NCES Blog

National Center for Education Statistics

Distance Education in College: What Do We Know From IPEDS?

Distance education (DE) is defined by the Integrated Postsecondary Education Data System (IPEDS) as “education that uses one or more technologies to deliver instruction to students who are separated from the instructor.” By allowing students to take classes online in their own locations and on their own schedules, DE has increased access to college. Since the beginning of the coronavirus pandemic in spring 2020, DE has become an important way to deliver college classes while helping to keep students safe.

IPEDS collects information on DE in four of its surveys: Institutional Characteristics, Fall Enrollment, Completions, and, most recently, 12-Month Enrollment. The figures below present key statistics on DE course/program offerings and enrollments at U.S. colleges.

How many colleges offer distance education courses and programs?

In 2018–19, most colleges (79 percent) offered either stand-alone DE courses or entire DE programs (e.g., 100% online degrees). DE course and program offerings differed by the control (public, private nonprofit, or private for-profit) and level (4-year or 2-year) of the college.

  • Almost all public 4- and 2-year colleges (96 and 97 percent, respectively) offered either DE courses or DE programs.
  • A majority of private nonprofit and for-profit 2-year colleges (53 and 59 percent, respectively) did not offer DE courses or DE programs, though they account for a small number of colleges.

Figure 1. Percentage distribution of colleges, by control, level, and distance education (DE) offerings of college: Academic year 2018–19

NOTE: Figure includes U.S. degree-granting institutions that participate in Title IV federal financial aid programs. Although rounded numbers are displayed, the figures are based on unrounded data. Detail may not sum to totals because of rounding.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS) Institutional Characteristics component, Fall 2018.


How many students are enrolled in distance education courses?

In fall 2018, about 6.9 million students enrolled in DE courses, or 35 percent of the total fall enrollment population (19.6 million).

  • Between fall 2012 and 2018, DE course enrollment increased 29 percent (from 5.4 to 6.9 million), while total fall enrollment declined by 5 percent (from 20.6 to 19.6 million).
  • The number of students enrolled in a mix of DE and face-to-face courses increased by 33 percent (from 2.8 to 3.7 million) between fall 2012 and 2018. The number of students enrolled in only DE courses also increased, but at a slower rate of 24 percent (from 2.6 to 3.3 million).

Figure 2. Total college enrollment, by distance education (DE) participation of students: Fall 2012 through fall 2018

NOTE: Figure includes U.S. degree-granting institutions that participate in Title IV federal financial aid programs. Although rounded numbers are displayed, the figures are based on unrounded data.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS) Fall Enrollment component, Spring 2013 through Spring 2019.


How does enrollment in distance education courses vary by college control?

In fall 2018, the share of students enrolled in DE courses differed by control of the college.

  • About one-third of students at public and private nonprofit colleges enrolled in at least one DE course (34 and 30 percent, respectively).
  • At public colleges, students were more likely to enroll in a mix of DE and face-to-face courses (22 percent) than in only DE courses (12 percent). This trend reversed at private nonprofit colleges, with 10 percent of students enrolled in a mix of DE and face-to-face courses and 20 percent in only DE courses.
  • At private for-profit colleges, most students (73 percent) enrolled in at least one DE course (10 percent in a mix of DE and face-to-face courses and 63 percent in only DE courses).

Figure 3. Percentage distribution of college enrollment, by control of college and distance education (DE) participation of students: Fall 2012 through fall 2018

NOTES: Figure includes U.S. degree-granting institutions that participate in Title IV federal financial aid programs. Although rounded numbers are displayed, the figures are based on unrounded data. Detail may not sum to totals because of rounding.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS) Fall Enrollment component, Spring 2013 through Spring 2019.


Among students enrolled in only DE courses, where do they live relative to their colleges?

Students taking only DE courses do not necessarily live far away from their colleges (even when physically coming to campus is generally not required), especially among students enrolled in public colleges.

  • In fall 2018, most (82 percent) of the 1.8 million students taking only DE courses at public colleges lived in the same state as their colleges. Only 15 percent lived in a different state.
  • At private nonprofit and for-profit colleges, students taking only DE courses were less likely to live in the same state as their colleges (35 percent and 17 percent, respectively) and more likely to live in a different state (63 percent and 81 percent, respectively) in fall 2018.

Figure 4. Percentage distribution of college enrollment for students enrolled in only distance education (DE) courses, by control of college and location of students: Fall 2018

NOTE: One square represents 1 percent. “State unknown” is reported by the institution when a student’s home state of residence cannot be determined; “Location unknown” is imputed by IPEDS to classify students when the institution does not report any residence status. Figure includes U.S. degree-granting institutions that participate in Title IV federal financial aid programs.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS) Fall Enrollment component, Spring 2019.


