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Institute of Education Sciences

NCES Releases Updated 2022–23 Data Table on School District Structures

The National Center for Education Statistics (NCES) has released an updated data table (Excel) on local education agencies (LEAs)1  that serve multiple counties. This new data table—which was updated with 2022–23 data—can help researchers examine LEA structures and break down enrollment by LEA and county. Read this blog post to learn more about the table and how it can be used to understand structural differences in school districts.

The data table—which compiles data from both the Common Core of Data (CCD) and Demographic and Geographic Estimates (EDGE)—provides county and student enrollment information on each LEA in the United States (i.e., in the 50 states and the District of Columbia) with a separate row for each county in which the agency has a school presence. The table includes all LEA types, such as regular school districts, independent charter school districts, supervisory union administrative centers, service agencies, state agencies, federal agencies, specialized public school districts, and other types of agencies.

LEA presence within a county is determined by whether it had at least one operating school in the county. School presence within a county is determined by whether there is at least one operating school in the county identified in the CCD school-level membership file. For example, an LEA that is coterminous with a county has one record (row) in the listing. A charter school LEA that serves a region of a state and has a presence in five counties has five records. LEA administrative units, which do not operate schools, are listed in the county in which the agency is located.

In the 2022–23_LEA_List tab, column D shows the “multicnty” (i.e., multicounty) variable. LEAs are assigned one of the following codes:

1 = School district (LEA) is in single county and has reported enrollment.

2 = School district (LEA) is in more than one county and has reported enrollment.

8 = School district (LEA) reports no schools and no enrollment, and the county reflects county location of the administrative unit. 

9 = School district (LEA) reports schools but no enrollment, and the county reflects county location of the schools.

In the Values tab, the “Distribution of local education agencies, by enrollment and school status: 2022–23” table shows the frequency of each of the codes (1, 2, 8, and 9) (i.e., the number of districts that are marked with each of the codes in the 2022–23_LEA_List tab):

  • 17,042 LEAs had schools in only one county.
  • 754 LEAs had schools located in more than one county and reported enrollment for these schools (note that in the file there are 1,936 records with this characteristic since each LEA is listed once for every county in which it has a presence).
  • 1,008 LEAs had no schools of their own and were assigned to a single county based on the location of the LEA address. (Typically, supervisory union administrative centers are examples of these LEAs.)
  • 262 LEAs had schools located in one county but did not report enrollment for these schools (note that in the file there are 384 records with this characteristic since each LEA is listed once for every county in which it has a presence).

This data table is part of our effort to meet emerging data user needs and provide new products in a timely manner. Be sure to follow NCES on XFacebookLinkedIn, and YouTube and subscribe to the NCES News Flash to stay informed when these new products are released.

By Tom Snyder, AIR


[1] Find the official definition of an LEA.

[2] See Number and enrollment of public elementary and secondary schools, by school level, type, and charter, magnet, and virtual status: Selected years, 1990–91 through 2018–19Enrollment of public elementary and secondary schools, by school level, type, and charter, magnet, and virtual status: School years 2010–11 through 2021–22 (ed.gov)Number of public elementary and secondary education agencies, by type of agency and state or jurisdiction: 2004–05 and 2005–06; and Number of public elementary and secondary education agencies, by type of agency and state or jurisdiction: School years 2020–21 and 2021–22.

[3] See Education Governance for the Twenty-First Century: Overcoming Structural Barriers to School Reform.

[4] The annual School District Finance Survey (F-33) is collected by NCES from state education agencies and the District of Columbia. See Documentation for the NCES Common Core of Data School District Finance Survey (F-33) for more information.

 

Leveraging Economic Data to Understand the Education Workforce

The Digest of Education Statistics recently debuted 13 new tables on K–12 employment and wages from a data source that is new to the Digest—the Occupational Employment Wage Statistics (OEWS) program of the Bureau of Labor Statistics (BLS). NCES’s Annual Reports and Information Staff conducted an extensive review of existing and emerging data sources and found that BLS’s OEWS program provides high-quality, detailed, and timely data that are suitable to inform policymaking in education and workforce development.1 In this blog post, we share why we added this new data source, how we evaluated and prepared these data, and our future plans to expand on these efforts.

