IES Blog

Institute of Education Sciences

Recognizing Asian and Pacific Islander Educators with the National Teacher and Principal Survey (NTPS)

May is Asian American and Pacific Islander Heritage Month, which celebrates the achievements of Asian/Pacific Islander Americans and immigrants and the many ways they have contributed to the United States.

In honor of Asian and Native Hawaiian/Pacific Islander1 educators who help students learn every day, here are some selected facts and figures from the 2017–18 National Teacher and Principal Survey (NTPS). The NTPS collects data about public and private K–12 schools in the United States from the perspective of the teachers and principals who staff them. These data were collected in 2017–18, prior to the coronavirus pandemic.

 

Composition of U.S. K12 Public and Private Schools: 201718

  • Although Native Hawaiian/Pacific Islander teachers and principals are important members of school communities, they comprise a relatively small percentage of public and private school educators overall. Less than 1 percent of either public or private school teachers (0.2 and 0.1 percent,2 respectively) and principals (0.2 percent and 0.3 percent,3 respectively) were Native Hawaiian/Pacific islander.

Figure 1. Percentage distribution of all teachers and principals who are Asian and Native Hawaiian/Pacific Islander, by school type: 201718

! Interpret data with caution. The coefficient of variation (CV) for this estimate is between 30 and 50 percent.
NOTE: Race categories exclude persons of Hispanic ethnicity.
SOURCE: U.S. Department of Education, National Center for Education Statistics, National Teacher and Principal Survey (NTPS), "Public School Teacher and Private School Teacher Data File, Public School Principal and Private School Principal Data File," 2017–18


Community and K12 School Characteristics: 201718

  • A higher percentage of Asian teachers worked in city schools than in most other community types (i.e., suburb, town, and rural) in 2017–18. There were some differences by school type (i.e., public vs. private).4 For example, teacher employment patterns in both school types were similar at rural schools and city schools but different at suburban schools.
  • Higher percentages of Asian teachers worked in both public and private city schools (3.1 and 3.8 percent, respectively) than in public and private rural schools (0.5 and 0.8 percent, respectively) (figure 2).
  • Although a lower percentage of Asian private school teachers worked in suburban schools (2.3 percent) than in city schools (3.8 percent), there was no significant difference in the percentage of Asian public school teachers who worked in suburban versus city schools.

Figure 2. Percentage distribution of all teachers who are Asian and Native Hawaiian/Pacific Islander, by school type and community type: 201718

# Rounds to zero
! Interpret data with caution. The coefficient of variation (CV) for this estimate is between 30 and 50 percent.
‡ Reporting standards not met. The coefficient of variation (CV) for this estimate is 50 percent or greater (i.e., the standard error is 50 percent or more of the estimate) or the response rate is below 50 percent.
NOTE: Race categories exclude persons of Hispanic ethnicity.
SOURCE: U.S. Department of Education, National Center for Education Statistics, National Teacher and Principal Survey (NTPS), "Public School Teacher and Private School Teacher Data File," 2017–18


In honor of Asian American and Pacific Islander Heritage Month, NCES would like to thank Asian and Pacific Islander educators nationwide who play vital roles in our education system.

The data in this blog would not be possible without the participation of teachers, principals, and school staff in the NTPS. We are currently conducting the 2020–21 NTPS to learn more about teaching experiences during the pandemic. If you were contacted about participating in the 2020–21 NTPS and have questions, please email ntps@census.gov or call 1-888-595-1338.

For more information about the National Teacher and Principal Survey (NTPS), please visit https://nces.ed.gov/surveys/ntps/. More findings and details are available in the NTPS schoolteacher, and principal reports.

 

[1] The NTPS definition of “Asian American or Native Hawaiian/Pacific Islander” is synonymous with the Library of Congress’ term “Asian/Pacific Islander.” The Library of Congress, one of the sponsors of the heritage month, states that Asian/Pacific encompasses all of the Asian continent and the Pacific islands of Melanesia (New Guinea, New Caledonia, Vanuatu, Fiji and the Solomon Islands), Micronesia (Marianas, Guam, Wake Island, Palau, Marshall Islands, Kiribati, Nauru and the Federated States of Micronesia) and Polynesia (New Zealand, Hawaiian Islands, Rotuma, Midway Islands, Samoa, American Samoa, Tonga, Tuvalu, Cook Islands, French Polynesia and Easter Island). Note that the Hawaiian Islands are included as “Pacific islands” in their definition but are named independently in the NTPS definition, and that only Asian or Native Hawaiian/Pacific Islander respondents who also indicated that they were not Hispanic, which includes Latino, are included in this definition.

