systems to track detailed occupational skills, such as those established by the U.S. Department of Labor (DOL), much less effort has been made to document which of these skills are being developed in higher education at a similar granularity.Here, we fill this gap by presenting Course-Skill Atlas -- a longitudinal dataset of skills inferred from over three million course syllabi taught at nearly three thousand U.S. higher education institutions. To construct Course-Skill Atlas, we apply natural language processing to quantify the alignment between course syllabi and detailed workplace activities (DWAs) used by the DOL to describe occupations. We then aggregate these alignment scores to create skill profiles for institutions and academic majors. Our dataset offers a large-scale representation of college education's role in preparing students for the labor market.Overall, Course-Skill Atlas can enable new research on the source of skills in the context of workforce development and provide actionable insights for shaping the future of higher education to meet evolving labor demands, especially in the face of new technologies.

This dataset consists of a selection of variables extracted from the U.S. Department of Education's College Scorecard 2015/2016. For the original, raw data visit the College Scorecard webpage. This dataset includes variables about institution types, proportion of degree types awarded, student enrollments and demographics, and a number of price and revenue variables. For 2005-2006 data, see here.Note: Data is not uniformly available for all schools on all variables. Variables for which there is no data (NULL), or where data is suppressed for reasons of privacy, are indicated by 999999999.

ATTRIBUTE DESCRIPTION EXAMPLE

ID2 1

UNITIDUnit ID for institution 100654

OPEID 8-digit OPE ID for institution 100200

OPEID6 6-digit OPE ID for institution 1002

State FIPS

1

State

AL

Zip

35762

City

Normal

Institution Name

Alabama A & M University

Institution Type 1 Public 2 Private nonprofit 3 Private for-profit 1

Institution Level 1 4-year 2 2-year 3 Less-than-2-year 1

In Operation 1 true 0 false 1

Main Campus 1 true 0 false 1

Branches Count of the number of branches 1

Popular Degree 1 Predominantly certificate-degree granting 2 Predominantly associate's-degree granting 3 Predominantly bachelor's-degree granting 4 Entirely graduate-degree granting 3

Highest Degree 0 Non-degree-granting 1 Certificate degree 2 Associate degree 3 Bachelor's degree 4 Graduate degree 4

PCIP01 Percentage of degrees awarded in Agriculture, Agriculture Operations, And Related Sciences. 0.0446

PCIP03 Percentage of degrees awarded in Natural Resources And Conservation. 0.0023

PCIP04 Percentage of degrees awarded in Architecture And Related Services. 0.0094

PCIP05 Percentage of degrees awarded in Area, Ethnic, Cultural, Gender, And Group Studies. 0

PCIP09 Percentage of degrees awarded in Communication, Journalism, And Related Programs. 0

PCIP10 Percentage of degrees awarded in Communications Technologies/Technicians And Support Services. 0.0164

PCIP11 Percentage of degrees awarded in Computer And Information Sciences And Support Services. 0.0634

PCIP12 Percentage of degrees awarded in Personal And Culinary Services. 0

PCIP13 Percentage of degrees awarded in Education. 0.1268

PCIP14 Percentage of degrees awarded in Engineering. 0.1432

PCIP15 Percentage of degrees awarded in Engineering Technologies And Engineering-Related Fields. 0.0587

PCIP16 Percentage of degrees awarded in Foreign Languages, Literatures, And Linguistics. 0

PCIP19 Percentage of degrees awarded in Family And Consumer Sciences/Human Sciences. 0.0188

PCIP22 Percentage of degrees awarded in Legal Professions And Studies. 0

PCIP23 Percentage of degrees awarded in English Language And Literature/Letters. 0.0235

PCIP24 Percentage of degrees awarded in Liberal Arts And Sciences, General Studies And Humanities. 0.0423

PCIP25 Percentage of degrees awarded in Library Science. 0

PCIP26 Percentage of degrees awarded in Biological And Biomedical Sciences. 0.1009

PCIP27 Percentage of degrees awarded in Mathematics And Statistics. 0.0094

PCIP29 Percentage of degrees awarded in Military Technologies And Applied Sciences. 0

