IES Blog

In her first IES grant, Dr. Elizabeth Tighe (Georgia State University) is taking expertise honed in both an NCER predoctoral fellowship and PIAAC methods training program to help further adult literacy research. Her earlier work includes developing assessments for adults with low literacy, leveraging statistical approaches to understand these adults’ abilities and difficulties, and using eye-tracking paradigms to explore their ability to self-monitor during reading. 

Program officer, Meredith Larson, interviewed Dr. Tighe about her previous work and new grant.

What is your general area of research, and why is it important?

I focus on adult struggling readers, which comprises roughly 36 million (1 in 6) adults in the U.S. Only a fraction of these adults enroll in adult education programs, which are plagued by insufficient funding, high teacher turnover rates, and a lack of research-based instructional practices and curricula. By better understanding these adults’ strengths and deficits and how best to measure their skills, I aim to inform and improve adult education programs.

What could people do with your research?

My research could directly inform how we help adults become stronger readers, and this can improve educational outcomes, such as GED attainment. I am working towards building better assessments for adult education practitioner and researcher use. My longer-term goal is to design a curriculum to teach morphology (e.g., prefixes and suffixes) and use this to improve adults’ vocabulary and reading comprehension.

What are you trying to learn through your new IES project?

For this grant, I’m using the Program for the International Assessment of Adult Competencies (PIAAC), a large-scale, international assessment of adult literacy, numeracy, and digital problem-solving skills, to create risk profiles of adults with low literacy skills. This sort of information could move us closer to being able to individualize instruction in adult education programs to match the needs of specific learners.

We will use PIAAC data to explore how demographic characteristics (age, race/ethnicity, educational background, employment status) and malleable factors (enjoyment of learning, frequency of computer use, reading and writing behaviors at home and at work) influence low literacy performance.

Further, we are examining whether risk factors differ by whether someone has a high school diploma and whether someone has participated in education or training recently. We will also explore whether reading components and literacy skills are predictive of low-skilled adults’ numeracy skills.

Our findings could have important implications for understanding risk factors and predictors of low literacy as well as low numeracy. As stated previously, 1 in 6 U.S. adults have low literacy skills and nearly 1 in 3 have low numeracy skills. For GED attainment, adults must demonstrate proficiency in both of these areas (along with science, social studies, and writing knowledge). It’s important to have targeted, individualized instruction for these adults because they may have time or resource barriers.

How did this particular research project arise?

I first learned about PIAAC at a summer institute. I was intrigued, in particular, because PIAAC is the first assessment of this size to include a reading component supplement for lower-skilled adults.

I recently attended a 3-day NCER/ETS PIAAC training workshop, which allowed me to work with PIAAC data and network with others. This workshop influenced my decision to apply for an IES grant. I felt that a 2-year grant using extant data would be a great way to combine my interests regarding individual differences in adults’ component skills and get my feet wet with IES as a new investigator. I am excited to bridge my interests and grow as a researcher by learning and working alongside two experts (Drs. Yaacov Petscher and John Sabatini) in the larger reading and education field!

Charter school enrollment has grown significantly over time. Between fall 2000 and fall 2015, overall public charter school enrollment increased from 0.4 million to 2.8 million students, and the percentage of public school students who attended charter schools increased from 1 to 6 percent. The number of charter schools also increased during this period, from 1,990 to 6,860.

The characteristics of charter schools and traditional public schools differ in some ways. A higher percentage of charter schools are located in cities and a lower percentage are located in rural areas as compared to traditional public schools.

There are also some differences in the characteristics of students who attend charter schools and traditional public schools. A higher percentage of charter schools had higher percentages of minority students enrolled. In school year 2015–16, more than half of the students were White in 58 percent of traditional public schools. In comparison, 34 percent of charter schools had more than 50 percent White enrollment. In 9 percent of traditional public schools more than half of students were Black compared to 23 percent for charter schools. In 16 percent of traditional public schools, more than half of students were Hispanic compared to 25 percent for charter schools.

High-poverty schools are those in which more than 75 percent of students qualify for free or reduced-price lunch (FRPL) under the National School Lunch Program. In the 2015–16 school year, 24 percent of traditional public schools were high-poverty compared with 35 percent of public charter schools. In contrast, low-poverty schools–in which less than 25 percent of students qualify for FRPL–accounted for 16 percent of traditional public schools and 21 percent of public charter schools.

Access indicators from the Condition of Education on the characteristics of traditional public schools and public charter schools as well as charter school enrollment for more data!

