IES Blog

Institute of Education Sciences

Announcing the Condition of Education 2018 Release

We are pleased to present The Condition of Education 2018, a congressionally mandated annual report summarizing the latest data on education in the United States. This report is designed to help policymakers and the public monitor educational progress. This year’s report includes 47 indicators on topics ranging from prekindergarten through postsecondary education, as well as labor force outcomes and international comparisons. 

In addition to the regularly updated annual indicators, this year’s spotlight indicators highlight new findings from recent NCES surveys. The first spotlight indicator examines the choices and costs that families face as they select early childhood care arrangements. Drawing on data from the NCES National Household Education Survey, the indicator finds that early childhood care expenses were higher in 2016 than in 2001. For example, families’ average hourly out-of-pocket expenses for center-based care were 72 percent higher in 2016 ($7.60) than in 2001 ($4.42), in constant 2016–17 dollars. The indicator also finds that in 2016, some 57 percent of children under the age of 6 had parents who reported there were good choices for child care where they lived. Among children whose parents reported difficulty finding child care in 2016, some 32 percent cited cost as the primary reason. The complete indicator, Early Childhood Care Arrangements: Choices and Costs, contains more information about how these findings varied by family income, race/ethnicity, locale (urban, suburban, town, or rural), and children’s age.


Average hourly out-of-pocket child care expense for children under 6 years old and not yet in kindergarten whose families paid for child care, by primary type of child care arrangement: 2001 and 2016

1 Center-based arrangements include day care centers, Head Start programs, preschools, prekindergartens, and childhood programs.
NOTE: Estimates include only those children whose families paid at least part of the cost out of pocket for their child to receive nonparental care at least weekly.
SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Program Participation Survey of the National Household Education Surveys Program (ECPP-NHES: 2001 and 2016). See Digest of Education Statistics 2017, table 202.30c.


The second spotlight describes the characteristics of teachers who entered the teaching profession through an alternative route to certification program. Compared to those who entered through a traditional route, higher percentages of alternative route teachers in 2015–16 were Black (13 vs. 5 percent), Hispanic (15 vs. 8 percent), of Two or more races (2 vs. 1 percent), and male (32 vs. 22 percent), and lower percentages were White (66 vs. 83 percent). Overall, 18 percent of public school teachers in 2015–16 had entered teaching through an alternative route to certification program. The percentages were higher among those who taught career or technical education (37 percent), natural sciences (28 percent), foreign languages (26 percent), English as a second language (24 percent), math and computer science (22 percent), and special education (20 percent). The analysis also examines how the prevalence of alternative route teachers varies between charter schools and traditional public schools, between high and low poverty schools, and between schools that enroll high or low percentages of racial/ethnic minority students. For more findings from this analysis of data from the National Teacher and Principal Survey, see the complete indicator, Characteristics of Public School Teachers Who Completed Alternative Route to Certification Programs.


Percentage distribution of public elementary and secondary school teachers, by route to certification and race/ethnicity: 2015–16

NOTE: Teachers were asked whether they entered teaching through an alternative route to certification program, which is a program that was designed to expedite the transition of nonteachers to a teaching career (for example, a state, district, or university alternative route to certification program). Detail may not sum to totals because of rounding. Race categories exclude persons of Hispanic ethnicity. Data for American Indian/Alaska Native teachers who entered teaching through a traditional route and Pacific Islander teachers who entered teaching through traditional and alternative routes round to zero and are not displayed.
SOURCE: U.S. Department of Education, National Center for Education Statistics, National Teacher and Principal Survey (NTPS), “Public School Teacher Data File,” 2015–16. See Digest of Education Statistics 2017, table 209.24.


The third spotlight presents data on average student loan balances for students completing graduate degrees. Using data from the National Postsecondary Student Aid Study, this indicator examines how average student loan balances changed between 1999–2000 and 2015–16, and how those trends varied by degree type. Among graduate school completers who had student loans for undergraduate or graduate studies, average student loan balances increased for all degree types (in constant 2016–17 dollars). For example, average student loan balances for students who completed research doctorate degrees, such as a Ph.D., doubled during this time period, from $53,500 to $108,400 (an increase of 103 percent). Average student loan balances increased by 90 percent for those who completed professional doctorate degrees, such as medical doctorates and law degrees (from $98,200 to $186,600). The complete indicator, Trends in Student Loan Debt for Graduate School Completers, also describes how average student loan balances varied among specific degree programs, such as medical doctorates, law degrees, and master’s degrees in business administration.


