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IES Grant

Title: Reading and Playing With Math: Promoting Preschoolers' Math Language Through Picture Books and Play Activities
Center: NCER Year: 2020
Principal Investigator: Purpura, David Awardee: Purdue University
Program: Early Learning Programs and Policies      [Program Details]
Award Period: 4 years (08/01/2020 - 07/31/2024) Award Amount: $1,399,800
Type: Development and Innovation Award Number: R305A200389

Co-Principal Investigators: Logan, Jessica; Schmitt, Sara

Purpose: The purpose of this study is to develop, refine, and evaluate a new math language intervention, Reading and Playing with Math (RP-Math). Math language is the specific content language (e.g., words and concepts such as more, fewer, a lot, many) that has distinct meanings when used in math contexts. It is one of the strongest predictors of growth in numeracy skills, and it underlies acquisition of numeracy skills. Yet there are currently no empirically supported tools for providing instruction in this domain. RP-Math will leverage the evidentiary basis of language instruction using storybooks and mathematics instruction using learning trajectories, incorporating recent intervention work by the research team on math language.

Project Activities: Researchers will iteratively develop picture books, guided play activities, session guides, and professional development (PD) modules in collaboration with teachers. They will then test and refine the feasibility of implementation and usability of RP-Math with teachers. Finally, they will conduct a small-scale cluster randomized trial to examine the promise of the fully developed RP-Math, and gather information about the cost to deliver the intervention.

Products: The primary products of this project will be a fully developed math language intervention, RP-Math, and evidence of the promise of RP-Math at improving children's math language and numeracy skills. Researchers will carry out a diverse array of dissemination activities, including presenting at conferences and publishing in peer-reviewed journals, to connect the research to practice.

Structured Abstract

Setting: The research activities will take place in Indiana.

Sample: In Phase 1, two teachers will be recruited to assist with book, session guide, guided play activities, and PD module development. In Phase 2, six teachers will be recruited to implement and provide feedback on the intervention materials. In Phase 3, data will be collected in 20 preschool classrooms serving children from families of low socio-economic status in urban, suburban, and rural settings. Approximately 200 preschool children (3- to 5-years old) and their teachers will participate.

Intervention: RP-Math will consist of 6 storybooks rich in math language, 30 session guides with linked guided play activities, and 4 PD modules developed and refined in collaboration with teachers. Sessions will consist of reading a picture book with embedded dialogic reading prompts and then engaging the students in a linked guided play activity.

Research Design and Methods: Researchers will develop the intervention in collaboration with teachers following an iterative development process. Six teachers will then implement the RP-Math and provide feedback as to the feasibility and usability of the intervention. Once the iterative development process is complete, researchers will use a cluster randomized trial to carry out the pilot test of the fully developed intervention. Researchers will randomly assign half of the classrooms to the intervention condition and half of the classrooms to the active control condition. RP-Math will be implemented by teachers twice per week (30 min sessions) for 15 weeks during the pilot test of the intervention.

Control Condition: The active control condition will use a parallel version of the intervention with different books that do not include math language concepts. The structure will align with RP- Math (2-times per week for 15 weeks) of storybooks and guided play activities and will include professional development.

Key Measures: Children will be pre-tested, post-tested, and delayed post-tested on measures of math language, numeracy, and vocabulary. Classroom observations of children and teachers use of math language and questioning will be conducted during activities.

Data Analytic Strategy: As classroom/teacher is the unit of assignment, a two-level hierarchical linear model (HLM) will be fitted to the data for each outcome of interest. The main research question will be assessed using a residualized change HLM. Post-test (either immediate or delayed) will be predicted from the pre-test assessment of the same construct and a dummy variable representing intervention condition.

Cost Analysis: Researchers will assess the cost to deliver the intervention during the pilot study.