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Institute of Education Sciences

Using IPEDS Data: Available Tools and Considerations for Use

The Integrated Postsecondary Education Data System (IPEDS) contains comprehensive data on postsecondary institutions. IPEDS gathers information from every college, university, and technical and vocational institution that participates in federal student financial aid programs. The Higher Education Act of 1965, as amended, requires institutions that participate in federal student aid programs to report data on enrollments, program completions, graduation rates, faculty and staff, finances, institutional prices, and student financial aid.

These data are made available to the public in a variety of ways via the IPEDS Use the Data webpage. This blog post provides a description of available IPEDS data tools as well as considerations for determining the appropriate tool to use.


Available Data Tools

College Navigator

College Navigator is a free consumer information tool designed to help students, parents, high school counselors, and others access information about postsecondary institutions.

Note that this tool can be found on the Find Your College webpage (under "Search for College"), along with various other resources to help users plan for college.

IPEDS provides data tools for a variety of users that are organized into three general categories: (1) Search Existing Data, (2) Create Custom Data Analyses, and (3) Download IPEDS Data.

Search Existing Data

Users can search for aggregate tables, charts, publications, or other products related to postsecondary education using the Data Explorer or access IPEDS data via NCES publications like the Digest of Education Statistics or the Condition of Education.

Create Custom Data Analyses

Several data tools allow users to create their own custom analyses with frequently used and derived variables (Data Trends) or all available data collected within IPEDS (Statistical Tables). Users can also customize tables for select subgroups of institutions (Summary Tables). Each of these options allows users to generate analyses within the limitations of the tool itself.

For example, there are three report types available under the Data Feedback Report (DFR) tool. User can

  1. select data from the most recent collection year across frequently used and derived variables to create a Custom DFR;
     
  2. create a Statistical Analysis Report using the variables available for the Custom DFR; and
     
  3. access the NCES developed DFR for any institution.

Download IPEDS Data

Other data tools provide access to raw data through a direct download (Complete Data Files) or through user selections in the IPEDS Custom Data Files tool. In addition, IPEDS data can be downloaded for an entire collection year for all survey components via the Access Database.

IPEDS Data Tools Help

The IPEDS Data Tools User Manual is designed to help guide users through the various functions, processes, and abundant capabilities of IPEDS data tools. The manual contains a wealth of information, hints, tips, and insights for using the tools.

 

Data Tool Considerations

Users may consider several factors—related to both data selection and data extraction—when determining the right tool for a particular question or query.

Data Selection

  1. Quick access – Accessing data in a few steps may be helpful for users who want to find data quickly. Several data tools provide data quickly but may be limited in their selection options or customizable output.

  2. Data release – IPEDS data are released to the public in two phases: Provisional and Final. Provisional data have undergone quality control procedures and imputation for missing data but have not been updated based on changes within the Prior Year Revision System. Final data reflect changes made within the Prior Year Revision System and additional quality control procedures and will not change. Some tools allow users to access only final data. Table 1 summarizes how provisional and final data are used by various data tools. The IPEDS resource page “Timing of IPEDS Data Collection, Coverage, and Release Cycle” provides more information on data releases.


    Table 1. How provisional and final data are used in various data tools

  1. Select institutions – Users may want to select specific institutions for their analyses. Several tools allow users to limit the output for a selected list of institutions while others include all institutions in the output.
     
  2. Multiple years – While some tools provide a single year of data, many tools provide access to multiple years of data in a single output.
     
  3. Raw data – Some data tools provide access to the raw data as submitted to IPEDS. For example, Look Up an Institution allows users access to survey forms submitted by an institution.
     
  4. Institution-level data – Many data tools provide data at the institution level, since this is the unit of analysis within the IPEDS system.
     
  5. All data available – Many data tools provide access to frequently used and derived variables, but others provide access to the entirety of variables collected within the IPEDS system.

Data Extraction

  1. Save/upload institutions – Several data tools allow a user to create and download a list of institutions, which can be uploaded in a future session.