PCIP30 Percentage of degrees awarded in Multi/Interdisciplinary Studies. 0

PCIP31 Percentage of degrees awarded in Parks, Recreation, Leisure, And Fitness Studies. 0

PCIP38 Percentage of degrees awarded in Philosophy And Religious Studies. 0

PCIP39 Percentage of degrees awarded in Theology And Religious Vocations. 0

PCIP40 Percentage of degrees awarded in Physical Sciences. 0.0188

PCIP41 Percentage of degrees awarded in Science Technologies/Technicians. 0

PCIP42 Percentage of degrees awarded in Psychology. 0.0282

PCIP43 Percentage of degrees awarded in Homeland Security, Law Enforcement, Firefighting And Related Protective Services. 0.0282

PCIP44 Percentage of degrees awarded in Public Administration And Social Service Professions. 0.0516

PCIP45 Percentage of degrees awarded in Social Sciences. 0.0399

PCIP46 Percentage of degrees awarded in Construction Trades. 0

PCIP47 Percentage of degrees awarded in Mechanic And Repair Technologies/Technicians. 0

PCIP48 Percentage of degrees awarded in Precision Production. 0

PCIP49 Percentage of degrees awarded in Transportation And Materials Moving. 0

PCIP50 Percentage of degrees awarded in Visual And Performing Arts. 0.0258

PCIP51 Percentage of degrees awarded in Health Professions And Related Programs. 0

PCIP52 Percentage of degrees awarded in Business, Management, Marketing, And Related Support Services. 0.1479

PCIP54 Percentage of degrees awarded in History. 0

Admission Rate

0.6538

Average RetentionRate of retention averaged between full-time and part-time students. 0.4428

Retention, Full-Time Students

0.5779

Retention, Part-Time Students

0.3077

Completion Rate

0.1104

Enrollment Number of enrolled students 4505

Male Students Percentage of the student body that is male. 0.4617

Female Students Percentage of the student body that is female. 0.5383

White Percentage of the student body that identifies as white. 0.034

Black Percentage of the student body that identifies as African American. 0.9216

Hispanic Percentage of the student body that identifies as Hispanic or Latino. 0.0058

Asian Percentage of the student body that identifies as Asian. 0.0018

American Indian and Alaskan Native Percentage of the student body that identifies as American Indian or Alaskan Native. 0.0022

Native Hawaiian and Pacific Islander Percentage of the student body that identifies as Native Hawaiian or Pacific islander. 0.0018

Two or More Races Percentage of the student body that identifies as two or more races. 0

Non-Resident Aliens Percentage of the student body that are non-resident aliens. 0.0062

Race Unknown Percentage of the student body for whom racial identity is unknown. 0.0266

Percent Parents no HS Diploma Percentage of parents of students whose highest level of education is less than high school. 0.019298937

Percent Parents HS Diploma Percentage of parents of students whose highest level of education is high school 0.369436786

Percent Parents Post-Secondary Ed. Percentage of parents of students whose highest level of education is college or above. 0.611264277

Title IV Students Percentage of student body identified as Title IV 743

HCM2 Cash Monitoring Schools identified by the Department of Ed for Higher Cash Monitoring Level 2 0

Net Price

13435

Cost of Attendance

20809

In-State Tuition and Fees

9366

Out-of-State Tuition and Fees

17136

Tuition and Fees (Program) Tuition and fees for program-year schools NULL

Tution Revenue per Full-Time Student

9657

Expenditures per Full-Time Student

7941

Average Faculty Salary

7017

Percent of Students with Federal Loan

0.8159

Share of Students with Federal Loan

0.896382157

Share of Students with Pell Grant

0.860906217

Median Loan Principal Amount upon Entering Repayment

14600

Median Debt for Completed Students Median debt for student who completed a course of study 35000

Median Debt for Incompleted Students Median debt for student who did not complete a course of study 9500

Median Debt for Family Income $0K-$30K Median debt for students of families with less thank $30,000 income 14457

Median Debt for Family Income $30K-$75K Median debt for students of families with $30,000-$75,000 income 15000

Median Debt for Family Income over $75K Median debt for students of families with over $75,000 income 14250

Median Debt Female Students

16000

Median Debt Male Students

13750

Median Debt 1st Gen. Students Median debt for first generation college student 14307.5

