NCES Blog

National Center for Education Statistics

Highlights of 2015–16 and 2016–17 School-Level Finance Data

NCES annually publishes comprehensive data on the finances of public elementary and secondary schools through the Common Core of Data (CCD). For many years, these data have been released at the state level through the National Public Education Financial Survey (NPEFS) and at the school district level through the Local Education Agency (School District) Finance Survey (F-33).

Policymakers, researchers, and the public have long voiced concerns about the equitable distribution of school funding within and across districts. School-level finance data provide reliable and unbiased measures that can be utilized to compare how resources are distributed among schools within districts.

Education spending data are now available for 15 states[1] at the school level through the School-Level Finance Survey (SLFS), which NCES has been conducting annually since 2014.[2] In November 2018, the Office of Management and Budget (OMB) approved changes to the SLFS wherein variables have been added to make the SLFS directly analogous to the F-33 Survey and to the Every Student Succeeds Act (ESSA) provisions on reporting expenditures per pupil at the school and district levels.

Below are some key findings from the recently released NCES report Highlights of School-Level Finance Data: Selected Findings From the School-Level Finance Survey (SLFS) School Years 2015–16 (FY 16) and 2016–17 (FY 17).

 

Eight of the 15 states participating in the SLFS are able to report school-level expenditure data requested by the survey for a high percentage of their schools.

The initial years of the SLFS have consistently demonstrated that most states can report detailed school‑level spending data for the vast majority of their schools. In school year (SY) 2016–17 (FY 2017), most states participating in the SLFS (8 out of 15) reported school-level finance data for at least 95 percent of their schools (figure 1). With the exception of New Jersey,[3] all states were able to report at least partial SLFS finance data for more than 78 percent of their schools, ranging from 79 percent of schools in Colorado to 99 percent of schools in Oklahoma. In addition, the percentage of students covered by SLFS reporting was more than 99 percent in 9 of the 15 participating states. 


Figure 1. Percentage of students covered and percentage of schools with fiscal data reported in the School-Level Finance Survey (SLFS), by participating state: FY 2017


 

The SLFS can be used to evaluate school-level expenditure data based on various descriptive school characteristics.

The SLFS allows data users to not only view comparable school-level spending data but also evaluate differences in school-level spending based on a variety of school characteristics. In the report, SY 2016–17 (FY 2017) SLFS data were evaluated by charter status and urbanicity. Key findings from this evaluation include the following:

  • Median teacher salaries[4] in charter schools were lower than median teacher salaries in noncharter schools in all 7 states that met the standards for reporting teacher salaries for both charter and noncharter schools (figure 2).
  • School expenditures were often higher in cities and suburbs than in towns and rural areas. Median teacher salaries, for example, were highest for schools in either cities or suburbs in 9 of the 10 states that met the standards for reporting teacher salaries in each of the urbanicities (city, suburb, town, and rural) (figure 3).  

Figure 2. Median teacher salary for operational public elementary and secondary schools, by school charter status and reporting state: FY 2017


Figure 3. Median teacher salary for operational public elementary and secondary schools, by school urbanicity and reporting state: FY 2017


Median technology‑related expenditures per pupil were also highest for schools in either cities or suburbs in 9 of the 11 states that met the standards for reporting technology-related expenditures in each of the urbanicities, with schools in cities reporting the highest median technology-related expenditures per pupil in 6 of those states.

 

The SLFS can be used to evaluate and compare school-level expenditure data by various poverty indicators.

The report also evaluates and compares school-level spending by school poverty indicators, such as Title I eligibility and school neighborhood poverty level. Key findings from this evaluation include the following:

  • In SY 2016–17 (FY 2017), median teacher salaries were slightly lower for Title I eligible schools than for non-Title I eligible schools in 7 of the 8 states where standards were met for reporting both Title I eligible and non-Title I eligible schools. However, median personnel salaries per pupil were slightly lower for Title I eligible schools than for non-Title I eligible schools in only 2 of the 8 states where reporting standards were met.    
  • Median personnel salaries per pupil for SY 2016–17 were higher for schools in high‑poverty neighborhoods than for schools in low-poverty neighborhoods in 7 of the 12 states where standards were met for reporting school personnel salaries.

 

To learn more about these and other key findings from the SY 2015–16 and 2016–17 SLFS data collections, read the full report. The corresponding data files for these collections will be released later this year.


[1] The following 15 states participated in the SY 2015–16 and 2016–17 SLFS: Alabama, Arkansas, Colorado, Florida, Georgia, Kentucky, Louisiana, Maine, Michigan, New Jersey, North Carolina, Ohio, Oklahoma, Rhode Island, and Wyoming.