 

Need for Education Workforce Data

NCES recognized that education stakeholders need more granular and timely data on the condition of the education workforce to inform decisionmaking. In the wake of the coronavirus pandemic, school districts are looking to address critical staffing needs. According to NCES’s School Pulse Panel, entering the 2023–24 school year (SY), just under half of U.S. public schools reported feeling understaffed and had a need for special education teachers, transportation staff, and mental health professionals.

Since staffing needs and labor markets vary from district to district and state to state, it is important that we create national- and state-level tabulations for specific occupations, including those of special interest since the pandemic, like bus drivers, social workers, and special education teachers. Similarly, we want to be able to provide annual data updates so stakeholders can make the most up-to-date decisions possible.

Annual Digest table updates, coupled with detailed occupational and state-level data, will provide relevant and timely information on employment and wage trends that will be valuable in current and future efforts to address teacher and staff retention and recruitment. See below for a list of the new Digest tables.

  • National-level employment and annual wages
  • Selected teaching occupations (211.70)
  • Selected noninstructional occupations (213.70)
  • State-level employment and annual wages
  • Preschool teachers (211.70a)
  • Kindergarten teachers (211.70b)
  • Elementary school teachers (211.70c)
  • Middle school teachers (211.70d)
  • Secondary school teachers (211.70e)
  • Kindergarten and elementary special education teachers (211.70f)
  • Middle school special education teachers (211.70g)
  • Secondary school special education teachers (211.70h)
  • Substitute teachers (211.70i)
  • Teaching assistants (211.70j)
  • All occupations in the Elementary and Secondary Education industry (213.75)

 

Strengths of OEWS

OEWS and the Digest tables are aligned with the Federal Committee on Statistical Methodology’s Data Quality Framework, specifically the principles of objectivity (standardization), utility (granularity and timeliness), and integrity (data quality).


Standardization

OEWS produces employment and wage estimates using standardized industry and occupational classifications. Using the North American Industry Classification System, establishments are grouped into categories—called industries—based on their primary business activities. Like industries, occupations are organized into groups or categories based on common job duties (using the Standard Occupational Classification). Occupations that are common to K–12 schools can also be found in other industries, and the OEWS provides both cross-industry estimates and industry-specific estimates for just Elementary and Secondary Education industry. To provide the most relevant and comparable data for education stakeholders, NCES chose to focus on distinct occupational estimates for the Elementary and Secondary Education industry, since all establishments (e.g., school boards, school districts) provide the same services: instruction or coursework for basic preparatory education (typically K–12).2     

Another advantage of the OEWS data is the ability to examine specific detailed occupations, like elementary school teachers, secondary school teachers, and education administrators. Digest tables include estimates for specific instructional and noninstructional occupations, which allows users to make comparisons among teachers and staff with similar job responsibilities, providing opportunities for more targeted decisionmaking.


Granularity

In addition to data on detailed occupations, OEWS data provide data at national and state and levels, allowing for comparisons across geographies. National-level Digest tables include estimates for public and private education employers.3 Publicly funded charter schools run by private establishments are included in private ownership estimates, as they can be managed by parents, community groups, or private organizations. Public ownership is limited to establishments that are run by federal, state, or local governments. State-level Digest tables provide more localized information covering labor markets for the 50 states, the District of Columbia, Puerto Rico, Guam, and the U.S. Virgin Islands.
   

Timeliness and Data Quality

OEWS data are updated annually from a sample of about 1.1 million establishments’ data collected over a 3-year period. The OEWS sample is drawn from an administrative list of public and private companies and organizations that is estimated to cover about 95 percent of jobs.4 When employers respond to OEWS, they report from payroll data that are maintained as a part of regular business operations and typically do not require any additional collections or calculations. Payroll data reflect wages paid by employers for a job, which has a commonly accepted definition across employers or industries. This allows for more accurate comparisons of annual wages for a particular job. In contrast, when wages are self-reported by a respondent in person-level or household surveys, the reported data may be difficult to accurately code to a specific industry or detailed occupation, and there is greater chance of recall error by the respondent. Additionally, OEWS provides specialized respondent instructions for elementary and secondary schools and postsecondary institutions that accommodate the uniqueness of what educators do and how they are paid. These instructions enable precise coding of the occupations commonly found in these industries and a more precise and consistent reporting of wages of workers with a variety of schedules (e.g., school year vs. annual, part time vs. full time).   

OEWS uses strict quality control and confidentiality measures and strong sampling and estimation methodologies.5 BLS also partners with state workforce agencies to facilitate the collection, coding, and quality review of OEWS data. States’ highly trained staff contribute local knowledge, establish strong respondent relationships, and provide detailed coding expertise to further ensure the quality of the data. 

