IES Blog

In part 1 of this blog series, we highlight the benefits and advantages of using federal education data for policymaking at the federal, state, and district levels. In part 2, we will explore the challenges of and opportunities afforded by using these data.

States, districts, and schools are inundated with requests for data. To manage the volume of requests and avoid overwhelming educators, many districts have established processes to vet and limit the number of surveys allowed in their schools and administrative offices. District clearance processes are also understandably meant to make sure everyone is in compliance with data privacy laws. NCES data collections are sometimes not cleared by district offices, which then means NCES is not allowed to contact schools or educators to learn from their perspectives or experiences.

Since many state or district policymakers prioritize local survey collections, federal surveys are occasionally rejected by district offices that are striving to keep from overburdening their educators with too many survey requests. Without district permission, NCES surveys won’t include the educators in those schools, meaning that those districts’ voices will be missing from the table when decisions are made. This is problematic for the entire education system for a few reasons.

1. Local data rarely reach federal policymakers. We know state and district decisionmakers derive a lot of value from state and/or district survey collections—since they’re designed to provide detailed local data—and do not always see value in federal data collection and reporting efforts. More localized data are critical to their day-to-day decisions. However, the presence of numerous state-run surveys—in addition to the myriad individualized district surveys that can exist within a single state—has begun to create a data silo where information remains frozen within a state or district system. Since NCES (and therefore the Department of Education and Congress) rarely receives data from state or local collections, these data sources cannot readily be used to generate national policies, which greatly limits opportunities for state and district systems to learn from each other. These data silos can, for example, impact the focus or breadth of federal grants or funding available for schools.
   
   Federal, state, and district education agencies serve different roles in the education sector but have mutually beneficial responsibilities that should complement and support one another. The solution isn’t to supplant federal data collections with local ones, or vice versa, but instead to supplement local collections with federal collections like the National Teacher and Principal Survey (NTPS) so education decisionmakers at all levels have access to necessary information to make good decisions for our schools.
    
2. Benchmarking and comparability are limited. Without federal data collections, it can be difficult or impossible for states, districts, and local policymakers to compare their schools and educators with those in other areas because of the lack of common focus and definitions across data collections. Even if the topics being collected are similar, individualized district or state surveys can differ widely in both content and wording.
   
   National data collections—like the NTPS—are excellent tools local policymakers should use when setting priorities on behalf of the students and staff in their state or district. Since the data from the NTPS are collected from educators in the same way across the entire country, they can be used to establish benchmarks against which local collections can measure themselves.
    
3. Lack of participation decreases the representativeness of storytelling. If districts do not approve NCES’s survey research applications, we are unable to reach educators in certain schools, which can limit the kinds of perspectives that are included in the data. To paint a true picture of the education landscape, our survey teams select districts, schools, and/or educators that are as representative of the education field as possible.
   
   Teachers and principals who participate in NCES studies are grouped in different ways—such as by age, race/ethnicity, or the type of school at which they work—and their information is studied to identify patterns of experiences that people in these different groups may have had. This is what makes our datasets representative, or similar enough to the demographics of the population to able to accurately reflect the characteristics of everyone (even those who aren’t sampled to participate).
   
   For example, the NTPS is designed to support analysis of a variety of subgroups, such as those by

• school level (i.e., elementary, middle, high, and combined);
   
• school community type (i.e., urban, suburban, town, and rural);
   
• teachers’ and principals’ years of experience in the profession; and
   
• race/ethnicity of teachers and principals (figure 1).

These diverse subgroups are critically important for both federal and local policymakers who want to make decisions using information that truly represents everyone in the field.

Figure 1. Percentage of K–12 public and private school teachers who reported that they have any control over various areas of planning and teaching in their classrooms, by school type and selected school characteristic: 2020–21 

NOTE: Data are weighted estimates of the population. Response options included “no control,” “minor control,” “moderate control,” and “a great deal of control.” Teachers who reported “minor control,” “moderate control,” or “a great deal of control” were considered to have reported having “any control.”
SOURCE: U.S. Department of Education, National Center for Education Statistics, National Teacher and Principal Survey (NTPS), “Public and Private School Teacher Data File,” 2020–21.

Larger datasets allow for more nuanced comparisons by school, principal, or teacher characteristics that aren’t possible in smaller datasets, allowing for more equity in national and local estimates and more distinct answers to key policy questions. But we need district-level support to provide these nuanced data.