Median Debt Not 1st Gen. Students Median debt for not first generation college students 14953

Cumulative Loan Debt Greater than 90% of Students (90th Percentile)

48750

Cumulative Loan Debt Greater than 75% of Students (75th Percentile)

32704

Cumulative Loan Debt Greater than 25% of Students (25th Percentile)

5500

Cumulative Loan Debt Greater than 10% of Students (10th Percentile)

3935.5

Accrediting Agency

Southern Association of Colleges and Schools Commission on Colleges

Website

www.aamu.edu/

Price Calculator

www2.aamu.edu/scripts/netpricecalc/npcalc.htm

Latitude

34.783368

Longitude

-86.568502

The Bangladeshi Universities Dataset provides information on the geographical location, administrative division, field of specialization, type and Ph.D. granting status of various universities in Bangladesh.

The "Location" column in the dataset provides the geographic location of each university in Bangladesh. This information can be used to identify universities located in different parts of the country and to analyze the distribution of higher education institutions across the regions of Bangladesh.

The "Division" column categorizes each university according to its administrative division within Bangladesh. This information can be useful for studying the distribution of higher education institutions across the administrative regions of the country and identifying any regional disparities in access to higher education.

The "Specialization" column in the dataset identifies the fields of study that each university is known for. This information can be useful for students seeking admission to universities that offer programs in their areas of interest and for researchers studying the strengths and weaknesses of higher education institutions in Bangladesh.

The "Type" column categorizes each university as either public or private. This information can be used to analyze the distribution of public and private universities in Bangladesh and to compare the quality and accessibility of education offered by each type of institution.

Finally, the "Ph.D. granting" column indicates whether each university offers doctoral programs or not. This information can be useful for students seeking advanced degrees and for researchers studying the availability and quality of doctoral education in Bangladesh.

Success.ai’s Education Marketing Data offers businesses and organizations direct access to verified contact details for educators, administrators, and marketing professionals in the education sector. Sourced from over 170 million verified professional profiles, this dataset includes work emails, direct phone numbers, and LinkedIn profiles, ensuring precise and meaningful connections with decision-makers at schools, universities, training centers, and educational service providers. By using continuously updated and AI-validated data, Success.ai empowers you to engage with the right contacts and drive targeted marketing campaigns, recruitment efforts, and partnership opportunities within the education landscape.

Why Choose Success.ai’s Education Marketing Data?

1. Comprehensive Contact Information

   • Access verified work emails, direct phone numbers, and social profiles of school administrators, university professors, department heads, and education marketers.
   • AI-driven validation ensures 99% accuracy, enabling confident outreach and reducing wasted efforts.

2. Global Reach Across Education Segments

   • Includes contacts from K-12 schools, higher education institutions, vocational training centers, e-learning platforms, and professional certification organizations.
   • Covers regions including North America, Europe, Asia-Pacific, South America, and the Middle East, ensuring a broad spectrum of educational institutions and markets.

3. Continuously Updated Datasets

   • Real-time updates guarantee that your contact data remains current, reflecting changes in roles, institutional structures, and academic priorities.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and other global privacy regulations, ensuring your outreach is both ethical and legally compliant.

Data Highlights:

• 170M+ Verified Professional Profiles: Includes education sector leaders, influencers, and key decision-makers.
• 50M Work Emails: AI-validated for seamless communication and reduced bounce rates.
• 30M Company (Institution) Profiles: Gain insights into school types, program offerings, and organizational structures.
• 700M Global Professional Profiles: Enriched datasets to support market analysis, competitive benchmarking, and strategic planning.

Key Features of the Dataset:

1. Education Decision-Maker Profiles

   • Identify and connect with principals, superintendents, deans, admissions directors, marketing managers, and department heads shaping curriculum, enrollment, and academic initiatives.

2. Advanced Filters for Precision Targeting

   • Filter by institution type, geographic region, academic level, specialty programs, or job function to refine your outreach and campaigns.
   • Tailor messaging to align with unique educational needs, cultural contexts, and policy frameworks.

