IES Blog

The short answer to this question is reliability. However, new 2019 data from the National Household Education Surveys (NHES) program indicate that parents typically consider many factors when choosing care arrangements for their young children.  

The Early Childhood Program Participation: 2019 survey found that 59 percent of children age 5 and under were in a care arrangement (including care from a relative other than a parent, care from a nonrelative, or attendance at a preschool or day care) in 2019. The parents of these children were asked how important various factors were when choosing their child’s care arrangement. The reliability of the arrangement was the factor most often rated as “very important”: 87 percent of children had parents who rated reliability as very important when choosing a care arrangement for their child (figure 1). This factor was followed by available times for care and qualifications of staff (75 and 72 percent, respectively). A majority of children’s parents also rated the following factors as very important:

• Learning activities (68 percent)
• Location (60 percent)
• Time spent with other children (59 percent)
• Cost (55 percent)

Figure 1. Among children age 5 and under who were not yet in kindergarten and were in at least one weekly care arrangement, percentage whose parents indicated that the factor was “very important” when choosing child’s care arrangement: 2019

SOURCE: Cui, J., and Natzke, L. (2020). Early Childhood Program Participation: 2019 (NCES 2020-075). U.S. Department of Education. Washington, DC: National Center for Education Statistics.

For many factors, the percentage of children whose parents rated the factor as very important when choosing a care arrangement was similar across the children’s age ranges. However, for 5 of the 11 factors, ratings varied depending on the child’s age. For example, the percentage of children whose parents rated time spent with other children as very important increased with the age of the child (figure 2). Similarly, learning activities were rated as very important more often for children ages 3–5 (74 percent) than for younger children (59 percent for children under age 1; 64 percent for children ages 1–2).

Figure 2.  Among children age 5 and under who were not yet in kindergarten and were in at least one weekly care arrangement, percentage whose parents indicated that the factor was “very important” when choosing child’s care arrangement, by age of child: 2019

SOURCE: Cui, J., and Natzke, L. (2020). Early Childhood Program Participation: 2019 (NCES 2020-075). U.S. Department of Education. Washington, DC: National Center for Education Statistics.

The opposite pattern was true for the number of children in group and website ratings. Both of these factors were rated as very important more often by parents of children under age 1 (51 and 35 percent, respectively) than by parents of children ages 3–5 (40 and 25 percent, respectively).

More detailed information about child care arrangements is available in Early Childhood Program Participation: 2019. For a look at why parents of K–12 students choose schools for their children, check out this blog post and the recent NCES release Parent and Family Involvement in Education: 2019.

By Lisa Hudson, NCES

We know a lot about how people learn and the strategies and principles that promote learning and retention, but much of it gets stuck in translation between research and practice. Through the Cognition and Student Learning program, the Institute of Education Sciences (IES) supports projects that try to bridge that gap. Pooja Agarwal has been a researcher for multiple Cognition and Student Learning projects. She was also a Harry S. Truman Foundation Scholarship recipient, which gave her the opportunity to work as an intern at IES for a summer. She received her PhD from Washington University of St. Louis and is currently an Assistant Professor at Berklee College of Music and founder of RetrievalPractice.org. Here she shares some reflections on how IES and its grants programs have influenced her career and the field, culminating in a book she recently published with collaborator Patrice Bain, Powerful Teaching: Unleash the Science of Learning.

Fifteen years ago, I was double majoring in cognitive neuroscience and elementary education at Washington University in St. Louis. One semester, I was taking a psychology class on human memory on one side of campus and a class on K–12 social studies teaching methods on the other side of campus. I felt frustrated that the psychology class was too esoteric, thinking that’s not how memory works in the “real world.” Meanwhile, I felt the social studies methods class was too anecdotal; we were being told to teach the way the professor taught without any evidence to support their methods.

Around the same time, the Institute of Education Sciences (IES) was born, bridging the gap between research and practice. I was enthralled by the legislative authorization bill (yes, I was that college student). The more I read about IES, the more I was convinced that transformation of the education system through research was not only possible–it was starting to happen. Simply put, this was my coveted “lightbulb moment.”

Subsequently, I spent a summer as an intern at IES, and the following fall, my mentor Henry L. Roediger, III (“Roddy”) and colleagues received a Cognition and Student Learning (CASL) grant from IES (2006-2010). This opportunity was a perfect fit with my growing passion: I would be embedded in K–12 classrooms leading rigorous research on learning and memory.