By Lauren Musu

English learners (ELs) can be a tricky student population to study. In some ways, these students who are learning English as part of their education are a homogenous population. For example, more than 75% of them speak Spanish, and more than half of the nation's 4.8 million EL students  are concentrated in grades K – 3. On the other hand, EL education can be very context-driven. For example, districts and states vary considerably both in the composition of their particular EL population, and in the specific policies, assessments, and instructional supports they use to guide ELs’ education.

In response to this latter point, some NCER grantees have figured out that one good way to study and support EL education is by working in close partnership with a specific education agency. In other words, don’t fight the place-based nature of EL education – rather, use it as an asset to make your research even more relevant.

There are several examples of IES-funded projects that have successfully worked using this approach. The most obvious are eight Researcher-Practitioner Partnerships we have funded that explicitly focused on ELs. These projects have tackled a range of EL-related issues including science education and trajectories through middle and high school, and have taken place in states like Utah and Oregon, and districts like Saint Paul, MN and Cleveland, OH. As intended for RPP projects, these partners have leveraged their mutual interests to complete rigorous analyses and create products with immediate value for practitioners (read more about one example here).

Partnerships and collaborations are not limited to the RPP competition, however. Some EL researchers have found ways to collaborate closely with agency partners even in the context of a more “typical” research project. One example of this is work done by Peggy Estrada with the Los Angeles Unified School District (LAUSD). Dr. Estrada’s Goal 1 grant focused on longitudinal patterns in EL performance before and after reclassification, or the point at which a student is deemed to no longer need the services and supports associated with EL status.

In LAUSD, reclassification decisions were made based on three criteria, and Dr. Estrada found that many students who are not reclassified miss only one of the three. She also observed that there are only eight different profiles that can describe a student’s status on the three criteria. She reasoned, further, that if teachers knew a student’s profile, they could tailor their supports to help the student meet the criterion on which he or she fell short.

To share these findings with LAUSD, Dr. Estrada created a number of actionable data visualization tools. These proved key in what happened next: LAUSD staff members Kathy Hayes and Hilda Maldonado immediately saw the value in Dr. Estrada’s findings and visualizations, and worked with their colleagues to create an English Learner Dashboard that incorporated both. The Dashboard is an interactive data tool that provides summary information about student reclassification profiles and allows staff to design reports tailored to their needs. LAUSD staff can download the names of students in each profile and generate reports with student names and detailed assessment results for each reclassification criteria.

Creation of this Dashboard is another great example of the value created through collaborations between researchers and practitioners – particularly for EL research. LAUSD staff cited the value of working with an external partner who provided objectivity and helped them to think more critically and deeply about an issue they found important. Dr. Estrada found that working with LAUSD enhanced both the validity and the utility of her research. In the end, both parties win – as do, more importantly, the EL students themselves.

Written by Molly Faulkner-Bond, Program Officer, NCER and Karen Douglas, former Program Officer, NCER

Gender achievement gaps in education, particularly in the science, technology, engineering, and mathematics (STEM) domain continue to persist. On the 2015 NAEP, male students continue to significantly outperform female students in science in Grades 8 and 12, and on the 2017 NAEP, male students outperformed female students in mathematics at Grades 4 and 8. In addition, a recent study by Reardon and colleagues supported by IES found that the gender achievement gap favoring male students in mathematics was related to local socioeconomic conditions, with the gap being more prevalent in more socioeconomically advantaged school districts.

Although we know that the gender achievement gap is pervasive, particularly in STEM, what can we do to help close the gap? Previously, IES released a Practice Guide on Encouraging Girls in Math and Science that included evidence-based recommendations for how practitioners can better support and encourage girls to pursue math- and science-related fields. Adding to this research base, three new FY 2018 IES grants funded under the Education Research Grants program will explore potential causes and correlates of gender differences in achievement that can provide new insights and approaches to closing the gender achievement gap in STEM.  Here is a brief summary of these studies along with their potential contributions to research, practice, and policy.

Gender Stereotypes in STEM – Although many factors influence the gender gap in STEM, research points to gender difference in students' interest and motivation in STEM as a major contributor to later disparities in STEM majors and careers. Allison Master and colleagues will explore how and when gender stereotypes about academic fields emerge, the relationship between stereotypes and motivation in STEM fields, and whether teaching a growth mindset (i.e., the belief that intelligence is malleable) can change stereotypes and improve students' sense of belonging, self-efficacy, interest, and outcomes in STEM in grades 2 to 8. The results from this study will be used to inform the development of future interventions to reduce the impact of STEM-gender stereotypes.