  2. Save/upload variables – Two data tools allow a user to save the variables selected and upload in a future session.
     
  3. Export data – Many data tools allow a user to download data into a spreadsheet, while others provide information within a PDF. Note that several tools have limitations on the number of variables that can be downloaded in a session (e.g., Compare Institutions has a limit of 250 variables).
     
  4. Produce visuals – Several data tools produce charts, graphs, or other visualizations. For example, Data Trends provides users with the opportunity to generate a bar or line chart and text table.


Below is a graphic that summarizes these considerations for each IPEDS data tool (click the image to enlarge it). 

 

By Tara B. Lawley, NCES, and Eric S. Atchison, Arkansas State University and Association for Institutional Research IPEDS Educator

Unlocking Opportunities: Understanding Connections Between Noncredit CTE Programs and Workforce Development in Virginia

With rapid technological advances, the U.S. labor market exhibits a growing need for more frequent and ongoing skill development. Community college noncredit career and technical education (CTE) programs that allow students to complete workforce training and earn credentials play an essential role in providing workers with the skills they need to compete for jobs in high-demand fields. Yet, there is a dearth of research on these programs because noncredit students are typically not included in state and national postsecondary datasets. In this guest blog for CTE Month, researchers Di Xu, Benjamin Castleman, and Betsy Tessler discuss their IES-funded exploration study in which they build on a long-standing research partnership with the Virginia Community College System and leverage a variety of data sources to investigate the Commonwealth’s FastForward programs. These programs are noncredit CTE programs designed to lead to an industry-recognized credential in one of several high-demand fields identified by the Virginia Workforce Board.

In response to the increasing demand for skilled workers in the Commonwealth, the Virginia General Assembly passed House Bill 66 in 2016 to establish the New Economy Workforce Credential Grant Program (WCG) with the goal of providing a pay-for-performance model for funding noncredit training. The WCG specifically funds FastForward programs that lead to an industry-recognized credential in a high-demand field in the Commonwealth. Under this model, funding is shared between the state, students, and training institutions based on student performance, with the goal of ensuring workforce training is affordable for Virginia residents. An important implication of WCG is that it led to systematic, statewide collection of student-level data on FastForward program enrollment, program completion, industry credential attainment, and labor market performance. Drawing on these unique data, coupled with interviews with key stakeholders, we generated findings on the characteristics of FastForward programs, as well as the academic and labor market outcomes of students enrolled in these programs. We describe the preliminary descriptive findings below.

FastForward programs enroll a substantially different segment of the population from credit-bearing programs and offer a vital alternative route to skill development and workforce opportunities, especially for demographic groups often underrepresented in traditional higher education. FastForward programs in Virginia enroll a substantially higher share of Black students, male students, and older students than short-duration, credit-bearing programs at community colleges that typically require one year or less to complete. Focus groups conducted with FastForward students at six colleges indicate that the students were a mix of workers sent by their employers to learn specific new skills and students who signed up for a FastForward program on their own. Among the latter group were older career changers and recent high school graduates, many of whom had no prior college experience and were primarily interested in landing their first job in their chosen field. Moreover, 61% of FastForward participants have neither prior nor subsequent enrollment in credit-bearing programs, highlighting the program’s unique role in broadening access to postsecondary education and career pathways.

FastForward programs offer an alternative path for students who are unsuccessful in credit-bearing programs. The vast majority of students (78%) enrolled in only one FastForward program, with the average enrollment duration of 1.5 quarters, which is notably shorter than most traditional credit-bearing programs. While 36% have prior credit-bearing enrollment, fewer than 20% of these students earned a degree or certificate from it, and less than 12% of FastForward enrollees transitioned to credit-bearing training afterward. Interviews with administrators and staff indicated that while some colleges facilitate noncredit-to-credit pathways by granting credit for prior learning, others prioritize employment-focused training and support over stackable academic pathways due to students’ primary interest in seeking employment post-training.

FastForward programs have a remarkable completion rate and are related to high industry credential attainment rates. Over 90% of students complete their program, with two-thirds of students obtaining industry credentials. Student focus groups echoed this success. They praised the FastForward program and colleges for addressing both their tuition and non-tuition needs. Many students noted that they had not envisioned themselves as college students and credited program staff, financial aid, and institutional support with helping them to be successful.