Our research centered around extending a laboratory-based principle, retrieval practice, into the classroom. Retrieval practice is the process by which learners recall or retrieve information they have previously learned, which subsequently improves their long-term retention for that information. For example, do you know the fourth president of the United States? Your mental struggle is referred to as a “desirable difficulty,” which will help you remember the name of the president (it’s listed at the end of this blog).

Our first experiments on retrieval practice were conducted with Patrice Bain, a 6th grade world history teacher at Columbia Middle School in Columbia, Illinois. Initially, we compared student performance after lessons with brief quizzes vs. lessons without quizzes. Importantly, Patrice’s curriculum stayed the same; we simply included frequent retrieval practice. In one set of experiments, for example, retrieval practice boosted grades from a C to an A level, with benefits lasting nine months later, until the end of the school year. By year two, we were collecting data on a scale we never had in the lab, in various grade levels and content areas. We were fortunate to continue our research with a second CASL grant (2011-2014), publishing numerous peer-review publications, presenting at academic conferences, and creating a practice guide for educators on the research and implementation of retrieval practice in the classroom. I recently completed a review of the literature on retrieval practice, screening more than 2,000 abstracts and narrowing them down to 50 selected experiments. The majority of experiments demonstrated that retrieval practice consistently boosted student learning, regardless of type (for example, multiple-choice or short answer), spacing over time, or education level.

To get this information into the hands of educators around the world, my fellow cognitive scientists and I have written and disseminated 6 practice guides available in 6 languages, which have been downloaded more than 100,000 times. I continue to develop a community of more than 15,000 educators around the world via social media (Twitter and Facebook), a weekly newsletter, and articles and podcasts. Of course, our own research on retrieval practice informs my own teaching as a college professor on a daily basis.

Most recently, I co-authored a book, Powerful Teaching: Unleash the Science of Learning, with aforementioned collaborator Patrice Bain. Educators are given the impossible challenge of seeking out good research, making sense of it, and applying it in the classroom. It is impossible because this research isn’t accessible–literally and figuratively. In line with IES’s mission, we aimed to increase access to cognitive science research and make it applicable for today’s classrooms.

In Powerful Teaching, we focused on four teaching strategies we call Power Tools: retrieval practice, spacing, interleaving, and feedback-driven metacognition, all of which are supported by research from the CASL grants program.

1. Retrieval practice boosts learning by pulling information out of students’ heads, rather than cramming information into students’ heads.
2. Spacing boosts learning by spreading lessons and retrieval opportunities out over time, so learning is not crammed all at once. In this way, forgetting is a good thing for learning.
3. Interleaving boosts learning by mixing up closely related topics, encouraging discrimination between similarities and differences.
4. Feedback-driven metacognition boosts learning by providing the opportunity for students to know what they know and know what they don’t know.

The four Power Tools are flexible, practical, and quick to implement. By focusing on just a few carefully selected strategies, educators are empowered to harness cognitive science, without being stretched too thin. We have found these elements–accessibility and feasibility–to be critical if educators are to implement research-based strategies in their classrooms.

I say all this because I want to emphasize that IES–and the people behind the scenes–is much more than a granting agency. IES provides opportunities and support for applied research in education that can inform practice and make a difference in the classroom. Sometimes, all it takes is a lightbulb moment to spark a transformation.

Endnote: The fourth president of the United States was James Madison.

Pooja K. Agarwal, PhD (@RetrieveLearn) is a cognitive scientist, conducting research on how students learn since 2005. She is the author of the book Powerful Teaching: Unleash the Science of Learning and an Assistant Professor of Psychology at the Berklee College of Music in Boston. Pooja is also the Founder of RetrievalPractice.org, a source of research-based teaching strategies for more than 15,000 educators around the world.

The coronavirus pandemic forced teachers across the world to immediately transition instruction to a virtual setting in early 2020. To understand U.S. teachers’ level of preparedness for this shift in an international context, this blog examines recent international data from U.S. teachers’ responses to questions on the following topics:

• Their perceptions of information and communications technologies (ICT) resources
• Their use of ICT for instruction prior to the pandemic

In general, the results suggest that U.S. teachers are more resourced in ICT than their international peers, and they use ICT at a similar frequency at school when teaching.

Teachers’ perceptions of ICT resources at their school

The quantity and quality of ICT resources available in school systems prior to the coronavirus pandemic may impact teachers’ access to such resources for instructional purposes while classrooms are functioning in a virtual format. The United States participated in the 2018 International Computer and Information Literacy Study (ICILS), which asked questions about ICT resources to a nationally representative sample of eighth-grade teachers from 14 education systems.