After assessing the strengths of the OEWS data, the Digest team focused on the comparability of the data over time to ensure that the data would be best suited for stakeholder needs and have the most utility. First, we checked for changes to the industrial and occupational classifications. Although there were no industrial changes, the occupational classifications of some staff occupations—like librarians, school bus drivers, and school psychologists—did change. In those cases, we only included comparable estimates in the tables.

Second, all new Digest tables include nonoverlapping data years to account for the 3-year collection period. While users cannot compare wages in 2020 with 2021 and 2022, they can explore data from 2016, 2019, and 2022. Third, the Digest tables present estimates for earlier data years to ensure the same estimation method was used to produce estimates over time.6 Finally, we did not identify any geographical, scope, reference period, or wage estimation methodology changes that would impact the information presented in tables. These checks ensured we presented the most reliable and accurate data comparisons.

 

Next Steps  

The use of OEWS data in the Digest is a first step in harnessing the strength of BLS data to provide more relevant and timely data, leading to a more comprehensive understanding of the education workforce. NCES is investigating ways we can partner with BLS to further expand these granular and timely economic data, meeting a National Academies of Science, Engineering, and Medicine recommendation to collaborate with other federal agencies and incorporate data from new sources to provide policy-relevant information. We plan to explore the relationship between BLS data and NCES data, such as the Common Core of Data, and increase opportunities for more detailed workforce analyses.

NCES is committed to exploring new data sources that can fill important knowledge gaps and expand the breadth of quality information available to education stakeholders. As we integrate new data sources and develop new tabulations, we will be transparent about our evaluation processes and the advantages and limitations of sources. We will provide specific examples of how information can be used to support evidence-based policymaking. Additionally, NCES will continue to investigate new data sources that inform economic issues related to education. For example, we plan to explore Post-Secondary Employment Outcomes to better understand education-to-employment pathways. We are investigating sources for building and land use data to assess the condition and utilization of school facilities. We are also looking for opportunities to integrate diverse data sources to expand to new areas of the education landscape and to support timelier and more locally informed decisionmaking.
 

How will you use the new Digest tables? Do you have suggestions for new data sources? Let us know at ARIS.NCES@ed.gov.

 

By Josue DeLaRosa, Kristi Donaldson, and Marie Marcum, NCES


[1] See these frequently asked questions for a description of current uses, including economic development planning and to project future labor market needs.

[2] Although most of the K–12 instructional occupations are in the Elementary and Secondary Education industry, both instructional and noninstructional occupations can be found in others (e.g., Colleges, Universities, and Professional Schools; Child Care Services). See Educational Instruction and Library Occupations for more details. For example, preschool teachers differ from some of the other occupations presented in the Digest tables, where most of the employment is in the Child Care Services industry. Preschool teachers included in Digest tables reflect the employment and average annual wage of those who are employed in the Elementary and Secondary Education industry, not all preschool teachers.

[3] Note that estimates do not consider differences that might exist between public and private employers, such as age and experience of workers, work schedules, or cost of living.

[4] This includes a database of businesses reporting to state unemployment insurance (UI) programs. For more information, see Quarterly Census of Employment and Wages.

[5] See Occupational Employment and Wage Statistics for more details on specific methods.

[6] Research estimates are used for years prior to 2021, and Digest tables will not present estimates prior to 2015, the first year of revised research estimates. See OEWS Research Estimates by State and Industry for more information.

Measuring Student Safety: New Data on Bullying Rates at School

NCES is committed to providing reliable and up-to-date national-level estimates of bullying. As such, a new set of web tables focusing on bullying victimization at school was just released.  

These tables use data from the School Crime Supplement to the National Crime Victimization Survey, which collects data on bullying by asking a nationally representative sample of students ages 12–18 who were enrolled in grades 6–12 in public and private schools if they had been bullied at school. This blog post highlights data from these newly released web tables.

Some 19 percent of students reported being bullied during the 2021–22 school year. More specifically, bullying was reported by 17 percent of males and 22 percent of females and by 26 percent of middle school students and 16 percent of high school students. Moreover, among students who reported being bullied, 14 percent of males and 28 percent of females reported being bullied online or by text.