Earning an industry credential through FastForward on average increases quarterly earnings by approximately $1,000. In addition, industry credentials also increase the probability of being employed by 2.4 percentage points on average. We find substantial heterogeneity in economic return across different fields of study, where the fields of transportation (for example, commercial driver’s license) and precision production (for example, gas metal arc welding) seem to be associated with particularly pronounced earnings premiums. Within programs, we do not observe significant heterogeneity in economic returns across student subgroups.

What’s Next?

In view of the strong economic returns associated with earning an industry credential and the noticeable variation in credential attainment between training institutions and programs, our future exploration intends to unpack the sources of variation in program-institution credential attainment rates and to identify specific program-level factors that are within the control of an institution and which are associated with higher credential rates and lower equity gaps. Specifically, we will collect additional survey data from the top 10 most highly-enrolled programs at the Virginia Community College System (VCCS) that will provide more nuanced program-level information and identify which malleable program factors are predictive of higher credential attainment rates, better labor market outcomes, and smaller equity gaps associated with these outcomes.


Di Xu is an associate professor in the School of Education at UC, Irvine, and the faculty director of UCI’s Postsecondary Education Research & Implementation Institute.

Ben Castleman is the Newton and Rita Meyers Associate Professor in the Economics of Education at the University of Virginia.

Betsy Tessler is a senior associate at MDRC in the Economic Mobility, Housing, and Communities policy area.

Note: A team of researchers, including Kelli Bird, Sabrina Solanki, and Michael Cooper contributed jointly to the quantitative analyses of this project. The MDRC team, including Hannah Power, Kelsey Brown, and Mark van Dok, contributed to qualitative data collection and analysis. The research team is grateful to the Virginia Community College System (VCCS) for providing access to their high-quality data. Special thanks are extended to Catherine Finnegan and her team for their valuable guidance and support throughout our partnership.

This project was funded under the Postsecondary and Adult Education research topic; questions about it should be directed to program officer James Benson (James.Benson@ed.gov).

This blog was produced by Corinne Alfeld (Corinne.Alfeld@ed.gov), NCER program officer for the CTE research topic.

IES Makes Three New Awards to Accelerate Breakthroughs in the Education Field

Through the Transformative Research in the Education Sciences Grants program (ALN 84.305T), IES  invests in innovative research that has the potential to make dramatic advances towards solving seemingly intractable problems and challenges in the education field, as well as to accelerate the pace of conducting education research to facilitate major breakthroughs. In the most recent FY 2024 competition for this program, IES invited applications from partnerships between researchers, product developers, and education agencies to propose transformative solutions to major education problems that leverage advances in technology combined with research insights from the learning sciences.

IES is thrilled to announce that three grants have been awarded in the FY 2024 competition. Building on 20 years of IES research funding to lay the groundwork for advances, these three projects focus on exploring potentially transformative uses of generative artificial intelligence (AI) to deliver solutions that can scale in the education marketplace if they demonstrate positive impacts on education outcomes. The three grants are:

Active Learning at Scale (Active L@S): Transforming Teaching and Learning via Large-Scale Learning Science and Generative AI

Awardee: Arizona State University (ASU; PI: Danielle McNamara)

The project team aims to solve the challenge that postsecondary learners need access to course materials and high-quality just-in-time generative learning activities flexibly and on-the-go.  The solution will be a mobile technology that uses interactive, research-informed, and engaging learning activities created on the fly, customized to any course content with large language models (LLMs). The project team will leverage two digital learning platforms from the SEERNet networkTerracotta and ASU Learning@Scale – to conduct research and will include over 100,000 diverse students at ASU, with replication studies taking place at Indiana University (IU). IES funding has supported a large portion of the research used to identify the generative learning activities the team will integrate into the system—note-taking, self-explanation, summarization, and question answering (also known as retrieval practice). The ASU team includes in-house technology developers and researchers, and they are partnering with researchers at IU and developers at INFLO and Clevent AI Technology LLC. The ASU and IU teams will have the educator perspective represented on their teams, as these universities provide postsecondary education to large and diverse student populations.