[2] Interpret data with caution. The coefficient of variation (CV) for this estimate is between 30 percent and 50 percent (i.e., the standard error is at least 30 percent and less than 50 percent of the estimate).

[3] Interpret data with caution. The coefficient of variation (CV) for this estimate is between 30 percent and 50 percent (i.e., the standard error is at least 30 percent and less than 50 percent of the estimate).

[4] Given the size of the Native Hawaiian/Pacific Islander teacher and principal populations in the NTPS, granular differences about where Native Hawaiian/Pacific Islander teachers and principals were more often employed is difficult to produce from a sample survey because of sample sizes.

 

By Julia Merlin, NCES

Identifying Virtual Schools Using the Common Core of Data (CCD)

With the sudden changes in education due to the coronavirus pandemic, virtual instruction is in the spotlight more than ever before. Prior to the pandemic, there were already increasing numbers of virtual public schools that offered instructional programs to those that may have difficulty accessing or attending traditional brick-and-mortar schools. Even before the pandemic, some schools and districts were using virtual instruction in new ways, such as switching to virtual instruction on snow days rather than cancelling school. Throughout the pandemic, schools and districts have been relying more heavily on virtual instruction than ever before.

Since school year (SY) 2013–14, the Common Core of Data (CCD) has included a school-level virtual status flag, which has changed over time. For SY 2020–21, the Department of Education instructed states to classify schools that are normally brick-and-mortar schools but are operating remotely during the pandemic as supplemental virtual (see table below).

 

SY 201314 Through SY 201516

Virtual status is a Yes/No flag, meaning that a school was either virtual or not virtual based on the following definition: “A public school that offers only instruction in which students and teachers are separated by time and/or location, and interaction occurs via computers and/or telecommunications technologies. A virtual school generally does not have a physical facility that allows students to attend classes on site.”

 

SY 201617 and Onward

NCES changed the virtual status flag to be more nuanced. Rather than just a Yes/No flag, the reported value indicates virtual status on a spectrum using the following values:

 

Permitted Value Abbreviation

Definition

FULLVIRTUAL

Exclusively virtual. All instruction offered by the school is virtual. This does not exclude students and teachers meeting in person for field trips, school-sponsored social events, or assessment purposes. All students receive all instruction virtually. Prior to SY 2019–20, this value was labeled as “Fully virtual.”

FACEVIRTUAL

Primarily virtual. The school’s major purpose is to provide virtual instruction to students, but some traditional classroom instruction is also provided. Most students receive all instruction virtually. Prior to SY 2019–20, this value was labeled as “Virtual with face to face options.”

SUPPVIRTUAL

Supplemental virtual. Instruction is directed by teachers in a traditional classroom setting; virtual instruction supplements face-to-face instruction by teachers. Students vary in the extent to which their instruction is virtual.

NOTVIRTUAL

No virtual instruction. The school does not offer any virtual instruction.  No students receive any virtual instruction. Prior to SY 2019–20, this value was labeled as “Not virtual.”

 

Generally, data users should treat the value “FULLVIRTUAL” (exclusively virtual) under the new approach as the equivalent of Virtual=Yes in the old approach. The virtual flag is a status assigned to a school as of October 1 each school year. 

The number of exclusively virtual schools has increased in the past several years. In SY 2013–14, there were a total of 478 exclusively virtual schools reported in CCD (approximately 0.5% of all operational schools). In SY 2019–20 there were 691 schools (approximately 0.7% of all operational schools) that were exclusively virtual. The student enrollment in exclusively virtual schools also increased from 199,815 students in SY 2013–14 to 293,717 in SY 2019–20, which is an increase from 0.4% of the total student enrollment in public schools to 0.6%.

Of the 691 virtual schools in SY 2019–20, 590 were reported as “regular” schools, meaning they offered a general academic curriculum rather than one focused on special needs or vocational education, 218 were charter schools, and 289 were high schools. Of the 8,673 schools that were reported as either primary virtual or supplemental virtual, 7,727 were regular schools, 624 were charter schools, and 4,098 were high schools.

To see tables summarizing the above data, visit our Data Tables web page and select the nonfiscal tables.

To learn more about the CCD, visit our web page. For more information about how to access CCD data, including tips for using the District and School Locators and the Elementary and Secondary Information System, read the blog post “Accessing the Common Core of Data (CCD).” You can also access the raw data files for additional information about public elementary and secondary schools. Enrollment and staff data for SY 2020–21 are currently being collected, processed, and verified and could be released by spring 2022.

 

By Patrick Keaton, NCES

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

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