The DE enrollment figures above use the most recent IPEDS data available, which is limited to a fall “snapshot” date. However, in 2020–21, IPEDS expanded the 12-Month Enrollment survey to collect DE course enrollment for the entire 12-month academic year, which will provide even more information on DE enrollments at U.S. colleges. The first 12-month DE enrollment data, representing the 2019–20 academic year, will be released in spring 2021. These will be the first IPEDS enrollment data to overlap with the coronavirus pandemic, and DE course enrollments are expected to increase.

To learn more about DE data collected in IPEDS, visit the Distance Education in IPEDS resource page. To explore IPEDS data through easy-to-use web tools or to access data files to conduct your own original analyses like the ones presented in this blog, visit the IPEDS Use the Data page.

 

By Roman Ruiz and Jie Sun, AIR

New International Data Show Large and Widening Gaps Between High- and Low-Performing U.S. 4th- and 8th-Graders in Mathematics and Science

NCES recently released results from the 2019 Trends in International Mathematics and Science Study (TIMSS). TIMSS tests students in grades 4 and 8 in mathematics and science every 4 years. The results show that

  • Across both subjects and grades, the United States scored, on average, in the top quarter of the education systems that took part in TIMSS 2019.
    • Among the 64 education systems that participated at grade 4, the United States ranked 15th and 8th in average mathematics and science scores, respectively.
    • Among the 46 education systems that participated at grade 8, the United States ranked 11th in average scores for both subjects.
  • On average, U.S. scores did not change significantly between the 2011 and 2019 rounds of TIMSS.

Average scores are one measure of achievement in national and international studies. However, they provide a very narrow perspective on student performance. One way to look more broadly is to examine differences in scores (or “score gaps”) between high-performing students and low-performing students. Score gaps between high performers and low performers can be one indication of equity within an education system. Here, high performers are those who scored in the 90th percentile (or top 10 percent) within their education system, and low performers are those who scored in the 10th percentile (or bottom 10 percent) within their education system.

In 2019, while some education systems had a higher average TIMSS score than the United States, none of these education systems had a wider score gap between their high and low performers than the United States. This was true across both subjects and grades.

Figure 1 shows an example of these findings using the grade 8 mathematics data. The figure shows that 17 education systems had average scores that were higher or not statistically different from the U.S. average score.

  • Of these 17 education systems, 13 had smaller score gaps between their high and low performers than the United States. The score gaps in 4 education systems (Singapore, Chinese Taipei, the Republic of Korea, and Israel) were not statistically different from the score gap in the United States.
  • The score gaps between the high and low performers in these 17 education systems ranged from 170 points in Quebec, Canada, to 259 points in Israel. The U.S. score gap was 256 points.
  • If you are interested in the range in the score gaps for all 46 education systems in the TIMSS 2019 grade 8 mathematics assessment, see Figure M2b of the TIMSS 2019 U.S. Highlights Web Report, released in December 2020. This report also includes these results for grade 8 science and both subjects at the grade 4 level.

Figure 1. Average scores and 90th to 10th percentile score gaps of grade 8 students on the TIMSS mathematics scale, by education system: 2019

NOTE: This figure presents only those education systems whose average scores were similar to or higher than the U.S. average score. Scores are reported on a scale of 0 to 1,000 with a TIMSS centerpoint of 500 and standard deviation of 100.

SOURCE: International Association for the Evaluation of Educational Achievement (IEA), Trends in International Mathematics and Science Study (TIMSS), 2019.


From 2011 to 2019, U.S. average scores did not change significantly. However, the scores of low performers decreased, and score gaps between low and high performers grew wider in both subjects and grades. In addition, at grade 8, there was an increase in the scores of high performers in mathematics and science over the same period. These two changes contributed to the widening gaps at grade 8.

Figure 2 shows these results for the U.S. grade 8 mathematics data. Average scores in 2011 and 2019 were not significantly different. However, the score of high performers increased from 607 to 642 points between 2011 and 2019, while the score of low performers decreased from 409 to 385 points. As a result, the score gap widened from 198 to 256 points between 2011 and 2019. In addition, the 2019 score gap for grade 8 mathematics is significantly wider than the gaps for all previous administrations of TIMSS.


Figure 2. Trends in average scores and selected percentile scores of U.S. grade 8 students on the TIMSS mathematics scale: Selected years, 1995 to 2019

* p < .05. Significantly different from the 2019 estimate at the .05 level of statistical significance.

NOTE: Scores are reported on a scale of 0 to 1,000 with a TIMSS centerpoint of 500 and standard deviation of 100.

SOURCE: International Association for the Evaluation of Educational Achievement (IEA), Trends in International Mathematics and Science Study (TIMSS), 1995, 1999, 2003, 2007, 2011, 2015, 2019.