Talking Math: Improving Math Performance and Engagement Through AI-Enabled Conversational Tutoring

Awardee: Worcester Polytechnic Institute (PI: Neil Heffernan)

The project team aims to provide a comprehensive strategy to address persistent achievement gaps in math by supporting students during their out-of-school time. The team will combine an evidence-based learning system with advances in generative AI to develop a conversational AI tutor (CAIT– pronounced as “Kate”) to support independent math practice for middle school students who struggle with math, and otherwise, may not have access to after-school tutoring. CAIT will be integrated into ASSISTments, a freely available, evidence-based online math platform with widely used homework assignments from open education resources (OER). This solution aims to dramatically improve engagement and math learning during independent math problem-solving time. The team will conduct research throughout the product development process to ensure that CAIT is effective in supporting math problem solving and is engaging and supportive for all students. ASSISTments has been used by over 1 million students and 30,000 teachers, and IES has supported its development and efficacy since 2003. The project team includes researchers and developers at Worcester Polytechnic Institute and the ASSISTments Foundation, researchers from WestEd, educator representation from Greater Commonwealth Virtual School, and a teacher design team.

Scenario-Based Assessment in the age of generative AI: Making space in the education market for alternative assessment paradigm

Awardee: University of Memphis (PI: John Sabatini)

Educators face many challenges building high-quality assessments aligned to course content, and traditional assessment practices often lack applicability to real world scenarios. To transform postsecondary education, there needs to be a shift in how knowledge and skills are assessed to better emphasize critical thinking, complex reasoning, and problem solving in practical contexts. Supported in large part by numerous IES-funded projects, including as part of the Reading for Understanding Initiative, the project team has developed a framework for scenario-based assessments (SBAs). SBAs place knowledge and skills into a practical context and provide students with the opportunity to apply their content knowledge and critical thinking skills. The project team will leverage generative AI along with their framework for SBAs to create a system for postsecondary educators to design and administer discipline-specific SBAs with personalized feedback to students, high levels of adaptivity, and rich diagnostic information with little additional instructor effort. The project team includes researchers, developers, and educators at University of Memphis and Georgia State University, researchers and developers at Educational Testing Service (ETS), and developers from multiple small businesses including Capti/Charmtech, MindTrust, Caimber/AMI, and Workbay who will participate as part of a technical advisory group.

We are excited by the transformative potential of these projects and look forward to seeing what these interdisciplinary teams can accomplish together. While we are hopeful the solutions they create will make a big impact on learners across the nation, we will also share lessons learned with the field about how to build interdisciplinary partnerships to conduct transformative research and development.


For questions or to learn more about the Transformative Research in the Education Sciences grant program, please contact Erin Higgins (Erin.Higgins@ed.gov), Program Lead for the Accelerate, Transform, Scale Initiative.

NCES Presentation at National HBCU Week Conference

In NCES’s recently released Strategic Plan, Goal 3 identifies our commitment to foster and leverage beneficial partnerships. To fulfill that goal, NCES participates in multiple conferences and meetings throughout the year. Recently, NCES participated in the National Historically Black Colleges and Universities (HBCU) Week Conference. NCES’s presentation at this conference helps us to establish a dialogue with HBCUs and develop partnerships to address critical issues in education.

NCES Commissioner Peggy G. Carr kicked off the presentation with an overview of HBCU data—such as student characteristics, enrollment, and financial aid. Then, NCES experts explored how data from various NCES surveys can help researchers, educators, and policymakers better understand the condition and progress of HBCUs. Read on to learn about these surveys.

 

Integrated Postsecondary Education Data System (IPEDS)

The Integrated Postsecondary Education Data System (IPEDS) is an annual administrative data collection that gathers information from more than 6,000 postsecondary institutions, including 99 degree-granting, Title IV–eligible HBCUs (in the 2021–22 academic year).