The results from this study show that 86 percent of eighth-grade teachers both in the United States and across ICILS 2018 education systems “strongly agreed” or “agreed” that ICT is considered a priority for use in teaching (figure 1). Compared with the ICILS 2018
averages,^[1] higher percentages of U.S. eighth-grade teachers “strongly agreed” or “agreed” with various statements about the use of ICT.

While 86 percent of U.S. eighth-grade teachers “strongly agreed” or “agreed” that “ICT is considered a priority for use in teaching,” only 61 percent “strongly agreed” or “agreed” that “there is sufficient opportunity for me to develop expertise in ICT” (figure 1). Additionally, 62 percent of U.S. eighth-grade teachers “strongly agreed” or “agreed” that “there is enough time to prepare lessons that incorporate ICT.” These disparities may have had an impact on teacher capacity during the sudden shift to 100 percent online learning as a result of the coronavirus pandemic, which would be a good topic for future research and analyses.  

Figure 1. Percentage of eighth-grade teachers who reported that they “strongly agree” or “agree” with statements about using ICT in teaching at school, by statement: 2018

* p < .05. Significantly different from the U.S. estimate at the .05 level of statistical significance.

¹ Did not meet the guidelines for a sample participation rate of 85 percent and not included in the international average.
² National Defined Population covers 90 to 95 percent of National Target Population.
NOTE: ICT = information and communications technologies. The ICILS 2018 average is the average of all participating education systems meeting international technical standards, with each education system weighted equally. Statements are ordered by the percentages of U.S. teachers reporting “strongly agree” or “agree” from largest to smallest.
SOURCE: International Association for the Evaluation of Educational Achievement (IEA), The International Computer and Information Literacy Study (ICILS), 2018. Modified reproduction of figure 17 from U.S. Results from the 2018 ICILS Web Report.

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Teachers’ perceptions of the use of ICT for instruction

Teachers’ views on the role of ICT in virtual instruction during the coronavirus pandemic are not yet clear. However, in 2018, when instruction was conducted in physical classrooms, most U.S. eighth-grade teachers participating in ICILS expressed positive perceptions about “using ICT in teaching and learning at school,” as did many teachers internationally.

Among eighth-grade teachers in the United States, 95 percent agreed that ICT “enables students to access better sources of information,” 92 percent agreed that ICT “helps students develop greater interest in learning,” and 92 percent agreed that ICT “helps students work at a level appropriate to their learning needs.” On average across other education systems participating in ICILS, at least 85 percent of teachers agreed with each of these statements (Fraillon et al. 2019).

Seventy-five percent of U.S. eighth-grade teachers in 2018 agreed that ICT “improves academic performance of students,” which was higher than the ICILS international average of 71 percent. The percentages of teachers who agreed with this statement varied across education systems, from three-quarters or more of teachers in Chile, Denmark, Kazakhstan, and Portugal to less than half of teachers in Finland and North Rhine-Westphalia (Germany).

 

Frequency of teachers’ use of ICT

Teachers’ reported use of ICT for instruction in physical classroom settings may provide insight into their level of experience as they transition to virtual settings during the coronavirus pandemic.

In 2018, half of U.S. eighth-grade teachers reported “using ICT at school when teaching” every day, which was not significantly different from the ICILS average of 48 percent. However, the U.S. percentage was lower than the percentages of teachers in Moscow (76 percent), Denmark (72 percent), and Finland (57 percent) (figure 2).

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Figure 2. Percentage of eighth-grade teachers who reported using ICT at school every day when teaching, by education system: 2018

* p < .05. Significantly different from the U.S. estimate at the .05 level of statistical significance.
¹ Met guidelines for sample participation rates only after replacement schools were included.
² National Defined Population covers 90 to 95 percent of National Target Population.
³ Did not meet the guidelines for a sample participation rate of 85 percent and not included in the international average.
⁴ Data collected at the beginning of the school year.
NOTE: ICT = information and communications technologies. The ICILS 2018 average is the average of all participating education systems meeting international technical standards, with each education system weighted equally. Education systems are ordered by their percentages of teachers reporting using ICT at school when teaching from largest to smallest. Italics indicate the benchmarking participants.
SOURCE: International Association for the Evaluation of Educational Achievement (IEA), The International Computer and Information Literacy Study (ICILS), 2018. Modified reproduction of figure 15 from U.S. Results from the 2018 ICILS Web Report.

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For more information on teachers and technology, check out NCES’s ICILS 2018 website, the international ICILS website, and the earlier NCES blog “New Study on U.S. Eighth-Grade Students’ Computer Literacy.”

 

By Amy Rathbun, AIR, and Stephen Provasnik, NCES

 

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[1] The ICILS average is the average of all participating education systems meeting international technical standards, with each education system weighted equally. The United States did not meet the guidelines for a sample participation rate of 85 percent, so it is not included in the international average.

