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The Power of Logic Models

The Texas Education Agency (TEA) has developed initiatives aimed at reducing the number of low-performing public schools in Texas. As part of Regional Educational Laboratory (REL) Southwest’s School Improvement Research Partnership (SWSI) with TEA and Texas districts, researchers from REL Southwest planned a series of logic model training sessions that support TEA’s school improvement programs, such as the System of Great Schools (SGS) Network initiative.

To ensure that programs are successful and on track, program developers often use logic models to deepen their understanding of the relationships among program components (that is, resources, activities, outputs, and outcomes) and how these interact over time. A logic model is a graphical depiction of the logical relationship among the resources, activities, and intended outcomes of a program, with a series of if-then statements connecting the components. The value of using a logic model to undergird programs is that it helps individuals and groups implementing an initiative to articulate the common goals of the effort. Additionally, it helps to ensure that the strategies, resources, and supports provided to key stakeholders are aligned with the articulated goals and outcomes, providing a roadmap that creates clear connections across these program components. Finally, over the course of implementation, logic models can facilitate decisionmaking about how to adjust implementation and make changes to the program that can be tested to ensure they align with overall goals and outcomes identified in the logic model.

The logic model training is designed to provide TEA with a hands-on experience to develop logic models for the state’s school improvement strategy. Another overarching goal is to build TEA’s capacity to support local stakeholders with the development of logic models for their school improvement initiatives aligned with Texas’s strategy and local context.

The first training session, titled “School Improvement Research Partnership: Using Logic Modeling for Statewide School Improvement Efforts,” was held earlier this year. SWSI partners focused on developing a logic model for the SGS initiative. It was an in-person gathering aimed at teaching participants how to create logic models by addressing the following:

  • Increasing knowledge of general concepts, purposes, and uses of logic models
  • Increasing knowledge and understanding of the components that make up a logic model
  • Building capacity in understanding links between components of school improvement initiatives
  • Providing hands-on opportunities to develop logic models for local school improvement initiatives

The timing of the logic model workshop was helpful because it allowed the district-focused SGS leaders at TEA to organize the developed SGS framework into a logic model that enables TEA to plan and guide implementation, lay the foundation for the development of an implementation rubric, and serve as a resource to continuously improve the strategy. TEA also plans to use the logic model to communicate with districts and other stakeholders about the sequence of the program and intended outcomes.

REL Southwest will continue to provide TEA with training and technical support and will engage local stakeholders as the logic models are finalized. These sessions will focus on refining the logic models and ensure that TEA staff will be equipped with the ability to develop logic models on their own for current and future initiatives and programs.

This blog post was co-published with REL Southwest.

2019-08-07

IES Published Our REL Southwest Study on Trends in Teacher Mobility

The U.S. Department of Education’s Institute of Education Sciences published a report of a study we conducted for REL Southwest! We are thankful for the support and engagement we received from the Educator Effectiveness Research Alliance throughout the study.

The study was published in December 2017 and provides updated information regarding teacher mobility for Texas public schools during the 201112 through 201516 school years. Teacher mobility is defined as teachers changing schools or leaving the public school system.

In the report, descriptive information on mobility rates is presented at the regional and state levels for each school year. Mobility rates are disaggregated further into destination proportions to describe the proportion of teacher mobility due to within-district movement, between-district movement, and leaving Texas public schools. This study leverages data collected by the Texas Education Agency during the pilot of the Texas Teacher Evaluation and Support System (T-TESS) in 57 school districts in 201415. Analyses examine how components of the T-TESS observation rubric are related to school-level teacher mobility rates.

During the 2011-12 school year, 18.7% of Texas teachers moved schools within a district, moved between districts, or left the Texas Public School system. By 2015-16, this mobility rate had increased to 22%. Moving between districts was the primary driver of the increase in mobility rates. Results indicate significant links between mobility and teacher, student, and school demographic characteristics. Teachers with special education certifications left Texas public schools at nearly twice the rate of teachers with other teaching certifications. School-level mobility rates showed significant positive correlations with the proportion of special education, economically disadvantaged, low-performing, and minority students. School-level mobility rates were negatively correlated with the proportion of English learner students. Schools with higher overall observation ratings on the T-TESS rubric tended to have lower mobility rates.

Findings from this study will provide state and district policymakers in Texas with updated information about trends and correlates of mobility in the teaching workforce, and offer a systematic baseline for monitoring and planning for future changes. Informed by these findings, policymakers can formulate a more strategic and targeted approach for recruiting and retaining teachers. For instance, instead of using generic approaches to enhance the overall supply of teachers or improve recruitment, more targeted efforts to attract and retain teachers in specific subject areas (for example, special education), in certain stages of their career (for example, novice teachers), and in certain geographic areas are likely to be more productive. Moreover, this analysis may enrich the existing knowledge base about schools’ teacher retention and mobility in relation to the quality of their teaching force, or may inform policy discussions about the importance of a stable teaching force for teaching effectiveness.

2018-02-01
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