The data collected in IPEDS includes information on institutional characteristics and resources; admissions and completions; student enrollment; student financial aid; and human resources (i.e., staff characteristics). These data are disaggregated, offering insights into student and employee demographics by race/ethnicity and gender, students’ age categories, first-time/non-first-time enrollment statuses, and full-time/part-time attendance intensity.

Data from IPEDS can be explored using various data tools—such as Data Explorer, Trend Generator, and College Navigator—that cater to users with varying levels of data knowledge and varying data needs.

 

National Postsecondary Student Aid Study (NPSAS)

The National Postsecondary Student Aid Study (NPSAS) is a nationally representative study that examines the characteristics of students in postsecondary institutions—including HBCUs—with a special focus on how they finance their education. NPSAS collects data on the percentage of HBCU students receiving financial aid and the average amounts received from various sources (i.e., federal, state, and institution) by gender and race/ethnicity.

Conducted every 3 or 4 years, this study combines data from student surveys, student-level school records, and other administrative sources and is designed to describe the federal government’s investment in financing students’ postsecondary education.

Data from NPSAS can be explored using DataLab and PowerStats.

 

National Teacher and Principal Survey (NTPS)

The National Teacher and Principal Survey (NTPS) is the U.S. Department of Education’s primary source of information on K–12 public and private schools from the perspectives of teachers and administrators. NTPS consists of coordinated surveys of schools, principals, and teachers and includes follow-up surveys to study principal and teacher attrition.

Among many other topics, NTPS collects data on the race/ethnicity of teachers and principals. These data—which show that Black teachers and principals make up a relatively small portion of the K–12 workforce—can be used to explore the demographics and experiences of teachers and principals. NTPS provides postsecondary institutions, like HBCUs, a snapshot of the preK–12 experiences of students and staff.

Data from NTPS can be explored using DataLab and PowerStats.

 

National Assessment of Educational Progress (NAEP)

The National Assessment of Educational Progress (NAEP)—also known as the Nation’s Report Card—is the the largest nationally representative and continuing assessment of what students in public and private schools in the United States know and are able to do in various subjects.

Main NAEP assesses students in grades 4, 8, and 12 in subjects like reading, mathematics, science, and civics, while NAEP Long-Term Trend assesses 9-, 13-, and 17-year-olds in reading and mathematics.

Among many other topics, NAEP collects data on students by race/ethnicity. These data can help to shed light on students’ experiences, academic performance, and level of preparedness before they enroll in HBCUs.

Data from NAEP can be explored using the NAEP Data Explorer.

 

To explore more HBCU data from these and other NCES surveys—including enrollment trends from 1976 to 2021—check out this annually updated Fast Fact. Be sure to follow NCES on X, Facebook, LinkedIn, and YouTube and subscribe to the NCES News Flash to stay up to date on the latest from NCES.

 

By Megan Barnett, AIR

Education at a Glance 2023: Putting U.S. Data in a Global Context

International comparisons provide reference points for researchers and policy analysts to understand trends and patterns in national education data and are very important as U.S. students compete in an increasingly global economy.

Education at a Glance (EAG), an annual publication produced by the Organization for Economic Cooperation and Development (OECD), provides data on the structure, finances, and progress of education systems in 38 OECD countries—including the United States—as well as a number of OECD accession and partner countries. Data presented in EAG on topics of high policy interest in the United States are also featured in NCES reports, including the Condition of Education and Digest of Education Statistics.  

The recently released 2023 edition of EAG shows that the United States is above the international average on some measures, such as funding of postsecondary education, but lags behind in others, such as participation in early childhood education and care (ECEC). The 2023 report also features a Spotlight on Vocational Education and Training as well as interactive data dashboards on ECEC systems, upper secondary education systems, and educational support for Ukrainian refugees.


Spotlight on Vocational Education and Training (VET)

Each EAG edition centers on a particular theme of high policy relevance in OECD countries. The focus of this year’s report is VET programs, which look very different in the United States compared with many other OECD countries. Unlike in many OECD countries, most high schools in the United States do not offer a separate, distinct vocational track at the upper secondary (high school) level. Instead, vocational education is available as optional career and technical education (CTE) courses throughout high school. Regardless of whether they choose to take CTE courses, all U.S. students who complete high school have the same potential to access postsecondary programs. In other OECD countries, selecting a vocational track at this level may lead to different postsecondary opportunities. Check out the 2023 EAG Spotlight for an overview of VET programs across OECD countries.


