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Overview

The goal of this COVID relief funded project is to support the research to accelerate pandemic recovery in Special Education. In Year 1 of , teachers are randomly assigned to receive intense coaching or light coaching on the use of data-based individualization (DBI) when teaching students with specific learning disabilities in mathematics. DBI integrates assessment and instructional design principles to create individualized, responsive intervention for students with persistent learning needs. Weekly student assessment data will be used to determine which coaching model is most effective for teacher implementation and student achievement. These coaching models are pulled from an existing evidence-based intervention framework with the special education teachers called Project STAIR: Supporting Teaching of Algebra with Individual Readiness.

In Year 2, teachers will be grouped based on responsiveness to their coaching in Year 1. All teachers will receive continued coaching in the form of Core PD; most teachers will additionally receive TailoredPD; non-responders will be randomly assigned further PD (peer mentoring or booster sessions). Weekly student assessment data will be used to evaluate the effectiveness of the teachers’ implementations of DBI when teaching students with certain learning needs in math. At the conclusion of Years 1 and 2, the sustainability of the various PD methods and the use of DBI will be examined and evaluated, and in an effort to support sustainability, DBI PD is provided to schools at the conclusion of each year.

Funder

U.S. Department of Education, Institute for Education Sciences, under the Research to Accelerate Pandemic Recovery in Special Education

Principal Investigators

(University of Missouri)

Dr. Leanne Ketterlin Geller (Southern Methodist University)

(University of Texas at Austin)

Purpose

In this project, DBI serves as the overarching approach for addressing individual students' needs when learning algebra while experiencing a learning disability in mathematics. The post-pandemic, societal need for this research is evidenced by local, state, and national testing measures in mathematics. STAIR 2.0 addresses Special Education Teachers’ needs by 1) providing DBI PD to increase data-based decision making, 2) increasing evidence-based intervention in math classrooms, and 3) utilizing assessment tools to make informed decisions. STAIR 2.0 addresses Special Education èßäÊÓƵapp’ needs by a) increasing pre-algebraic and algebraic knowledge through evidence-based intervention, b) fostering competency on high-stakes tests, and c) guaranteeing interactions with culturally relevant practices and math strategies. School-based educators will develop capacity to implement these practices through professional development and coaching. The intended outcome of this project is improved algebraic reasoning and overall mathematics achievement for middle school students with disabilities.

Methodology

A multi-faceted evaluation approach will be implemented to assess the impact on algebra-readiness and overall mathematics performance for middle school students with disabilities including quasi-experimental research designs, single-case designs, and social validity studies. Four types of measures will be used. Teachers will be administered survey instruments and participate in focus groups to determine the feasibility and social validity of the professional learning experiences. Classroom observations, using fidelity and instructional quality measures, will also be used to revise the program. Proximal measures of algebra-readiness and a distal measure(standardized mathematics achievement test) will be used to examine the outcomes for students with disabilities. Social validity instruments will also be utilized for students and administrators. Descriptive data from teacher surveys, classroom observations, and student mathematics performance will be used to iteratively revise the program, to determine feasibility, and to examine the potential impact on student mathematics achievement. Focus group data will be analyzed qualitatively and will be used to refine the program. Correlation and other strength of association methods will be used to test hypotheses related to implementation fidelity and quality of teacher-student instructional interactions.

Outcomes

We anticipate that STAIR 2.0 will result in improvements to teachers’ preparation and implementation of data-based individualization for middle school mathematics students. In turn, implementing data-based individualization will support student achievement and lead to measurable gains in students’ algebraic reasoning.

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References

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