Reference

Fraillon, J., Ainley, J., Schulz, W., Friedman, T., and Duckworth, D. (2019). Preparing for Life in a Digital World: IEA International Computer and Information Literacy Study 2018 International Report. Amsterdam: International Association for the Evaluation of Educational Achievement.

Every year in the Common Core of Data (CCD), NCES releases data on the number of students eligible for the National School Lunch Program (NSLP), a U.S. Department of Agriculture (USDA) meal program that provides nutritionally balanced low-cost or free meals to children during the school day. The program was established under the National School Lunch Act, signed into law by President Harry Truman in 1946, and currently serves nearly 30 million children.

This post highlights substantial changes to the NSLP and related changes in CCD reporting and provides guidance on how to use the NSLP data.

Free or Reduced-Price Lunch vs. Direct Certification

Historically, student eligibility for free or reduced-price lunch (FRPL) was determined through individual students submitting school meals application forms within school districts. In 1986, the USDA introduced a direct certification option to reduce participation barriers in the school meal program. Under direct certification, any child belonging to a household that participates in Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF), Food Distribution Program on Indian Reservations (FDPIR), or (in some states) Medicaid—as well as children who are migrant, homeless, in foster care, or in Head Start—are categorically eligible to receive free meals at school.

The NSLP data included in CCD releases include school-level FRPL and direct certification eligibility counts for all public schools with students enrolled. These point-in-time counts are taken on or around October 1 of each school year and reported by the states based on the following guidance: 

• FRPL-Eligible Students
  • Free lunch students: those eligible to participate in the Free Lunch Program (i.e., those with family incomes below 130 percent of the poverty level or who are directly certified)
  • Reduced-price lunch students: those eligible to participate in the Reduced-Price Lunch Program (i.e., those with family incomes between 130 and 185 percent of the poverty level)
  • Free and reduced-price lunch student: the total of free lunch students and reduced-price lunch students
• Direct Certification
  • The number of students reported as categorically eligible to receive free meals to the USDA for the FNS 742. Students are categorically eligible to receive free meals if they belong to a household receiving the selected federal benefits noted above or are migrant, homeless, in foster care, or in Head Start.

The count of students eligible for free lunch includes students directly certified plus any students who qualified for free lunch by completing a school meals application. As such, the number of students reported as directly certified should always be less than or equal to the number of free lunch students.

Note that changes in SNAP (both legislated eligibility requirements and temporary changes such as national disasters) can have implications for reported NSLP eligibility as well.

The Healthy, Hunger-Free Kids Act of 2010

In 2010, the Healthy, Hunger-Free Kids Act (HHFKA) established national nutrition standards for food served and sold in schools and made changes to the NSLP to increase food access. These changes also impacted the NSLP data published through CCD:

• While direct certification had been an option since 1986, HHFKA mandated that states directly certify NSLP eligibility for at least 95 percent of SNAP participants. With the mandated use of direct certification, several states stopped reporting FRPL eligibility entirely. 
• HHFKA introduced the Community Eligibility Provision (CEP) to expand access to free meals to all students in low-income areas. Schools qualifying under CEP no longer count students who qualify for reduced-price lunch since all students are provided a free lunch. CEP schools may report all students as eligible for free lunch regardless of economic status, since all students are provided a free lunch.

Guidance for Data Users

The NSLP eligibility data published through CCD are often used by researchers as a proxy measure for the number of students living in poverty. However, there are limitations to the usefulness of these data that researchers should consider when using NSLP data.

The NSLP data published through CCD has changed over time. CCD published just FRPL counts through SY 2015–16. Starting in SY 2016–17, states can report FRPL and/or direct certification eligibility counts for each school, and CCD publishes both FRPL and direct certification, as reported by the states.^[1]

When creating state and national estimates (including tables in the Digest of Education Statistics), NCES uses FRPL counts when they are available. If FRPL data are not available, direct certification data is used as a proxy. For this type of analysis, NCES includes all schools for which both student enrollment data and FRPL or direct certification were reported. States that only reported direct certification are footnoted. NCES recommends that data users be mindful of the reporting differences when analyzing or drawing conclusions with these data.

The NSLP data meet a variety of critical analysis needs to help policy makers, researchers, and the public target resources and answer policy questions. CCD is the only source of nationwide school-level NSLP data. Explore NSLP data as well as all of the other CCD data elements available either by using the CCD data query tool or by downloading data files directly.

By Beth Sinclair, AEM, and Chen-Su Chen, NCES