Average cumulative student loan balance for graduate school completers, by degree type: Selected years, 1999–2000 through 2015–16

1 Includes chiropractic, dentistry, law, medicine, optometry, pharmacy, podiatry, and veterinary medicine. 
NOTE: Data refer to students who completed graduate degrees in the academic years indicated. Includes student loans for undergraduate and graduate studies. Average excludes students with no student loans.
SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999–2000, 2003–04, 2007–08, 2011–12, and 2015–16 National Postsecondary Student Aid Study (NPSAS:2000, NPSAS:04, NPSAS:08, NPSAS:12, and NPSAS:16). See Digest of Education Statistics 2017, table 332.45.


The Condition includes an At a Glance section, which allows readers to quickly make comparisons within and across indicators, and a Highlights section, which captures key findings from each indicator. The report contains a Reader’s Guide, a Glossary, and a Guide to Sources that provide additional background information. Each indicator provides links to the source data tables used to produce the analyses.

As new data are released throughout the year, indicators will be updated and made available on The Condition of Education website. In addition, NCES produces a wide range of reports and datasets designed to help inform policymakers and the public. For more information on our latest activities and releases, please visit our website or follow us on Twitter, Facebook, and LinkedIn.

By James L. Woodworth, NCES Commissioner 

Computerized Preschool Language Assessment Extends to Toddlers

Identifying young children with language delays can improve later outcomes

Language is a core ability that children must master for success both in and out of the classroom. Extensive studies have shown that many tasks, including math, depend on linguistic skill, and that early language skills are predictive of school readiness and academic success. Being able to quickly identify children at early ages with language delays is crucial for targeting effective interventions.

Enter the QUILS.

In 2011, the National Center for Education Research (NCER) at IES funded a 4-year grant to Dr. Roberta Golinkoff (University of Delaware) and Drs. Kathy Hirsh-Pasek (Temple University) and Jill de Villiers (Smith College) to develop a valid and reliable computer-based language assessment for preschoolers aged 3-5 years old. The resulting product was the Quick Interactive Language Screener (QUILS), a computerized tool to measure vocabulary, syntax, and language acquisition skills. The assessment ultimately measures what a child knows about language and how a child learns, and automatically provides results and reports to the teacher.

The preschool version of QUILS is now being used by early childhood educators, administrators, reading specialists, speech-language pathologists, and other early childhood professionals working with young children to identify language delays. The QUILS is also being utilized in other learning domains. For example, a new study relied on the QUILS, among other measures, to examine links between approaches to learning and science readiness in over 300 Head Start students aged 3 to 5 years.

QUILS is now being revised for use with toddlers. In 2016, the National Center for Special Education Research (NCSER) funded a 3-year study to revise the QUILS for use with children aged 24-36 months. The researchers have been testing the tool in both laboratory and natural (child care centers, homes, and Early Head Start programs) settings to determine which assessment items to use in the toddler version of QUILS. Ultimately, these researchers aim to develop a valid and reliable assessment to identify children with language delays so that appropriate interventions can begin early.

By Amanda M. Dettmer, AAAS Science & Technology Policy Fellow Sponsored by the American Psychological Association Executive Branch Science Fellowship

The experiences of our nation’s young children from kindergarten through fourth grade

By Jill Carlivati McCarroll and Gail M. Mulligan

In 2014–15, boys had higher fourth-grade math scores than girls, but no significant differences were found in boys’ versus girls’ fourth-grade reading knowledge and skills. These findings come from the most recent data release for the Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K:2011). A recently released report provides a first look at the status of students who were in kindergarten for the first time during the 2010-11 school year and were in fourth grade in 2014-15. The longitudinal nature of this study allows for a comparison of trends over time. For example, differences in math scores between boys and girls were also observed in third grade but not in earlier grades. No significant differences in reading results for boys and girls have been detected in any grade between kindergarten and fourth. More data on assessment scores, as well as the demographic and family characteristics of the cohort of students who were first-time kindergartners in 2010-11, are available in the reports.

