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Institute of Education Sciences


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IES Grant

Title: Recognition and Response: Addressing Early Learning Difficulties in Math through an RTI Model for Pre-K
Center: NCSER Year: 2012
Principal Investigator: Buysse, Virginia Grantee: University of North Carolina, Chapel Hill
Program: Early Intervention and Early Learning in Special Education      [Program Details]
Award Period: 03/01/2012–02/28/2015 Award Amount: $1,500,000
Goal: Development Award Number: R324A120059
Description:

Co-Principal Investigator: Ellen Peisner-Feinberg

Historically, little attention has been paid to teaching math prior to kindergarten entry. The National Research Council's Committee on Early Childhood Mathematics concluded that while virtually all young children have the capability to learn and acquire core competencies in math, most do not realize their full potential. The Committee attributed this to children's limited opportunities to learn math in either early childhood education programs or through every day experiences at home. This lack of instructional opportunities could be particularly problematic for children most at risk for math failure. These children start school behind their peers and may be unable to catch up without extensive, high-quality early math instruction.

The purpose of this project is to adapt an instructional system, called Recognition and Response, for preschool mathematics instruction. The model is intended to improve the quality of math practices for all children and provide additional supports for some children to ensure that every child is ready for kindergarten.

Project Activities: Approximately 50 preschool classrooms in North Carolina will participate in this study. All classroom children will participate, but the researchers will focus on children most at risk for math failure. The Recognition and Response model has shown promise for improving language and literacy outcomes for preschool children. The basic framework of the model—including screening and frequent monitoring of children's progress, use of quality classroom instruction and intensive interventions, and problem solving across collaborative partners—will be modified with preschool math content. Development and revision of the intervention and assessment and professional development materials will occur in years 1 and 2. A pilot study investigating the promise of the system for improving math outcomes and for changing instructional practices will occur in year 3. Using a quasi-experimental design, classrooms will be matched on classroom and teacher variables. Students in the comparison condition will receive math instruction as usual. A series of data analytic strategies, including multi-level modeling, will be used to determine whether the Recognition and Response-Math system shows promise for improving mathematics outcomes. The researchers will also investigate whether differences in growth exist for intervention and comparison children most at risk for math failure or need special education services.

Products: The products of this project will be a fully developed preschool system, called Recognition and Response-Math, to teach math to preschool children. Published reports describing the intervention's promise for improving outcomes will also be produced.

Structured Abstract

Setting: The research will take place in preschools in North Carolina.

Sample: Approximately 50 preschool classrooms will participate in this study. All classroom children will participate, but the researchers will focus on children most at risk for math failure.

Intervention: Recognition and Response is a particular response to intervention model designed for preschool children. There are three key components of the model: (1) recognition, which involves gathering formative assessment information by screening all of the children in the classroom and periodically monitoring those who need more targeted intervention; (2) response, which involves providing an effective core curriculum and targeted interventions linked to formative assessment results, and (3) problem solving based on collaboration among teachers, parents, and specialists. This research project will adapt this model, which has been developed for early literacy skills, and extend it to teaching mathematics. The team will use the Big Math for Little Kids curriculum as the core curriculum and basis for intensified instruction. The Big Math for Little Kids curriculum is comprised of six sequenced units with five lessons per unit. Each unit is centered on a different mathematical concept: number; shape; measurement; construction and partition numbers; patterns and logic; and navigation and special concepts.

Research Design and Methods: The activities will consist of four phases. The team will design and adapt the intervention and assessment components and professional development materials, iteratively test and revise the components, investigate the teacher proficiency for implementation, and conduct a pilot study to examine the promise of the intervention for improving math outcomes. Development and revision of the materials will occur in years 1 and 2. The separate components will be tested and revised based on data assessing the acceptability and feasibility of the component and teachers' implementation fidelity. A pilot study investigating the promise of the system for improving math outcomes and for changing instructional practices will occur in year 3. A quasi-experimental design will be used with classrooms matched on classroom and teacher variables.

Control Condition: Students in the comparison condition will receive math instruction as usual.

Key Measures: A variety of student assessment and observational data will be collected. The mCLASS:CIRCLE math assessment will be used as a universal screening and progress monitoring tool. Additional measures of math will be administered to measure students' overall math growth and individual skills with problem solving, number comparison, numeral literacy, calculation, shape and pattern. Fidelity of implementation data will also be collected through teacher observations and the team will conduct focus groups and interviews with participating teachers.

Data Analytic Strategy: Multi-level modeling will be used to determine whether the Recognition and Response-Math system shows promise for improving math outcomes. The researchers will also investigate whether differences in growth exist for intervention and comparison children most at risk for math failure or need special education services.


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