3. AI-Driven Enrichment

   • Profiles are enriched with actionable data, offering insights into institutional priorities, enrollment trends, and academic focal points, enabling more personalized and effective engagement.

Strategic Use Cases:

1. Marketing and Enrollment Campaigns

   • Target admissions and marketing professionals at universities, colleges, and language schools to promote your educational products, tutoring services, or learning management systems.
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This data (Age, MEQ, BMI) is from 384 university students enrolled in health and physical exercise (HPE) courses at a mid-sized university in the West South Central United States. The data are from a two-semester period (Fall 2019 & Spring 2020) and were collated and de-identified by members of the institutional research team before being given to the research team for analysis. This study does not include data from students who opted out (the default option), students with BMI values below 14.5 kg·m-2 or above 49.4 kg·m-2, and students whose age was below 16 or above 24.

This dataset displays the location of schools that are overseen by the Bureau of Indian Education. There are 183 Bureau-funded elementary and secondary schools on 64 reservations in 23 states, serving approximately 40,000 Indian students. Of these, 55 are BIE-operated and 128 are tribally controlled under BIE contracts or grants. The Bureau also funds or operates off-reservation boarding schools and peripheral dormitories near reservations for public school students. The BIE also serves American Indian and Alaska Native post-secondary students through higher education scholarships and support funding for tribal colleges and universities. The BIE directly operates two post-secondary institutions: the Haskell Indian Nations University (HINU) in Lawrence, Kansas, and the Southwestern Indian Polytechnic Institute (SIPI) in Albuquerque, New Mexico. Native American boarding schools and dormitories were established in the United States during the late 19th and early 20th centuries. The land where the schools are located is administered by the Bureau of Indian Affairs while the facilities and there operation is under the jurisdiction of the Bureau of Indian Education. As stated in Title 25 CFR Part 32.3, BIE’s mission is to provide quality education opportunities from early childhood through life in accordance with a tribe’s needs for cultural and economic well-being, in keeping with the vast diversity of Indian tribes and Alaska Native villages as distinct cultural and governmental entities. Further, the BIE is to manifest consideration of the whole person by considering the individual's spiritual, mental, physical, and cultural aspects within his or her family and tribal or village context. The BIE school system employs thousands of teachers, administrators and support personnel, while many more work in tribal school systems.

Background and Objective: Every year thousands of applications are being submitted by international students for admission in colleges of the USA. It becomes an iterative task for the Education Department to know the total number of applications received and then compare that data with the total number of applications successfully accepted and visas processed. Hence to make the entire process easy, the education department in the US analyze the factors that influence the admission of a student into colleges. The objective of this exercise is to analyse the same.

Domain: Education

Dataset Description:

Attribute Description GRE Graduate Record Exam Scores GPA Grade Point Average Rank It refers to the prestige of the undergraduate institution. The variable rank takes on the values 1 through 4. Institutions with a rank of 1 have the highest prestige, while those with a rank of 4 have the lowest. Admit It is a response variable; admit/don’t admit is a binary variable where 1 indicates that student is admitted and 0 indicates that student is not admitted. SES SES refers to socioeconomic status: 1 - low, 2 - medium, 3 - high. Gender_male Gender_male (0, 1) = 0 -> Female, 1 -> Male Race Race – 1, 2, and 3 represent Hispanic, Asian, and African-Americ

This feature layer, utilizing data from the U.S. Department of Education (USDED), displays colleges and universities in the U.S. and its territories. The feature layer is composed of all post secondary education facilities as defined by the Integrated Post Secondary Education System (IPEDS), National Center for Education Statistics (NCES) and the USDED. Included are doctoral/research universities, masters colleges and universities, baccalaureate colleges, associates colleges, theological seminaries, medical schools and other health care professions. Also included in the data are schools of engineering and technology, business and management, art, music, design, law schools, teachers colleges, tribal colleges, and other specialized institutions.Gallaudet UniversityData currency: see Colleges and UniversitiesData downloaded from: Homeland Infrastructure Foundation-Level Data (HIFLD) > Colleges and UniversitiesData modification(s): noneFor more information: USDED; NCES; IPEDSFor feedback please contact: ArcGIScomNationalMaps@esri.comThumbnail image courtesy of: Antonio Barrera