The series of Early Childhood Longitudinal Studies are consistently some of the most popular NCES studies due in large part to the fact that they provide comprehensive and reliable data on important topics such as child development, school readiness, and early school experiences. The ECLS-K:2011 was designed to provide data that can be used to describe and to better understand children’s development and experiences in the elementary grades, and how children’s early experiences relate to their later development, learning, and experiences in school. The study is longitudinal, meaning that it followed the same group of children over time; in the case of the ECLS-K:2011, children were followed from their kindergarten year (the 2010-11 school year) until the spring of 2016, when most of the children were in the fifth grade.

All planned waves of data through fifth grade have been collected and staff at the National Center for Education Statistics (NCES) are hard at work releasing reports of the findings as well as the data from all rounds of the study. Researchers, educators, policy makers, and other interested members of the public now have access to much of the important data from the ECLS-K:2011, with additional reports and data releases on their way.

The diverse sample of children who participated in the ECLS-K:2011 is nationally representative of students who were in kindergarten in U.S. schools in the 2010-11 school year. Information on children’s cognitive, social, emotional, and physical development was collected every year using direct child assessments and surveys for the adults central to the children’s education. Adults surveyed for the study included the children’s parents/guardians, their teachers, their school administrators, and their kindergarten before- and after-school care providers. Topics covered by the surveys included the children’s home environment, home educational activities, school environment, classroom environment, classroom curriculum, teacher qualifications, and before- and after-school care. 

Public-use data from the kindergarten through fourth-grade rounds of the ECLS-K:2011 are now available online. A restricted-use dataset with data from the kindergarten through fourth-grade rounds is also available to qualified researchers with an IES Restricted-use Data License. For information on licensing, please see https://nces.ed.gov/pubsearch/licenses.asp. The schedule of future data releases is available on the ECLS website.

For more information on the ECLS-K:2011 as well as the other ECLS studies, please see our homepage or email the ECLS study team at ECLS@ed.gov.  

Taking Education Research Out of the Lab and Into the Real World

The Institute of Education Sciences is committed to supporting research that develops and tests solutions to the challenges facing education in the United States and working to share the results of that research with a broad audience of policymakers and practitioners. In this blog post, Katherine Pears (pictured right), a principal investigator from the Oregon Social Learning Center, shares how an IES-funded grant supported not only the development and testing of an intervention, but its implementation in classrooms.

Sometimes when I tell people that I am a research scientist, they say "Ok, but what do you do?" What they are really asking is whether the work I am doing is helping students and families in actual schools and community. It’s a good question and the short answer is “Yes!” but moving programs from the research lab to children, families and schools takes time and funding. Here is how it worked with my program.

I wanted to help children at risk for school failure to start kindergarten with skills to help them to do better. I teamed up with Dr. Phil Fisher and others, and we built on years of research and program development at the Oregon Social Learning Center (OSLC) to create a program called Kids in Transition to School (KITS). This is a summer program that continues into the first few weeks of school and focuses not only on letters and numbers, but also on teaching children how to get along with others and how to learn (such as focusing their attention). We also train the KITS teachers to use positive teaching strategies and help parents learn the same techniques to increase the chances that children will succeed.

However, before a school will put a program like KITS in place, they need to have some proof that it will actually work. That is why we sought external funding to evaluate the program.  With funding from the Institute of Education Sciences (IES), as well as the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Institute on Drug Abuse (NIDA), we were able to test KITS with three different groups of children at high risk for difficulties in school: children in foster care, children with developmental disabilities and behavior problems, and children from low-income neighborhoods. 

Across these studies, KITS led to positive outcomes for children and the parents. Funding from IES helped us show that the KITS Program worked with different groups of children and that it was a good candidate for use in school settings. In many cases, this is where the process of moving programs from research to practice can get bogged down due to a gap between researchers and the people in the education systems that could use the programs. IES is strongly committed to bridging that gap by supporting partnerships between researchers and practitioners. In our IES-funded study, we partnered with two of our local school districts and United Way of Lane County (UWLC). Working with the schools and community agencies helped us to both test KITS and develop plans for how the districts could keep the program going after the funding for the research study ended.

Our partnership with UWLC also enabled us to start a new project to bring KITS to more schools. With funding from the Corporation for National and Community Service (CNCS) Social Innovation Fund, UWLC offered grants to education foundations in Lane County, Oregon to implement KITS in the local school districts. The Social Innovation Fund allows promising programs to be brought to scale (i.e., made available to large numbers of people) by providing funding for community agencies to start and develop plans for sustaining these programs. In 2015, the KITS Program had about 30 educators serving about 120 children and families in 6 school districts in Lane County, Oregon. By summer 2017, two years into the grant, the KITS Program had trained 125 educators to serve approximately 435 children and families in 13 school districts in the county. That’s more than a threefold increase in the number of children and families served, as well as the number of teachers trained in the KITS Program.