Students were also asked about the recurrence and perpetrators of bullying and about the effects bullying has on them. During the 2021–22 school year, 12 percent of students reported that they were bullied repeatedly or expected the bullying to be repeated and that the bullying was perpetrated by someone who was physically or socially more powerful than them and who was not a sibling or dating partner. When these students were asked about the effects this bullying had on them,

  • 38 percent reported negative feelings about themselves;
  • 27 percent reported negative effects on their schoolwork;
  • 24 percent reported negative effects on their relationships with family and friends; and
  • 19 percent reported negative effects on their physical health.

Explore the web tables for more data on how bullying victimization varies by student characteristics (e.g., sex, race/ethnicity, grade, household income) and school characteristics (e.g., region, locale, enrollment size, poverty level) and how rates of bullying victimization vary by crime-related variables such as the presence of gangs, guns, drugs, alcohol, and hate-related graffiti at school; selected school security measures; student criminal victimization; personal fear of attack or harm; avoidance behaviors; fighting; and the carrying of weapons.

Find additional information on this topic in the Condition of Education indicator Bullying at School and Electronic Bullying. Plus, explore more School Crime and Safety data and browse the Report on Indicators of School Crime and Safety: 2022.

Highlights From the FY 21 Revenues and Expenditures for Public Elementary and Secondary Education Report

NCES recently released a finance tables report, Revenues and Expenditures for Public Elementary and Secondary Education: FY 21 (NCES 2023-301), which draws from data in the National Public Education Financial Survey (NPEFS). To accompany the report, NCES has updated the interactive data visualization tool to highlight the per pupil revenues and expenditures (adjusted for inflation) and average daily attendance (ADA) trends from the fiscal year 2021 (FY 21) NPEFS.

This tool allows users to see national or state-specific per pupil amounts and year-to-year percentage changes for both total revenue and current expenditures by using a slider to toggle between the two variables. Total revenues are shown by source, and total current expenditures are shown by function and subfunction. Clicking on a state in the map will display data for the selected state in the bar charts.

The tool also allows users to see the ADA for each state. It is sortable by state, ADA amount, and percentage change. It may also be filtered to easily compare selected states. Hovering over the ADA of a state will display another bar graph with the last 3 years of ADA data.

Overall, the results show that spending1 on elementary and secondary education increased in school year 2020–21 (FY 21). This is the eighth consecutive year that year-over-year education spending increased (since FY 13), after adjusting for inflation. This increase follows declines in year-over-year spending for the prior 4 years (FY 10 through FY 13).

 

Revenues

The 50 states and the District of Columbia reported $837.3 billion in revenues collected for public elementary and secondary education in FY 21. State and local governments provided $748.9 billion, or 89.4 percent of all revenues. The federal government contributed $88.4 billion, or 10.6 percent of all revenues. Total revenues increased by 3.0 percent after adjusting for inflation2 (from $812.8 to $837.3 billion) from FY 20 to FY 21; local revenues remained relatively unchanged (from $365.1 to $365.1 billion); state revenues decreased by 0.6 percent (from $385.9 to $383.8 billion); and federal revenues increased by 43.2 percent (from $61.8 to $88.4 billion).

Total revenues per pupil averaged $17,015 on a national basis in FY 21. This reflects an increase of 5.9 percent between FY 20 and FY 21 and follows an increase of 1.5 percent from FY 19 to FY 20. The percentage change in revenues per pupil from FY 20 to FY 21 ranged from an increase of 15.3 percent in Maine to a decrease of 4.2 percent in Hawaii.


Image of NPEFS data visualization site showing revenues per pupil for public elementary and secondary schools in FY 20 and FY 21


Revenues from COVID-19 Federal Assistance Funds for public elementary and secondary education totaled $25.3 billion, or 28.6 percent of all federal revenues.

  • Revenues from the Federal Coronavirus Relief Fund accounted for $8.9 billion, or 35.2 percent of total revenues from COVID-19 Federal Assistance Funds.
     
  • Revenues from the Elementary and Secondary School Emergency Relief (ESSER I) Fund accounted for $8.5 billion, or 33.7 percent of total revenues from COVID-19 Federal Assistance Funds.
     
  • Revenues from the Elementary and Secondary School Emergency Relief (ESSER II) Fund accounted for $6.5 billion, or 25.8 percent of total revenues from COVID-19 Federal Assistance Funds.