[2] Spending refers to “current expenditures,” which are expenditures for the day-to-day operation of schools and school districts for public elementary/secondary education. For the SY 2015–16 and 2016–17 data collections referenced in this blog, the SLFS did not collect complete current expenditures; the current expenditures collected for those years included expenditures most typically accounted for at the school level, such as instructional staff salaries, student support services salaries, instructional staff support services salaries, school administration salaries, and supplies and purchased services. As of SY 2017–18, the SLFS was expanded to collect complete current expenditures.

[3] In New Jersey, detailed school-level finance reporting is required for only its “Abbott” districts, which comprised only 31 of the state’s 699 school districts in SY 2016–17.

[4] “Median teacher salaries” are defined as the median of the schools’ average teacher salary. A school’s average teacher salary is calculated as the teacher salary expenditures reported for the school divided by the number of full-time-equivalent (FTE) teachers at the school. Note that this calculation differs from calculating the median of salaries across all teachers at the school, as the SLFS does not collect or report salary data at the teacher level.

 

 

By Stephen Cornman, NCES

Tips for Navigating the Digest of Education Statistics

Have you explored the recently released Digest of Education Statistics 2019? The Digest is a great resource for education data on a range of topics from a variety of sources. Because of the report’s size (the 2019 edition has more than 700 tables across 7 chapters), it can sometimes be a bit tricky to find the data you need. Read on to discover some tips for navigating the Digest website.

 

Finding the Most Recent Versions of Tables

There are several ways to find the most recent version of a table, depending on what page you are on. From the Digest landing page, click on “Most Current Digest Tables” (figure 1). From the list of tables page for a specific year, use the drop-down menu to select “Current” (figure 2).


Figure 1


Figure 2


  • Tip: If you navigate to a table from a search engine, you may not be on the most recent year. Check for a “Click here for the latest version of this table” option in the top righthand corner of the table’s page.

 

Finding Tables Using the Digest Indexing System

Have you ever navigated to a Digest table from a search engine or another NCES report and wanted to find other similar tables? What should you do if a Digest table covers a topic you want to learn about but does not include the specific data you need? You can use the Digest indexing system to find other similar tables.

The Digest indexing system is based on numbered chapters and topical subsections. Each table identifier contains the chapter number (1 through 7) followed by the subsection (e.g., 01, 02, 03) and the table number after the period (e.g., .10, .20, .30). For example, table 601.10 is the first table in chapter 6 under “Population, Enrollment, and Teachers,” which is subsection 01 (figure 3).


Figure 3


To find tables similar to the one you have found already, click on the link at the top left of the table’s page, which will take you to a full list of tables for the Digest edition you are viewing. For example, a Digest 2019 table will feature a “2019 Tables and Figures” link at the top left of the table (figure 4).


Figure 4


From here you can navigate to the relevant chapter and subsection using the indexing system. For example, if you were viewing table 601.10 and wanted to find other similar tables, you would click the + sign next to “Chapter 6. International Comparisons of Education” and then click the + next to “601 Population, Enrollment, and Teachers” (figure 5). You can then click through and explore all the relevant tables in that subsection.


Figure 5


  • Tip: Use the radio buttons at the top right to toggle between viewing tables and figures.
  • Tip: Use Ctrl + click to open tables in a new tab to avoid losing your place on the page.

If you do not see a table with the information you need, remember that the SOURCE note of a Digest table can be a great way to find related resources. Scroll to the bottom of a table to find the data sources used to prepare it.

 

Searching for Key Terms or Phrases Across All Tables

What if you want to search the Digest by topic instead of starting with a specific table? One easy way to do so is to navigate to the “List of 2019 Tables Page” and click “Show All” next to each chapter (figure 6).

  • Tip: Start at chapter 7 and work your way up to avoid having to scroll.

Figure 6


Once the tables are displayed for each chapter, you can easily do a global search of the entire page (Ctrl + F) and search for the term or phrase of your choice.

  • Tip: Try a few different search terms if you do not find what you are looking for right away. For example, the Digest uses the term “distance education” for remote learning.

 

Accessing Older Versions of Tables

In addition to the current edition of the report, the Digest website also contains archives of each report through 1990. You can access previous editions of the report in several ways (figure 7):

  • Select a year from the drop-down menu to access the HMTL versions of that year’s tables.
  • Click on “Access PDF versions of the Digest from 1990–2019” to access archived PDF files.
    • From here, you can click the + next to “Digest of Education Statistics” and select the report you want to view.

Figure 7


In addition to trying these tips for navigating the Digest website, you can explore the Reader’s Guide and Guide to Sources to learn more about the data sources used in the report. The Reader’s Guide also provides additional information about common measures and indexes, data analysis and interpretation, limitations of the data, and other aspects of the report. 

 

By Megan Barnett, AIR

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. A recording is also available for a RISE Webinar from 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