Highlights From EAG 2023

Below is a selection of topics from the EAG report highlighting how key education benchmarks in the United States compare with other OECD countries.


Postsecondary Educational Attainment

The percentage of U.S. 25- to 34-year-olds with a postsecondary degree increased by 13 percentage points between 2000 and 2022, reaching 51 percent (the OECD average in 2022 was 47 percent) (Table A1.3).1 In this age group in the United States, higher percentages of women than men attained a postsecondary degree (56 vs. 46 percent) (Table A1.2). Across OECD countries, the average postsecondary educational attainment gap between 25- to 34-year-old men and women in 2022 (13 percentage points) was wider than the gap in the United States (10 percentage points). In the United States, the postsecondary attainment rate for 25- to 34-year-old men was 5 percentage points higher than the OECD average, and the attainment rate for women was 3 percentage points higher than the OECD average.


Figure 1. Percentage of 25- to 34-year-olds with a postsecondary degree, by OECD country: 2022

[click to enlarge image]

Data include a small percentage of adults with lower levels of attainment.
Year of reference differs from 2022. Refer to the source table for more details.
SOURCE: OECD (2023), Table A1.3. See Source section for more information and Annex 3 for notes.


International Student Enrollment

The United States is the top OECD destination country for international students enrolling in postsecondary education. In 2021, some 833,204 foreign students were enrolled in postsecondary programs in the United States, representing 13 percent of the international education market share (Table B6.1).2 In comparison, the United Kingdom had the second highest number of international students enrolled in postsecondary education in 2021, representing 9 percent of the international education market share. Interestingly, when examining enrollment trends over the past 3 years (2019 to 2021), foreign student enrollment decreased by 143,649 students (15 percent) in the United States but increased by 111,570 students (23 percent) in the United Kingdom. International student enrollment during these years was likely affected by the coronavirus pandemic, which had large impacts on global travel in 2020 and 2021.


Education Spending

U.S. spending on education is relatively high across all levels of education compared with the OECD average. The largest difference is in postsecondary spending, where the United States spent $36,172 per full-time postsecondary student in 2020, the second highest amount after Luxembourg ($53,421) and nearly double the OECD average ($18,105) (Table C1.1).3 This spending on postsecondary education amounts to 2.5 percent of the U.S. GDP, higher than the OECD average (1.5 percent) (Table C2.1). These total expenditures include amounts received from governments, students, and all other sources.


Figure 2. Expenditures per full-time equivalent student, by education level and OECD country: 2020

[click to enlarge image]

1 Year of reference differs from 2020. Refer to the source table for more details.
SOURCE: OECD (2023), Table C1.1. See Source section for more information and Annex 3 for notes.


High School Completion Rate

The United States has a higher upper secondary (high school) completion rate than most other OECD countries. In 2021, some 87 percent of U.S. students completed their high school program in the expected timeframe, compared with the OECD average of 72 percent (Table B3.1).


Early Childhood Education

The level of participation in early childhood education programs in the United States is below the OECD average. In 2021, average enrollment rates across OECD countries were 72 percent for 3-year-olds, 87 percent for 4-year-olds, and 84 percent for 5-year-olds (Table B2.1). In contrast, enrollment rates for students of these ages in the United States were 30 percent for 3-year-olds, 50 percent for 4-years-olds, and 81 percent for 5-year-olds.  

 

Browse the full EAG 2023 report to see how the United States compares with other countries on these and other important education-related topics.

 

By RaeAnne Friesenhahn, AIR, and Cris De Brey, NCES


[1] EAG data for the year 2000 can be accessed via the online OECD Stat database.

[2] Unrounded data in Excel format can be accessed via the StatLink located below each table.

[3] Expenditure in national currencies was converted into equivalent USD by dividing the national currency figure by the purchasing power parity (PPP) index for GDP. For more details on methodology see Annex 2 and Annex 3.