The Relation of Gender-Integrated Classroom Climate to Students' Academic Outcomes - Because boys and girls are typically taught together in classrooms, there is the assumption that boys and girls are cooperative and integrated in their classroom activities, yet evidence suggests this may not be the case.  Some classroom climates facilitate gender integration, while other classroom climates may perpetuate gender segregation where students tend to only work with classmates of the same gender. Carol Lynn Martin and colleagues will examine how gender integration relates to 4th to 6th grade students' school-related engagement and academic perceptions and achievement. The results from this study will provide preliminary evidence of potentially promising practices for gender integration in classrooms that can help girls feel more comfortable working with boys and may encourage persistence in STEM.

Underrepresented Student Learning in Online Introductory STEM College Courses – Online instruction has the potential to make course content more accessible to a larger number of students, thereby strengthening the STEM pipeline. Michelle Perry and colleagues will explore the interaction among various characteristics of online instruction and postsecondary students' persistence in STEM courses. In particular, the researchers will explores how students traditionally underrepresented in STEM (e.g., women, first-generation students, minorities) benefit from or are impeded by online course features (e.g., course videos, discussion boards). The results from this study will provide a theory of postsecondary online STEM instruction that could strengthen persistence in STEM among women and others traditionally underrepresented in STEM. 

Written by Christina Chhin, Education Research Analyst, National Center for Education Research

Statistics paint a portrait of our Nation. They provide important information that can help track progress and show areas that need attention. Beginning with the first Census in 1790, federal statistics have been used to allocate representation in Congress. Labor statistics have been gathered since the middle of the 19th century. And since 1870, the federal government has collected statistics on the condition and progress of American education.

One of the early Commissioners, John Eaton, lamented in his 1875 report to Congress that, “When the work of collecting educational statistics was begun by the Office, it was found that there was no authentic list of the colleges in the United States, or of academies, or normal schools, or schools of science, law, or medicine, or of any other class of educational institutions.” In the beginning, data were collected on basic items such as public school enrollment and attendance, teachers and their salaries, high school graduates, and expenditures. Over the years, the level of detail gradually has increased to address the needs of policy makers and the public. For example, data collections were expanded after WWII to provide more information on the growth of postsecondary education resulting from the Servicemen’s Readjustment Act, also known as the GI Bill.

Patterns of enrollment change help to illustrate the growth in the nation’s education system. In 1900, relatively few students ever attended high school or college.  Of the 17.1 million students in 1900, only about 0.6 million, 4 percent of students, were enrolled in grades 9 through 12 and 0.2 million, 1 percent of students, were enrolled in postsecondary education.  During the first half of the 20th century, high school became a key part of the educational experience for most Americans. Between 1899-1900 and 1949-50, both population growth and an increase in the number of students attending high school and postsecondary education led to shifts in the distribution of students at different levels. Of the 31.2 million students in 1949-50, about 71 percent were enrolled in prekindergarten through grade 8, about 21 percent were enrolled in grades 9 through 12, and about 9 percent were enrolled in college. From 1949–50 to more recent years, enrollment in postsecondary education has become more common. Of the 75.7 million students enrolled in 2015, about 26 percent were enrolled in postsecondary education. About 52 percent of students were enrolled in prekindergarten through grade 8 in 2015, and about 22 percent were enrolled in grades 9 through 12.   

In 1962, the National Center for Education Statistics was authorized by legislation, which underscored the expanding role of education statistics within the federal system. This new role was highlighted by major advances in gathering policy-relevant and research-oriented information about our education system through the establishment of the National Assessment of Educational Progress (NAEP) in the late 1960s and the beginning of the National Longitudinal Study of 1972. Elementary and secondary administrative record systems were expanded by working collaboratively with state education agencies through the Common Core of Data beginning in the late 1970s.

The Integrated Postsecondary Education Data System (IPEDS) was developed from existing systems to better meet the needs of institutional, state, and federal decision makers. At the same time, the Center developed new sample surveys to efficiently meet research and policy needs. These new surveys included the National Postsecondary Student Aid Study (1986-87), the Schools and Staffing Survey (1987-88) and the National Household Education Survey (1991).

NCES longitudinal studies have continued to strongly support research and policy analyses at all levels from early childhood to postsecondary education.  One example was the groundbreaking Early Childhood Longitudinal Study, Birth Cohort (2001), which obtained nationally representative data on children from birth to kindergarten entry. NCES has continued a tradition of innovation by including digitally based assessments in the 2017 National Assessment of Educational Progress and by introducing interactive geographic mapping to our website. NCES strives to improve measures of the condition of education by collecting data that reflect the educational experiences of all students, while maintaining a faithful commitment to accuracy, transparency, and objectivity. Find out more about the history of NCES here or by visiting the NCES webpage at nces.ed.gov.

By Tom Snyder