Professional Development

Aligning the Science Teacher Education Pathway: A Networked Improvement Community

This project will study the activities of a Networked Improvement Community (NIC) as a vehicle to bridge gaps across four identified steps along the science teacher training and development pathways within local contexts of 8 participating universities. The overarching goal of the project is to strengthen the capacity of universities and school districts to reliably produce teachers of science who are knowledgeable about and can effectively enact the Next Generation Science Standards (NGSS), although prepared in varied organizational contexts.

Award Number: 
1908900
Funding Period: 
Mon, 07/01/2019 to Fri, 06/30/2023
Full Description: 

California State University will study the activities of a Networked Improvement Community (NIC) as a vehicle to bridge gaps across four identified steps along the science teacher training and development pathways within local contexts of 8 participating universities (NIC sites). Networked Improvement Community (NIC) will co-create a shared vision and co-defined research agenda between university researchers, science educators and school district practitioners working together to reform teacher education across a variety of local contexts. By studying outcomes of shared supports and teacher tools for use in multiple steps along the science teacher education pathway, researchers will map variation existing in the system and align efforts across the science teacher education pathway. This process will integrate an iterative nature of educational change in local contexts impacting enactment of the NGSS in both university teacher preparation programs and in school district professional training activities and classrooms.

The overarching goal of the project is to strengthen the capacity of universities and school districts to reliably produce teachers of science who are knowledgeable about and can effectively enact the Next Generation Science Standards (NGSS), although prepared in varied organizational contexts. The project will accomplish this goal 1) leveraging the use of an established Networked Improvement Community, composed of science education faculty from eight university campuses and by 2) improving and studying coherence in the steps along the science teacher education pathway within and across these universities and school districts. The project will use a mixed methods approach to data collection and analysis. Consistent with Improvement Science Theory, research questions will be co-defined by all stakeholders.

Building a Teacher Knowledge Base for the Implementation of High-Quality Instructional Resources through the Collaborative Investigation of Video Cases (Collaborative Research: DiNapoli)

This project will address the pressing national need to generate shared, practice-based knowledge about how to implement freely available, high-quality instructional resources (mathematics formative assessment lessons) that have been shown to produce significant gains in student learning outcomes. It will expand a professional development model (Analyzing Instruction in Mathematics using the Teaching for Robust Understanding Framework (AIM-TRU)) that supports teacher learning about effective lesson implementation.

Lead Organization(s): 
Award Number: 
1908319
Funding Period: 
Mon, 07/01/2019 to Fri, 06/30/2023
Full Description: 

This project will address the pressing national need to generate shared, practice-based knowledge about how to implement freely available, high-quality instructional resources (mathematics formative assessment lessons) that have been shown to produce significant gains in student learning outcomes. It will expand a professional development model (Analyzing Instruction in Mathematics using the Teaching for Robust Understanding Framework (AIM-TRU)) that supports teacher learning about effective lesson implementation. The backbone of AIM-TRU is a growing, open repository of video cases available to teachers and teacher educators across the U.S. who use or are interested in using the lessons. The repository will include tools such as a facilitator's guide to support teachers and teacher educators to engage in the model and collaboratively investigate the video cases. Consequently, the work will have the potential to engage teachers and teacher educators in improving mathematics education at scale. Because the video cases will capture implementation and ideas for improving instruction in schools serving populations who are underrepresented in mathematics, AIM-TRU will serve to improve mathematics education equitably.