Although the NTPS has a fairly large sample to support state representation, it still only includes a small percentage of all schools and educators in the country. Sampling is used to avoid collecting data from all systems, staff, and students, thus helping to limit overall respondent burden on our education system. For this reason, it’s important that all sampled schools and educators participate if selected. Since some districts also have formal review processes—through which a survey must be approved before any schools or educators can be contacted—it is also important that districts with sampled schools grant NCES surveys permission to collect data from their schools.

Both levels of participation will help us collect data that accurately describe a state or population. Otherwise, the story we are telling in the data is only augmenting some voices—and these are the experiences that will be reflected in federal policy and funding.

As the education sector strives to understand the needs of students and staff on the tails of the coronavirus pandemic, trustworthy data are only becoming more critical to the decisionmaking process. NCES datasets like the NTPS are critical resources that federal, state, and district policymakers can and have used for benchmarking strategic goals or conducting analyses on how a topic has (or hasn’t) changed over time.

The catch being, of course, that all data on the NTPS—and many other NCES surveys—come directly from schools, principals, and teachers themselves. These analyses and reports are not possible without district and educator participation. While it may seem counterintuitive that any one person could make such a large difference in federal education policy, the concept doesn’t differ from civic duties such as voting in federal or local elections.

By Maura Spiegelman and Julia Merlin, NCES

June is LGBTQ+ Pride Month, and NCES is proud to share some of the work we have undertaken to collect data on the characteristics and well-being of sexual and gender minority populations.

Inclusion of questions about sexual orientation and gender identity on federal surveys allows for better understanding of sexual and gender minority populations relative to the general population. These sexual orientation and gender identity (SOGI) data meet a critical need for information to understand trends within larger population groups, and insights gained from analysis of the data can lead to potential resources and needed interventions being provided to better serve the community. Giving respondents the opportunity to describe themselves and bring their “whole self” to a questionnaire helps them to be seen and heard by researchers and policymakers.

Sometimes, NCES is asked why questions like this appear on an education survey. They can be sensitive questions for some people, after all. NCES asks these questions to be able to understand the different experiences, equity, and outcomes related to education for sexual and gender minorities, just as NCES does for groups identified by other demographic characteristics like race, ethnicity, household income, and what part of the country someone lives in. By sexual minorities, we mean people who report their sexual orientation to be something other than straight or heterosexual, and by gender minorities, we mean people whose sex as recorded at birth is different from their gender.

Over the past 10 years, NCES has researched how to best ask respondents about their sexual orientation and gender identity, how respondents react to these questions, and the quality of data that NCES has collected on these characteristics.

At NCES, several studies include background questions for adults about their sexual orientation and gender identity. These are the High School Longitudinal Study: 2009 (HSLS:09) Second Follow-up in 2016, the Baccalaureate and Beyond Longitudinal Study (B&B) 08/18 and 16/21 collections, the National Postsecondary Student Aid Study (NPSAS) in 2020, and the Beginning Postsecondary Students Longitudinal Study (BPS) 2020/22 (see table below for more details about these surveys).

The collection of these data allows NCES to describe the experiences of gender and sexual minority individuals. For example:

• In 2020, postsecondary students who identified as genderqueer, gender nonconforming, or a different identity had difficulty finding safe and stable housing at three times the rate (9 percent) of students who identified as male or female (3 percent each).¹
   
• In 2018, about 10 years after completing a 2007–08 bachelor’s degree, graduates who were gender minorities² described their financial situations. Graduates who were gender minorities were less likely to own a home (31 percent) or hold a retirement account (74 percent) than graduates who were not gender minorities (63 percent and 87 percent, respectively) (figure 1).³  

The Common Core of Data (CCD) contains basic information on public elementary and secondary schools, local education agencies (LEAs), and state education agencies (SEAs) in the United States. The CCD collects fiscal and nonfiscal data about all public schools, public school districts, and state education agencies in the United States. Both IPEDS and CCD provide a sampling frame to many survey collections, including many conducted by NCES and the Department of Education. This blog post, one in a series of posts about CCD nonfiscal data, focuses on CCD’s two major releases and their corresponding components. For information on how to access and use CCD data, read the blog post Accessing the Common Core of Data (CCD).
 

Data Releases

CCD nonfiscal data are published in two releases every school year—as preliminary files and as provisional data files—within the CCD Data File tool. Understanding the differences between the two releases is important to understand how CCD nonfiscal data are released.

• The preliminary files contain basic information about schools and districts, such as name, address, phone number, status, and NCES ID number. Many schools and districts utilize information from the directory file, such as the NCES ID, to apply for grants or other opportunities for their schools. Therefore, it is important that these files are released first, even if the data are still preliminary. 
   