 

Expenditures

Current expenditures for public elementary and secondary education across the nation increased by 0.7 percent between FY 20 and FY 21 (from $698.3 to $703.5 billion). Within that increase, expenditures for instruction increased by 1.1 percent between FY 20 and FY 21 (from $422.4 to $427.1 billion), and student support expenditures increased by 3.6 percent between FY 20 and FY 21 (from $44.0 to $45.6 billion).

Current expenditures per pupil for the day-to-day operation of public elementary and secondary schools was $14,295 in FY 21, an increase of 3.5 percent from FY 20.3 In FY 21, education spending was 16.7 percent higher than at the lowest point of the Great Recession in FY 13.


Figure 1. National inflation-adjusted current expenditures per public for public elementary and secondary education: Fiscal years 2012 through 2021

 

NOTE: Spending is reported in constant FY 21 dollars, based on the Consumer Price Index (CPI). National totals include the 50 states and the District of Columbia. California did not report prekindergarten membership in the State Nonfiscal Survey of Public Elementary/Secondary Education. California reported prekindergarten expenditures separately, and these expenditures were excluded from the amounts reported in this figure.
SOURCE: U.S. Department of Education, National Center for Education Statistics, Common Core of Data (CCD), “National Public Education Financial Survey,” fiscal years 2012 through 2020, Final Version 2a; and fiscal year 2021, Provisional Version 1a; and Digest of Education Statistics 2021, table 106.75. Retrieved March 9, 2023, from nces.ed.gov/programs/digest/d21/tables/dt21_106.75.asp.


Without making adjustments for geographic cost differences, current expenditures per pupil ranged from $9,014 in Utah to $26,097 in New York. In addition to New York, current expenditures per pupil were highest in the District of Columbia ($25,113), Vermont ($24,050), New Jersey ($22,784), and Connecticut ($22,216). In addition to Utah, current expenditures per pupil were lowest in Idaho ($9,054), Arizona ($9,571), Mississippi ($10,060), and Nevada ($10,073). The states with the largest increases in current expenditures per pupil from FY 20 to FY 21 were Maine (11.9 percent), Arizona (7.6 percent), Montana (7.4 percent), Louisiana (7.3 percent), and Massachusetts (6.6 percent).


Image of NPEFS data visualization site showing current expenditures per pupil for public elementary and secondary schools in FY 20 and FY 21


In FY 21, salaries and wages ($389.2 billion) in conjunction with employee benefits ($169.7 billion) accounted for 79.4 percent ($558.8 billion) of current expenditures for public elementary and secondary education. Expenditures for instruction and instructional staff support services comprised 65.8 percent ($462.9 billion) of total current expenditures.

Between FY 20 and FY 21, total expenditures increased by 0.2 percent (from $812.3 to $813.6 billion). Of the $813.6 billion in total expenditures in FY 21, 86.5 percent were current expenditures, 9.8 percent were capital outlay expenditures, 2.7 percent were interest on debt, and 1.1 percent were expenditures for other programs.

Current expenditures from federal Title I grants for economically disadvantaged students (including carryover expenditures) accounted for $16.3 billion, or 2.3 percent of current expenditures for public elementary and secondary education at the national level in FY 21. Nationally, Title I expenditures per pupil averaged $331 and ranged from $123 in Utah to $874 in New York.

Current expenditures paid from COVID-19 Federal Assistance Funds for public elementary and secondary education totaled $24.2 billion for the 50 states and the District of Columbia. Of these, instructional expenditures accounted for $13.7 billion, or 56.5 percent of current expenditures paid from COVID-19 Federal Assistance Funds, and support services expenditures accounted for $9.1 billion, or 37.6 percent of current expenditures paid from COVID-19 Federal Assistance Funds.

To explore data on public elementary and secondary revenues, expenditures, and ADA, check out our new data visualization tool.

Be sure to follow NCES on TwitterFacebookLinkedIn, and YouTube and subscribe to the NCES News Flash to stay up-to-date on the latest from the National Public Education Financial Survey.

 

By Stephen Q. Cornman, NCES, and Malia Howell and Jeremy Phillips, U.S. Census Bureau

 


[1] Spending refers to current expenditures. Current expenditures are composed of expenditures for the day-to-day operation of schools and school districts for public elementary and secondary education, including expenditures for staff salaries and benefits, supplies, and purchased services. Current expenditures include instruction, instruction-related, support services (e.g., social work, health, and psychological services), and other elementary/secondary current expenditures but exclude expenditures on capital outlay, other programs, and interest on long-term debt.