These TIMSS findings provide insights regarding equity within the U.S. and other education systems. Similar results from the National Assessment of Educational Progress (NAEP) show that mathematics scores at both grades 4 and 8 decreased or did not change significantly between 2009 and 2019 for lower performing students, while scores increased for higher performing students. More national and international research on the gap between high- and low-performing students could help inform important education policy decisions that aim to address these growing performance gaps.

To learn more about TIMSS and the 2019 U.S. and international results, check out the TIMSS 2019 U.S. Highlights Web Report and the TIMSS 2019 International Results in Mathematics and Science. Registration is also open for an upcoming RISE Webinar on February 24, 2021 (What Do TIMSS and NAEP Tell Us About Gaps Between High- and Low-Performing 4th and 8th Graders?) that explores these topics further.  

 

By Katie Herz, AIR; Marissa Hall, AIR; and Lydia Malley, NCES

Online Training for the 2019 NHES Early Childhood Program Participation Survey Data and Parent and Family Involvement in Education Survey Data

The NCES National Household Education Survey (NHES) program administered two national surveys in 2019—the Early Childhood Program Participation (ECPP) survey and the Parent and Family Involvement in Education (PFI) survey. The ECPP survey collects information on young children’s care and education, including the use of home-based care with both relatives and nonrelatives and center-based care and education. The survey examines how well these care arrangements cover work hours, costs of care, location of care, the process of selecting care, and factors making it difficult to find care. The PFI survey collects information on a range of issues related to how families connect to schools, including information on family involvement with schools, school choice, homeschooling, virtual education, and homework practices.

NCES released data from the 2019 NHES administration on January 28, 2021. For each of the two surveys, this release includes the following:

  • Public-use data files, in ASCII, CSV, SAS, SPSS, Stata, and R
  • Restricted-use data files (in formats listed above and with codebook)
  • Public-Use Data File Codebook
  • Data File User’s Manual (for both public-use and restricted-use files)

That’s a lot of information! How should you use it? We suggest you start by viewing the NHES online data Distance Learning Dataset Training modules. The modules provide a high-level overview of the NHES program and the data it collects. They also include important considerations to ensure that your analysis takes into account the NHES’s complex sample design (such as applying weights and estimating standard errors).   

You should first view the five general NHES modules, which were developed for the 2012 NHES data. These modules are:

  • Introduction to the NHES
  • Getting Started with the NHES Data
  • Data Collected Through the NHES
  • NHES Sample Design, Weights, Variance, and Missing Data
  • Considerations for Analysis of NHES Data

A sixth module explains key changes in the 2019 ECPP and PFI surveys compared to their respective 2012 surveys:

  • Introduction to the 2019 NHES Data Collection

The sixth module also provides links to the 2019 ECPP and PFI data, restricted-use licensing information, and other helpful resources.

Now you are ready to go! If you have any questions, please contact us at NHES@ed.gov.

By Lisa Hudson, NCES

New International Data Identify “Resilient” Students in Financial Literacy

NCES recently released the results of the Program for International Student Assessment (PISA) 2018 assessment of financial literacy. This assessment measured 15-year-old students’ knowledge and understanding of financial concepts, products, and risks and their ability to apply that knowledge to real-life situations. It found that, on average, U.S. students performed similarly to their peers across the 12 other participating Organization for Economic Cooperation and Development (OECD) countries. 

The assessment also found that 12 percent of U.S. students performed at the highest level of proficiency (level 5). Performance at this level indicates that students can apply their understanding of financial terms and concepts to analyze complex financial products, solve nonroutine financial problems, and describe potential outcomes of financial decisions in the big picture.[1] The U.S. percentage was again similar to the OECD average.

However, this analysis also identified a group of students who might be considered “resilient.” In education research, resilience is defined as the ability to perform well academically despite coming from the disadvantaged backgrounds that have more commonly been associated with lower performance.

High-performing students came from across the spectrum of school poverty levels, as measured by the percentage of students eligible for free or reduced-price lunch (FRPL).[2] In particular, 7 percent of high-performing students in financial literacy came from the highest poverty schools (figure 1).


Figure 1. Percentage distribution of U.S. 15-year-olds in public schools scoring below level 2 and at level 5 of proficiency on the PISA financial literacy scale, by percentage of students eligible for free or reduced-price lunch (FRPL) at their school: 2018

NOTE: Data for percentage of students eligible for FRPL were available for public schools only. An individual student’s level of poverty may vary within schools. Detail may not sum to totals due to rounding.

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2018.


It is these 7 percent of students who could be considered “resilient” and may be of interest for further study. For example, research could identify if there are factors that are associated with their high performance when compared to their lower performing peers in similar schools. Research on academically resilient students that used eighth-grade data from TIMSS found, for example, that having high educational aspirations increased the likelihood that students with few home education resources performed at or above the TIMSS Intermediate international benchmark in mathematics.[3] Experiencing less bullying also increased this likelihood.