• The provisional data files are the full release of the CCD nonfiscal data. These data files provide school-, district-, and state-level data on topics like enrollment, staffing, and free or reduced-price lunch. These files are much more detailed and include data that are broken down by characteristics such as grade, race/ethnicity, and gender—as well as by combinations of these characteristics. These files are not updated unless there is a significant change to the data.

Each file release includes a version that indicates the type of release. The first preliminary files have “0a” in the file names, and revised preliminary files include “0b,” “0c,” and so on. The first provisional files have “1a,” in the file names, and revised provisional files include “1b,” “1c,” and so on. Note, however, that releasing revised files is rare.
 

Components of a Release

It is important to utilize the various components that accompany each release to find additional information that is specific to the file and can help you better understand the data. In addition, there are other resources available that provide more ways to access and understand the data.
 

Documentation Components

Every data file will have documentation files that provide information about the data. These include the following:

• release notes—basic information about the data release, including details about any changes to the files, such as a change in a variable’s description or a variable that was added to the file; summary tables that include national totals and tables with selected frequencies are also included.
   
• state data notes—information on data anomalies that are discovered during NCES’s collaboration with the states; broken down by state and by file type, these notes describe things like changes to how data were collected by the state.
   
• companion files—included in each data file component, these files include a list of all the variables in the data file—including a brief description—and frequency tables; you should start with the companion files to better understand what variables are in each data file.

Resources and Tools

Along with the release of the CCD nonfiscal data files, additional resources are also updated to improve access to the data.

• Summary Tables: Released with the provisional data files, Summary Tables provide a national-level look at the data. These tables show the operational status of schools and districts by type as well as the number of schools, students, and teachers by state.
   
• Locators and ElSi: There are two primary tools that can be used to access CCD data: the Locators (School Locator and District Locator) and the Elementary/Secondary Information System (ElSi). These tools are updated as the data files are released. The Locators are updated with each release, while ElSi is updated with the release of the provisional data files. Learn more about these tools.
   
• Online Documentation: The online documentation provides some general information about CCD. This information is not year specific, but it provides a detailed explanation about how the data are collected, processed, and reviewed.

• Reference Library: The reference library includes detailed documentation on various components of the CCD files that applies to multiple years, levels, and components of the data collection. The library includes crosswalks, documentation describing changes to the collection, and guidance for utilizing the data files, such as how to aggregate free or reduced-price lunch data.

Be sure to follow NCES on Twitter, Facebook, LinkedIn, and YouTube and subscribe to the NCES News Flash to stay up-to-date on future CCD releases and resources.

By Patrick Keaton, NCES

Happy Get Ready for Kindergarten Month! 

For more than 20 years, the National Center for Education Statistics (NCES) has been collecting information about kindergartners’ knowledge and skills as part of the Early Childhood Longitudinal Studies (ECLS) program.

The first ECLS, the Early Childhood Longitudinal Study, Kindergarten Class of 1998–99 (ECLS-K), focused on children in kindergarten in the 1998–99 school year. At the time the ECLS-K began, no large national study focused on education had followed a cohort of children from kindergarten entry through the elementary school years. Some of today’s commonly known information about young children, such as the information about kindergartners’ early social and academic skills shown in the infographics below, comes out of the ECLS-K. For example, we all know that children arrive at kindergarten with varied knowledge and skills; the ECLS-K was the first study to show at a national level that this was the case and to provide the statistics to highlight the differences in children’s knowledge and skills by various background factors.

The second ECLS kindergarten cohort study, the Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K:2011), is the ECLS-K’s sister study. This study followed the students who were in kindergarten during the 2010–11 school year. The ECLS-K:2011, which began more than a decade after the inception of the ECLS-K, allows for comparisons of children in two nationally representative kindergarten classes experiencing different policy, educational, and demographic environments. For example, significant changes that occurred between the start of the ECLS-K and the start of the ECLS-K:2011 include the passage of No Child Left Behind legislation, a rise in school choice, and an increase in English language learners. 

From the parents of children in the ECLS-K:2011, we learned how much U.S. kindergartners like school, as shown in the following infographic.

The ECLS program studies also provide information on children’s home learning environments and experiences outside of school that may contribute to learning. For example, we learned from the ECLS-K:2011 what types of activities kindergartners were doing with their parents at least once a month (see the infographic below).

What’s next for ECLS data collections on kindergartners? NCES is excited to be getting ready to launch our next ECLS kindergarten cohort study, the Early Childhood Longitudinal Study, Kindergarten Class of 2023–24 (ECLS-K:2024). 