[2] Throughout this blog post, all comparisons between years are adjusted for inflation by converting the figures to constant dollars. Inflation adjustments utilize the Consumer Price Index (CPI) published by the U.S. Department of Labor, Bureau of Labor Statistics. For comparability to fiscal education data, NCES adjusts the CPI from a calendar year to a school fiscal year basis (July through June). See Digest of Education Statistics 2021, table 106.70.

[3] Per pupil expenditures are calculated using student membership derived from the State Nonfiscal Survey of Public Elementary/Secondary Education. In some states, adjustments are made to ensure consistency between membership and reported fiscal data. More information on these adjustments can be found in the data file documentation.

Rescaled Data Files for Analyses of Trends in Adult Skills

In January 2022, NCES released the rescaled data files for three adult literacy assessments conducted several decades earlier: the 1992 National Adult Literacy Survey (NALS), the 1994 International Adult Literacy Survey (IALS), and the 2003 Adult Literacy and Lifeskills Survey (ALL). By connecting the rescaled data from these assessments with data from the current adult literacy assessment, the Program for the International Assessment of Adult Competencies (PIAAC), researchers can examine trends on adult skills in the United States going back to 1992. This blog post traces the history of each of these adult literacy assessments, describes the files and explains what “rescaling” means, and discusses how these files can be used in analyses in conjunction with the PIAAC files. The last section of the post offers several example analyses of the data.

A Brief History of International and National Adult Literacy Assessments Conducted in the United States

The rescaled data files highlighted in this blog post update and combine historical data from national and international adult literacy studies that have been conducted in the United States.

NALS was conducted in 1992 by NCES and assessed U.S. adults in households, as well as adults in prisons. IALS—developed by Statistics Canada and ETS in collaboration with 22 participating countries, including the United States—assessed adults in households and was administered in three waves between 1994 and 1998. ALL was administered in 11 countries, including the United States, and assessed adults in two waves between 2003 and 2008.

PIAAC seeks to ensure continuity with these previous surveys, but it also expands on their quality assurance standards, extends the definitions of literacy and numeracy, and provides more information about adults with low levels of literacy by assessing reading component skills. It also, for the first time, includes a problem-solving domain to emphasize the skills used in digital (originally called “technology-rich”) environments.

How Do the Released Data Files From the Earlier Studies of Adult Skills Relate to PIACC?

All three of the released restricted-use data files (for NALS, IALS, and ALL) relate to PIAAC, the latest adult skills assessment, in different ways.

The NALS data file contains literacy estimates and background characteristics of U.S. adults in households and in prisons in 1992. It is comparable to the PIAAC data files for 2012/14 and 2017 through rescaling of the assessment scores and matching of the background variables to those of PIAAC.

The IALS and ALL data files contain literacy (IALS and ALL) and numeracy (ALL) estimates and background characteristics of U.S. adults in 1994 (IALS) and 2003 (ALL). Similar to NALS, they are comparable to the PIAAC restricted-use data (2012/14) through rescaling of the literacy and numeracy assessment scores and matching of the background variables to those of PIAAC. These estimates are also comparable to the international estimates of skills of adults in several other countries, including in Canada, Hungary, Italy, Norway, the Netherlands, and New Zealand (see the recently released Data Point International Comparisons of Adult Literacy and Numeracy Skills Over Time). While the NCES datasets contain only the U.S. respondents, IALS and ALL are international studies, and the data from other participating countries can be requested from Statistics Canada (see the IALS Data Files/Publications and ALL Data pages for more detail). See the History of International and National Adult Literacy Assessments page for additional background on these studies. 

Table 1 provides an overview of the rescaled NALS, IALS, and ALL data files.


Table 1. Overview of the rescaled data files for the National Adult Literacy Survey (NALS), International Adult Literacy Survey (IALS), and Adult Literacy and Lifeskills Survey (ALL) 

Table showing overview of the rescaled data files for the National Adult Literacy Survey (NALS), International Adult Literacy Survey (IALS), and Adult Literacy and Lifeskills Survey


What Does “Rescaled” Mean?

“Rescaling” the literacy (NALS, IALS, ALL) and numeracy (ALL) domains from these three previous studies means that the domains were put on the same scale as the PIAAC domains through the derivation of updated estimates of proficiency created using the same statistical models used to create the PIAAC skills proficiencies. Rescaling was possible because PIAAC administered a sufficient number of the same test questions used in NALS, IALS, and ALL.1 These rescaled proficiency estimates allow for trend analysis of adult skills across the time points provided by each study.