Research questions focus on what teachers learn about high-quality mathematics instruction and instructional materials within a community of practice, and how that learning influences their teaching. In AIM-TRU, teachers engage in the collaborative investigation of video cases utilizing a shared repertoire that includes questioning protocols adapted from the Teaching for Robust Understanding (TRU) framework. This framework articulates five dimensions of classroom instruction that are necessary and sufficient to support students in becoming powerful mathematical thinkers. This affords teachers opportunities to use the TRU dimensions as lenses to diagnose common problems of practice that arise in implementation, and propose innovations and theories for improving instruction that can be tested in real classrooms and documented in new video cases. Analytic tools will be used from frame analysis to produce empirical evidence of what teachers are learning about instruction and instructional materials along the five dimensions of TRU. These data will be mapped to a random sample of video recordings of participating teachers' instruction, scored using the TRU Math Rubric, in order to link learning outcomes from the professional development to changes in instruction. Addressing these research questions will provide a deeper understanding and empirical evidence of learning within teacher collectives, the pressing national need to develop mechanisms to produce collective professional knowledge for teaching, and further efforts to understand the types of knowledge required for effective teaching.

The Analyzing Instruction in Math using the Teaching for Robust Understanding Framework (AIM-TRU) learning cycle is the result of a research-practice partnership centered on using the analysis of videocases grounded in high-quality instructional materials for use as a resource for in-service and pre-service professional learning. For videos, materials, slidedecks and a facilitation guide, please visit our website (note: a free user name is necessary to access the materials).

Building a Teacher Knowledge Base for the Implementation of High-Quality Instructional Resources through the Collaborative Investigation of Video Cases (Collaborative Research: Jabon)

This project will address the pressing national need to generate shared, practice-based knowledge about how to implement freely available, high-quality instructional resources (mathematics formative assessment lessons) that have been shown to produce significant gains in student learning outcomes. It will expand a professional development model (Analyzing Instruction in Mathematics using the Teaching for Robust Understanding Framework (AIM-TRU)) that supports teacher learning about effective lesson implementation.

Lead Organization(s): 
Award Number: 
1908311
Funding Period: 
Mon, 07/01/2019 to Fri, 06/30/2023
Full Description: 

This project will address the pressing national need to generate shared, practice-based knowledge about how to implement freely available, high-quality instructional resources (mathematics formative assessment lessons) that have been shown to produce significant gains in student learning outcomes. It will expand a professional development model (Analyzing Instruction in Mathematics using the Teaching for Robust Understanding Framework (AIM-TRU)) that supports teacher learning about effective lesson implementation. The backbone of AIM-TRU is a growing, open repository of video cases available to teachers and teacher educators across the U.S. who use or are interested in using the lessons. The repository will include tools such as a facilitator's guide to support teachers and teacher educators to engage in the model and collaboratively investigate the video cases. Consequently, the work will have the potential to engage teachers and teacher educators in improving mathematics education at scale. Because the video cases will capture implementation and ideas for improving instruction in schools serving populations who are underrepresented in mathematics, AIM-TRU will serve to improve mathematics education equitably.

Research questions focus on what teachers learn about high-quality mathematics instruction and instructional materials within a community of practice, and how that learning influences their teaching. In AIM-TRU, teachers engage in the collaborative investigation of video cases utilizing a shared repertoire that includes questioning protocols adapted from the Teaching for Robust Understanding (TRU) framework. This framework articulates five dimensions of classroom instruction that are necessary and sufficient to support students in becoming powerful mathematical thinkers. This affords teachers opportunities to use the TRU dimensions as lenses to diagnose common problems of practice that arise in implementation, and propose innovations and theories for improving instruction that can be tested in real classrooms and documented in new video cases. Analytic tools will be used from frame analysis to produce empirical evidence of what teachers are learning about instruction and instructional materials along the five dimensions of TRU. These data will be mapped to a random sample of video recordings of participating teachers' instruction, scored using the TRU Math Rubric, in order to link learning outcomes from the professional development to changes in instruction. Addressing these research questions will provide a deeper understanding and empirical evidence of learning within teacher collectives, the pressing national need to develop mechanisms to produce collective professional knowledge for teaching, and further efforts to understand the types of knowledge required for effective teaching.