Before the ECLS-K:2024 national data collections can occur, the ECLS will conduct a field test—a trial run of the study to test the study instruments and procedures—in the fall of 2022.

If you, your child, or your school are selected for the ECLS-K:2024 field test or national study, please participate! While participation is voluntary, it is important so that the study can provide information that can be used at the local, state, and national levels to guide practice and policies that increase every child’s chance of doing well in school. The ECLS-K:2024 will be particularly meaningful, as it will provide important information about the experiences of children whose early lives were shaped by the COVID-19 pandemic.

Watch this video to learn more about participation in the ECLS-K:2024. For more information on the ECLS studies and the data available on our nation’s kindergartners, see the ECLS homepage, review our online training modules, or email the ECLS study team.

By Jill Carlivati McCarroll, NCES

For more than 3 decades, the Integrated Postsecondary Education Data System (IPEDS) has collected data from all postsecondary institutions participating in Title IV federal student aid programs, including universities, community colleges, and vocational and technical schools.

Since 2000, the 12 IPEDS survey components occurring in a given collection year have been organized into three seasonal collection periods: Fall, Winter, and Spring.

The timing of when data are collected (the “collection year”) is most important for the professionals who report their data to the National Center for Education Statistics (NCES). However, IPEDS data users are generally more interested in the year that is actually reflected in the data (the “data year”). As an example, a data user may ask, “What was happening with students, staff, and institutions in 2018–19?"

For data users, knowing the difference between the collection year and the data year is important for working with and understanding IPEDS data. Often, the collection year comes after the data year, as institutions need time to collect the required data and check to make sure they are reporting the data accurately. This lag between the time period reflected by the data and when the data are reported is typically one academic term or year, depending on the survey component. For example, fall 2021 enrollment data are not reported to NCES until spring 2022, and the data would not be publicly released until fall 2022.

After the data are collected by NCES, there is an additional time period before they are released publicly in which the data undergo various quality and validity checks. About 9 months after each seasonal collection period ends (i.e., Fall, Winter, Spring), there is a Provisional Data Release and IPEDS data products (e.g., web tools, data files) are updated with the newly released seasonal data. During this provisional release, institutions may revise their data if they believe it was inaccurately reported. A Revised/Final Data Release then happens the following year and includes any revisions that were made to the provisional data.

Sound confusing? The data collection and release cycle can be a technical and complex process, and it varies slightly for each of the 12 IPEDS survey components. Luckily, NCES has created a comprehensive resource page that provides information about the IPEDS data collection and release cycles for each survey component as well as key details for data users and data reporters, such as how to account for summer enrollment in the different IPEDS survey components.

Table 1 provides a summary of the IPEDS 2021–22 data collection and release schedule information that can be found on the resource page. Information on the data year and other details about each survey component can also be found on the resource page.

Table 1. IPEDS 2021–22 Data Collection and Release Schedule

Here are a few examples of how to distinguish the data year from the collection year in different IPEDS data products.

Example 1: IPEDS Trend Generator

Suppose that a data user is interested in how national graduation rates have changed over time. One tool they might use is the IPEDS Trend Generator. The Trend Generator is a ready-made web tool that allows users to view trends over time on the most frequently asked subject areas in postsecondary education. The Graduation Rate chart below displays data year (shown in green) in the headline and on the x-axis. The “Modify Years” option also allows users to filter by data year. Information about the collection year (shown in gold) can be found in the source notes below the chart.

Example 2: IPEDS Complete Data Files

Imagine that a data user was interested enough in 6-year Graduation Rates that they wanted to run more complex analyses in a statistical program. IPEDS Complete Data Files include all variables for all reporting institutions by survey component and can be downloaded by these users to create their own analytic datasets.

Data users should keep in mind that IPEDS Complete Data Files are organized and released by collection year (shown in gold) rather than data year. Because of this, even though files might share the same collection year, the data years reflected within the files will vary across survey components.

The examples listed above are just a few of many scenarios in which this distinction between collection year and data year is important for analysis and understanding. Knowing about the IPEDS reporting cycle can be extremely useful when it comes to figuring out how to work with IPEDS data. For more examples and additional details on the IPEDS data collection and release cycles for each survey component, please visit the Timing of IPEDS Data Collection, Coverage, and Release Cycle resource page.

Be sure to follow NCES on Twitter, Facebook, LinkedIn, and YouTube, follow IPEDS on Twitter, and subscribe to the NCES News Flash to stay up-to-date on all IPEDS data releases.

By Katie Hyland and Roman Ruiz, American Institutes for Research