We will continue to work with partners to evaluate the effects of the KITS program and make it available to more school districts. However, without the funding from IES and other federal agencies, we would not have been able to both test the program and partner with schools to make KITS a part of their everyday practice. 

 

Risk Factors and Academic Outcomes in Kindergarten through Third Grade

By Amy Rathbun, AIR and Joel McFarland

Previous NCES research has shown that students with family risk factors tend to have lower average scores than their peers on academic assessments.[1] Risk factors can include coming from a low-income family or single-parent household, not having a parent who completed high school, and living in a household where the primary language is not English. How common is it for children entering U.S. kindergartens to have certain types of family risk factors? And, how do children with risk factors at kindergarten entry perform on academic assessments compared to their peers?  A new spotlight from The Condition of Education 2017 helps to answer these questions.

The spotlight focuses on children experiencing two types of risk factors - living in poverty (i.e., in households with income below the federal poverty threshold) and not having a parent who completed high school, as well as the combination and lack of the two risk factors. Data come from the Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K:2011). During the 2010–11 school year, 6 percent of first-time kindergartners had both risk factors , 18 percent had the single risk factor of living in poverty, and 2 percent had the single risk factor of not having a parent who completed high school. About 75 percent had neither of these two risk factors present during their kindergarten year.


Percentage distribution of fall 2010 first-time kindergartners, by risk factors related to parent education and poverty: School year 2010–11

NOTE: Detail may not sum to totals because of rounding.
SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K:2011), Kindergarten–Third Grade Restricted-Use Data File. See Digest of Education Statistics 2016, table 220.39.


Are there differences in the prevalence of risk factors by student and family characteristics?

There were differences in the prevalence of family risk factors in relation to children’s race/ethnicity, primary home language, and family composition. For instance, it was more common for Hispanic students (15 percent) than for Black and Asian students (8 percent each) to have both risk factors, and these percentages were all higher than the percentage for White students (1 percent). Also, 23 percent of first-time kindergartners whose primary home language was not English had both the risk factor of living in poverty and the risk factor of not having a parent who completed high school, compared with 2 percent of kindergartners whose primary home language was English.

Does children’s performance in reading, math, and science in kindergarten through third grade differ based on risk factors?

Kindergarten students living in poverty and those with no parent that completed high school tended to score lower in reading, mathematics, and science over each of their first four years of school compared to their peers who had neither risk factor at kindergarten entry. For example, in the spring of third-grade, reading scores (on a scale of 0 to 141) were higher, on average, for students who had neither risk factor (114 points) than for those with the single risk factor of living in poverty (106 points), those with the single risk factor of not having a parent who completed high school (105 points), and those with both risk factors (102 points).[2]


Average reading scale scores of fall 2010 first-time kindergartners, by time of assessment and risk factors related to parent education and poverty: Fall 2010 through spring 2014

NOTE: Estimates weighted by W7C17P_7T170. Scores on the reading assessments reflect performance on questions measuring basic skills (print familiarity, letter recognition, beginning and ending sounds, rhyming words, and word recognition); vocabulary knowledge; and reading comprehension, including identifying information specifically stated in text (e.g., definitions, facts, and supporting details), making complex inferences from texts, and considering the text objectively and judging its appropriateness and quality. Possible scores for the reading assessment range from 0 to 141.
SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K:2011), Kindergarten–Third Grade Restricted-Use Data File. See Digest of Education Statistics 2016, table 220.40.


For more information on family risk factors and children’s achievement in reading, mathematics, and science from the fall of kindergarten through the spring of third grade, see the spotlight on this topic in The Condition of Education 2017.

[1] Given that the spring third-grade reading scores have a mean of 110.2 points and a standard deviation (SD) of 12.3 points, this would mean the average score for children who had no risk factors was about 1.0 SD higher than the score for children with no risk factors.

[2] Rathbun, A., and West, J. (2004). From Kindergarten Through Third Grade: Children's Beginning School Experiences (NCES 2004–007). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved March 2, 2017, from https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2004007.