What Can These Different Files Be Used For?

While mixing the national and international trend lines isn’t recommended, both sets of files have their own distinct advantages and purposes for analysis.

National files

The rescaled NALS 1992 files can be used for national trend analyses with the PIAAC national trend points in 2012/2014 and 2017. Some potential analytic uses of the NALS trend files are to

  • Provide a picture of the skills of adults only in the United States;
  • Examine the skills of adults in prison and compare their skills with those of adults in households over time, given that NALS and PIAAC include prison studies conducted in 1992 and 2014, respectively;
  • Conduct analyses on subgroups of the population (such as those ages 16–24 or those with less than a high school education) because the larger sample size of NALS allows for more detailed breakdowns along with the U.S. PIAAC sample;
  • Focus on the subgroup of older adults (ages 66–74), given that NALS sampled adults over the age of 65, similar to PIAAC, which sampled adult ages 16–74; and
  • Analyze U.S.-specific background questions (such as those on race/ethnicity or health-related practices).

International files

The rescaled IALS 1994 and ALL 2003 files can be used for international trend analyses among six countries with the U.S. PIAAC international trend point in 2012/2014: Canada, Hungary, Italy, Norway, the Netherlands, and New Zealand. Some potential analytic uses of the IALS and ALL trend files are to

  • Compare literacy proficiency results internationally and over time using the results from IALS, ALL, and PIAAC; and
  • Compare numeracy proficiency results internationally and over time using the results from ALL and PIAAC.

Example Analyses Using the U.S. Trend Data on Adult Literacy

Below are examples of a national trend analysis and an international trend analysis conducted using the rescaled NALS, IALS, and ALL data in conjunction with the PIAAC data.

National trend estimates

The literacy scores of U.S. adults increased from 269 in NALS 1992 to 272 in PIAAC 2012/2014. However, the PIAAC 2017 score of 270 was not significantly different from the 1992 or 2012/2014 scores.


Figure 1. Literacy scores of U.S. adults (ages 16–65) along national trend line: Selected years, 1992–2017

Line graph showing literacy scores of U.S. adults (ages 16–65) along national trend line for NALS 1992, PIAAC 2012/2014, and PIAAC 2017

* Significantly different (p < .05) from NALS 1992 estimate.
SOURCE: U.S. Department of Education, National Center for Education Statistics, National Adult Literacy Survey (NALS), NALS 1992; and Program for the International Assessment of Adult Competencies (PIAAC), PIAAC 2012–17.


International trend estimates

The literacy scores of U.S. adults decreased from 273 in IALS 1994 to 268 in ALL 2003 before increasing to 272 in PIAAC 2012/2014. However, the PIAAC 2012/2014 score was not significantly different from the IALS 1994 score.


Figure 2. Literacy scores of U.S. adults (ages 16–65) along international trend line: Selected years, 1994–2012/14

Line graph showing literacy scores of U.S. adults (ages 16–65) along international trend line for IALS 1994, ALL 2003, and PIAAC 2012/2014

* Significantly different (p < .05) from IALS 1994 estimate.
SOURCE: U.S. Department of Education, National Center for Education Statistics, Statistics Canada and Organization for Economic Cooperation and Development (OECD), International Adult Literacy Survey (IALS), 1994–98; Adult Literacy and Lifeskills Survey (ALL), 2003–08; and Program for the International Assessment of Adult Competencies (PIAAC), PIAAC 2012/14. See figure 1 in the International Comparisons of Adult Literacy and Numeracy Skills Over Time Data Point.


How to Access the Rescaled Data Files

More complex analyses can be conducted with the NALS, IALS, and ALL rescaled data files. These are restricted-use files and researchers must obtain a restricted-use license to access them. Further information about these files is available on the PIAAC Data Files page (see the “International Trend Data Files and Data Resources” and “National Trend Data Files and Data Resources” sections at the bottom of the page).

Additional resources:

By Emily Pawlowski, AIR, and Holly Xie, NCES


[1] In contrast, the 2003 National Assessment of Adult Literacy (NAAL), another assessment of adult literacy conducted in the United States, was not rescaled for trend analyses with PIAAC. For various reasons, including the lack of overlap between the NAAL and PIAAC literacy items, NAAL and PIAAC are thought to be the least comparable of the adult literacy assessments.