Project Activities
The Center brings together experts from four research institutions and three SEAs to study high-priority issues in the area of advanced and accelerated education. Using a variety of data sources such as state longitudinal datasets and direct classroom observations, the team will investigate issues around automatic enrollment, differentiation, teacher qualifications, and differentiated instruction; examine the data landscape for datasets that can help inform policy and practice; and create toolkits on related practices and policies to help guide state and local education agencies in their advanced education practices. The Center will also carry out national leadership activities designed to promote the Center’s national visibility, engage with the fields of research and practice, and allow the Center to function as a trusted source of scientific research in in the field; conduct supplemental research studies as determined with the Department of Education; and provide various research training activities to build the field’s capacity, including the capacity of investigators to conduct cutting-edge research and for policymakers to use data to inform practice and policy in advanced education.
Focused program of research
The Center team is conducting research and development projects in a number of areas identified as high priority by the participating SEAs. The team will conduct these activities in three phases over the 5 years of the project period. The projects will focus on the following:
- the effects of automatic enrollment on student outcomes
- the impact of specific teacher qualifications and preparation on students’ advanced learning
- the prevalence of high-quality differentiation practices in mixed-ability classroom instruction
- the impact of high-quality differentiation on students’ learning
- the identification of large-scale datasets that can inform policy and practice in advanced education
- the creation of toolkits on identification strategies, use of large-scale datasets to improve policy and practice in advanced education, and instructional and curricular differentiation practices
National leadership and outreach activities
The NRCAE team will provide national leadership for research-supported practice and policymaking in gifted and advanced education by presenting research via conference presentations, webinars, podcasts, policy briefs and research summaries, and publications in research, policy-focused, and practitioner journals and magazines. The Center team is also collaborating with national scientific and professional organizations and stakeholder groups to disseminate evidence-based resources.
The Center will also lead a range of training opportunities focused conducting high-quality, replicable research using open science principles, including workshops for SEA staff, faculty, and graduate students. The opportunities include asynchronous training modules for the center toolkits, a quarterly methods webinar series focused on topics in advanced education research, an annual hybrid symposium focusing on cutting-edge research in advanced education, training sessions for graduate students and postdocs held in conjunction with the annual meetings of professional associations, and webinars followed by individual coaching/mentoring of SEA staff on research design/quantitative analyses.
Structured Abstract
Setting
The three states collaborating on the Center’s activities have specific expertise in the focus areas for the Center:
- Nebraska has undertaken statewide curriculum improvement projects over the past several years, with an emphasis on supporting teachers who work in rural school settings to develop differentiation strategies.
- New Jersey passed a new gifted education law in 2020 and has focused on improving identification practices in its school districts.
- North Carolina passed the first state-level automatic enrollment policy in mathematics in 2018. Collectively, these states educate approximately 3.5 million students in over 7,500 public and private schools, with nearly 240,000 public school teachers.
The states represent a range of state and local organizational structures for education, and educators and students represent a range of rural, small town, suburban, and urban locales. All three states also have a range of licensing and certification pathways for educators.
Sample
- The phase I automatic enrollment study will include all students in grades 6-12 for which North Carolina state data systems have student data for the years 2020-2021 through 2024-2025, intended to be representative of all North Carolina students impacted by the state’s relevant policies.
- The phase II teacher qualifications study will include all North Carolina students in grades 4-8 for which North Carolina state data systems have linked data to their math and reading teachers for the 2007-2008 through 2025-2026 school years, intended to be representative of all North Carolina teachers and students in those grades over that time span.
- The first and second differentiation studies in phase III will include three teachers in each of 12-15 schools in Nebraska, intended to be representative of elementary school teachers in that state. If time and resources allow, a replication of the differentiation studies will be conducted in either North Carolina or New Jersey.
Research design and methods
- For the phase I automatic enrollment study, the research team will use North Carolina longitudinal data systems to determine whether the onset of the state’s 2018 automatic enrollment law led to changes in subsequent student course-taking and achievement in mathematics.
- For the phase II teacher qualifications study, the team will again use North Carolina longitudinal data systems to obtain data on student performance on state assessments and teacher qualifications.
- During the phase III differentiation studies, the research team will conduct observations of instructional differentiation practices of elementary school teachers, using a random selection process stratified by geography within the state, and link classroom practices to student assessment data.
Key measures
- For the automatic enrollment study, the research team will use North Carolina’s state longitudinal data systems to obtain data on student course enrollment and performance on the state assessment.
- The team will also use these data systems for the teacher qualifications study to obtain data on student performance on state assessments and teacher qualifications. Teacher qualifications will be measured through content-area knowledge with subject tests from the Praxis teacher licensure exam (e.g., Mathematics or Teaching Reading), whether a teacher has an Academically Gifted license, and a proxy measure for teachers’ underlying skills using the quality of the university they attended (as measured by the published median earnings of graduates).
- For the differentiation studies, the research team will use variations on two instruments designed for observation of teacher instructional differentiation practice as well as student data from the state assessment in an effort to link classroom practice with student advanced achievement.
Data analytic strategy
- For the automatic enrollment study, the research team will use a regression discontinuity design and difference-in-differences design to allow for causal conclusions about the impact of North Carolina’s policies.
- For the teacher qualification study, the team will use regression to create a descriptive model of the degree to which changes in student advanced achievement on the state assessment is related to teacher qualifications.
- In the differentiation studies, the team will describe the state of differentiation in classrooms (both quantity and quality) and use multilevel analyses to account for the nested nature of the data (repeated measures of students, nested within students, nested within classrooms, nested within schools) to examine the effects of differentiation on student achievement and growth and whether these effects vary by student academic need (e.g., whether the students is above or below level).
People and institutions involved
IES program contact(s)
Project contributors
Partner institutions
American Institutes for Research (AIR)
Nebraska Department of Education
New Jersey Department of Education
North Carolina Department of Public Instruction
Texas A&M University
University of Calgary
Products and publications
This project will produce evidence of the impact of automatic enrollment on students’ participation in advanced coursework and the effect of teacher qualifications on student achievement. Differentiation studies will provide estimates of the degree to which differentiation is occurring for advanced students, the effects of that differentiation on advanced students’ achievement, and best practices for differentiating up for advanced students. The project will also lead to resources for the field of advanced education, including a compilation of available relevant databases, toolkits for state and local agencies for policymaking and practice guidance, and training materials for researchers and for policymakers to learn to use data-based decision making in advanced education.
Publications:
ERIC Citations: Find available citations in ERIC for this award here.
Additional project information
In fulfillment of the requirement in the "Jacob K. Javits Gifted and Talented Students Education Program" in the Every Student Succeeds Act (ESSA) (SEC. 4644. ø20 U.S.C. 7294 [d]) for a National Research Center for the Education of Gifted and Talented Children and Youth.
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