The Analyzing Instruction in Math using the Teaching for Robust Understanding Framework (AIM-TRU) learning cycle is the result of a research-practice partnership centered on using the analysis of videocases grounded in high-quality instructional materials for use as a resource for in-service and pre-service professional learning. For videos, materials, slidedecks and a facilitation guide, please visit our website (note: a free user name is necessary to access the materials).

Building a Teacher Knowledge Base for the Implementation of High-Quality Instructional Resources through the Collaborative Investigation of Video Cases (Collaborative Research: Wilson)

This project will address the pressing national need to generate shared, practice-based knowledge about how to implement freely available, high-quality instructional resources (mathematics formative assessment lessons) that have been shown to produce significant gains in student learning outcomes. It will expand a professional development model (Analyzing Instruction in Mathematics using the Teaching for Robust Understanding Framework (AIM-TRU)) that supports teacher learning about effective lesson implementation.

Lead Organization(s): 
Award Number: 
1908185
Funding Period: 
Mon, 07/01/2019 to Fri, 06/30/2023
Full Description: 

This project will address the pressing national need to generate shared, practice-based knowledge about how to implement freely available, high-quality instructional resources (mathematics formative assessment lessons) that have been shown to produce significant gains in student learning outcomes. It will expand a professional development model (Analyzing Instruction in Mathematics using the Teaching for Robust Understanding Framework (AIM-TRU)) that supports teacher learning about effective lesson implementation. The backbone of AIM-TRU is a growing, open repository of video cases available to teachers and teacher educators across the U.S. who use or are interested in using the lessons. The repository will include tools such as a facilitator's guide to support teachers and teacher educators to engage in the model and collaboratively investigate the video cases. Consequently, the work will have the potential to engage teachers and teacher educators in improving mathematics education at scale. Because the video cases will capture implementation and ideas for improving instruction in schools serving populations who are underrepresented in mathematics, AIM-TRU will serve to improve mathematics education equitably.

Research questions focus on what teachers learn about high-quality mathematics instruction and instructional materials within a community of practice, and how that learning influences their teaching. In AIM-TRU, teachers engage in the collaborative investigation of video cases utilizing a shared repertoire that includes questioning protocols adapted from the Teaching for Robust Understanding (TRU) framework. This framework articulates five dimensions of classroom instruction that are necessary and sufficient to support students in becoming powerful mathematical thinkers. This affords teachers opportunities to use the TRU dimensions as lenses to diagnose common problems of practice that arise in implementation, and propose innovations and theories for improving instruction that can be tested in real classrooms and documented in new video cases. Analytic tools will be used from frame analysis to produce empirical evidence of what teachers are learning about instruction and instructional materials along the five dimensions of TRU. These data will be mapped to a random sample of video recordings of participating teachers' instruction, scored using the TRU Math Rubric, in order to link learning outcomes from the professional development to changes in instruction. Addressing these research questions will provide a deeper understanding and empirical evidence of learning within teacher collectives, the pressing national need to develop mechanisms to produce collective professional knowledge for teaching, and further efforts to understand the types of knowledge required for effective teaching.

The Analyzing Instruction in Math using the Teaching for Robust Understanding Framework (AIM-TRU) learning cycle is the result of a research-practice partnership centered on using the analysis of videocases grounded in high-quality instructional materials for use as a resource for in-service and pre-service professional learning. For videos, materials, slidedecks and a facilitation guide, please visit our website (note: a free user name is necessary to access the materials).

Getting Unstuck: Designing and Evaluating Teacher Resources to Support Conceptual and Creative Fluency with Programming

The project will create opportunities for teachers to develop programming content knowledge and new understandings of the creative possibilities in computer science education, thereby increasing opportunities for students to develop conceptual and creative fluency with programming.

