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IES Grant

Title: Building and Sustaining the Capacity of Local Math Coaches to Support College- and Career-Ready Mathematics Instruction
Center: NCER Year: 2019
Principal Investigator: Walters, Kirk Awardee: American Institutes for Research (AIR)
Program: Effective Instruction      [Program Details]
Award Period: 4 years (07/01/2019-06/30/2023) Award Amount: $1,399,170
Type: Development and Innovation Award Number: R305A190195
Description:

Co-Principal Investigators: Smith, Toni M.; Hill, Heather C.

Purpose: In this project, the project team will develop, refine, and evaluate a coaching intervention for elementary math teachers to be implemented by local district coaches. A math-specific observational coding system, the Mathematical Quality of Instruction (MQI), guides 1:1 and group coaching activities that emphasize teacher video analysis and practice with feedback. The pilot study will assess the implementation and promise of the fully developed intervention on teacher practice and student achievement.

Project Activities: In the first 2 years of the project, researchers will work closely with coaches and teachers to fully develop MQI Coaching+, using rapid-cycle methods to iteratively develop and refine the program. In Year 3, researchers will carry out a randomized controlled study of the implementation and impact of MQI Coaching+, as well as a detailed cost analysis.

Products: The research team will produce a refined MQI Coaching+ model, with refined guidelines for the fidelity of implementation. Materials will include a professional learning community (PLC) meeting planning guide, a PLC collaborative log template, sequenced stock video clips for the PLCs, a video library of coaching conversations, a protocol for guiding the lesson rehearsals, and a post-PLC teacher survey. The team will also produce findings about the usability, feasibility, implementation, and impact of MQI Coaching+, as well as estimates of implementation costs.

Structured Abstract

Setting: The research will take place in a large Maryland suburban district in the Baltimore–Washington, D.C. metropolitan area.

Sample: The development phases will involve 2 district coaches, 2 elementary schools, 6 third-grade teachers, 12 fourth- and fifth-grade teachers, and 450 third- to fifth-grade students. The pilot study will involve 10 district coaches, 40 elementary schools, 240 fourth- and fifth-grade teachers, and 6,000 fourth- and fifth-grade students. The student population is racially and economically diverse, with 29% of elementary schools classified as Title I.

Intervention: The intervention being developed will be called MQI Coaching+, a math coaching program for local district coaches that combines 1:1 video-based coaching cycles and school-based PLCs. The PLCs provide teachers opportunities to practice instruction with feedback and reinforce learning in the 1:1 cycles.

Research Design and Methods: The iterative development of MQI Coaching+ will use rapid-cycle, improvement science methods, while the pilot study is a school-level, randomized controlled trial.

Control Condition: For the pilot study, 10 district math coaches and their fourth- and fifth-grade teachers and students will participate in standard coaching activities, which do not involve the MQI, video analysis, or the PLCs focused on practice with feedback.

Key Measures: The key teacher outcomes are perceptions of reform-oriented teaching (survey), quality of instruction (MQI), and student achievement (Partnership for Assessment of Readiness for College and Careers math assessment).

Data Analytic Strategy: Researchers will use descriptive methods to iteratively develop the program and assess feasibility and implementation fidelity. The pilot study will follow an intent-to-treat approach, using a multilevel model with students nested within teachers with schools assigned to an MQI Coaching+ district coach.

Cost Analysis: Researchers will use a Resource Cost Model approach to identify costs of each intervention component. Researchers will also use the CostOut tool to help organize these costs and make any adjustments related to inflation or the use of materials, which are built into the tool. Analyses will (a) distinguish start-up costs, such as initial training of local coaches and video equipment, from ongoing costs, such as time for local coaches and teachers and ongoing operational costs of replacing cameras and paying for the video platform; (b) summarize costs by category, including external services, personnel, equipment, and incentives; and (c) convert total costs into per-school, per-teacher, and per-student costs.


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