Examining the “resilient” PISA financial literacy students more closely could also determine the extent to which their individual backgrounds are related to performance. This would be of interest because, even within high-poverty schools, students’ individual circumstances may vary. 

Patterns in Other PISA Subjects

There are similar subsets of “resilient” students in the other PISA 2018 subjects (table 1). Eight percent of high performers in reading were from the highest poverty schools, as were 5 percent of high performers in mathematics and 7 percent of high performers in science.


Table 1. Percentage of U.S. 15-year-olds in public schools scoring at or above level 5 of proficiency, by PISA subject and their schools’ free or reduced-price lunch (FRPL) status: 2018

[Standard errors appear in parentheses]

NOTE: Results are scaled separately; thus, percentages cannot be compared across subjects. Level 5 is the highest level of proficiency in financial literacy; levels 5 and 6 are the highest levels of proficiency in the other PISA subjects. Data for students eligible for FRPL were available for public schools only.

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2018.


For more information on the PISA 2018 results in financial literacy and other subjects, visit the NCES International Activities website. To create customized data and charts using PISA and other international assessment data, use the International Data Explorer.

 

By Maria Stephens, AIR


[2] Data for students eligible for FRPL are available for public schools only.

[3] Students at the Intermediate international benchmark can apply basic mathematical knowledge in a variety of situations, and those above this benchmark can do so in increasingly complex situations and, at the highest end, reason with information, draw conclusions, make generalizations, and solve linear equations.

Accessing the Common Core of Data (CCD)

Every year, NCES releases nonfiscal data files from the Common Core of Data (CCD), the Department of Education’s (ED’s) primary longitudinal database on public elementary and secondary education in the United States. CCD data releases include directory data (location, status, and grades offered), student membership data (by grade, gender, and race/ethnicity), data on full-time equivalent staff and teachers, and data on the number of students eligible for the National School Lunch Program (NSLP)

This blog post, one in a series of posts about CCD data, focuses on how to access and use the data. For information on using NSLP data, read the blog post Understanding School Lunch Eligibility in the Common Core of Data

CCD Data Use

CCD data are used both internally by ED and externally by the public. For example, within ED, CCD data serve as the sample frame for the National Assessment of Educational Progress (NAEP) and are the mainstay of many tables in the Digest of Education Statistics and The Condition of Education. Outside of ED, CCD data are used by researchers, the general public (e.g., realtor sites, The Common Application, Great Schools), and teachers who need their school’s NCES school ID to apply for grants.

Data Structure and Availability

CCD data are available at the state, district, and school levels, using a nested structure: all schools are within a parent district and all districts are within a state. CCD does not include any student- or staff-level data.

Most CCD data elements are available for school year (SY) 1986‒87 to the present.    

Unique Identifiers Within CCD

NCES uses a three-part ID system for public schools and districts: state-based Federal Information Processing Standards (FIPS) codes, district codes, and school codes. Using these three parts, several IDs can be generated:

  • District IDs: 7-digit (FIPS + 5-digit District)
  • School IDs:
    • 12-digit (FIPS + District + School)
    • 7-digit (FIPS + School) (unique from SY 2016‒17 on)

NCES IDs are assigned to districts and schools indefinitely, making them useful for analyzing data over time. For example, for a longitudinal school-level analysis, a school’s 7-digit ID should be used, as it remains the same even if the school changes districts. These IDs can also be used to link CCD district and school data to other ED databases.

Accessing CCD Data

There are three ways to access CCD data: the CCD District and School Locators, the Elementary/Secondary Information System (ElSi), and the raw data files. Each approach has different benefits and limitations.

  • CCD District and School locators
    • Quick and easy to use
    • Many ways to search for districts and schools (e.g., district/school name, street address, county, state)
    • Provides the latest year of CCD data available for the selected district(s) or school(s)
    • Tips for optimal use:
      • If you are having difficulty finding a district or school, only enter a key word for the name (e.g., for PS 100 Glen Morris in New York City, only enter “Glen Morris” or “PS 100”)
      • Export search results to Excel (including all CCD locator fields)

  • Elementary/Secondary Information System (ElSi)
    • quickFacts and expressTables: view most-requested CCD data elements at multiple levels
    • tableGenerator: combine data across topic areas and years to create a single file
    • Create “tables” that act like databases and include all of the roughly 100,000 public schools or 20,000 districts
    • Export data to Excel or CSV
    • Tips for optimal use:
      • Save and edit queries using the navigation buttons at the top of the screen
      • popularTables provide links to frequently requested data

 

Interested in learning more about CCD or accessing CCD data at the state, district, or school level? Check out the CCD website and use the District and School locators, ElSi, or the raw data files to find the data you are looking for.

 

By Patrick Keaton, NCES