Lead Organization(s): 
Award Number: 
1908110
Funding Period: 
Mon, 07/01/2019 to Wed, 06/30/2021
Full Description: 

The project will create opportunities for teachers to develop programming content knowledge and new understandings of the creative possibilities in computer science education, thereby increasing opportunities for students to develop conceptual and creative fluency with programming. K-12 introductory programming experiences are often highly scaffolded, and it can be challenging for students to transition from constrained exercises to open-ended programming activities encountered later in-and out of-school. Teachers can provide critical support to help students solve problems and develop the cognitive, social, and emotional capacities required for conceptually and creatively complex programming challenges. Teachers - particularly elementary and middle school teachers, especially in rural and Title I schools - often lack the programming content knowledge, skills, and practices needed to support deeper and more meaningful programming experiences for students. Professional development opportunities can cultivate teacher expertise, especially when supported by curricular materials that bridge teachers' professional learning and students' classroom learning. This research responds to these needs, addressing key national priorities for increasing access to high-quality K-12 computer science education for all students through teacher professional development.

The project will involve the design and evaluation of (1) an online learning experience for teachers to develop conceptual and creative fluency through short, daily programming prompts (featuring the Scratch programming environment), and (2) educative curricular materials for the classroom (based on the online experience). The online experience and curricular materials will be developed in collaboration with three 4th through 6th-grade rural or Title I teachers. The project will evaluate teacher learning in the online experience using mixed-methods analyses of pre/post-survey data of teachers' perceived expertise and quantitative analyses of teachers' programs and evolving conceptual knowledge. Three additional 4th through 6th-grade teachers will pilot the curricular materials in their classrooms. The six pilot teachers will maintain field journals about their experiences and will participate in interviews, evaluating use of the resources in practice. An ethnography of one teacher's classroom will be developed to further contribute to understandings of the classroom-level resources in action, including students' experiences and learning. Student learning will be evaluated through student interviews and analyses of student projects. Project outcomes will inform how computer science conceptual knowledge and creative fluency can be developed both for teachers and their students' knowledge and fluency that will be critical for students' future success in work and life.

Building Students' Data Literacy through the Co-design of Curriculum by Mathematics and Art Teachers (Collaborative Research: Matuk)

This project aims to enact and study the co-design of classroom activities by mathematics and visual arts teachers to promote middle school students' data literacy.

Award Number: 
1908557
Funding Period: 
Mon, 07/01/2019 to Wed, 06/30/2021
Full Description: 

The aim of this project is to enact and study a process in which middle school teachers of mathematics and visual arts co-design and teach activities that combine math and art to teach data science. Many existing efforts to promote data literacy are grounded in mathematical concepts of central tendency and variation, and typically are narrowly focused in single subject domains. Taking an art-based perspective on data science has the potential to promote student relevance, accessibility, engagement, reasoning, and meaning-making with data science. Moreover, visualization technology has advanced to a degree that the relation between the information in data and visual aesthetic can be leveraged easily. To explore the opportunity this offers, research on this project will examine how to equip teachers to develop such interdisciplinary pedagogical approaches to cultivate their students' data literacy. This exploratory project will provide support for 12 teachers during summer workshops and during the school year as these teachers implement their co-designed units in their classrooms. The work addresses the following questions: (1) How do we support effective co-design of data literacy units among art teachers, mathematics teachers, and researchers? (2) How are teachers able to use the unit materials in their classrooms to engage students in data literacy? And (3) How does an art-based approach support students' data literacy? Answers to these questions will build an understanding of how to support interdisciplinary curriculum design collaborations among researchers and teachers. They will also show how art-integrated, maker-oriented activities can support middle school learners' data literacy development; and how to design technologies that are accessible and powerful to teachers and learners in these interdisciplinary environments.

Through summer workshops and year-round design collaborations, the project will iteratively design, test and refine four units for middle school classrooms, including activities, tools, and assessments, to promote students' data literacy. Data will be collected from co-design sessions as well as classroom-enactments, and will include observations, video/audio recordings, student- and teacher-generated artifacts, and pre and post assessments of students' knowledge and self-efficacy. Mixed methods analyses of these data, and syntheses of findings across participants, classroom enactments, and project years, will explore effective ways to support co-design among art teachers, mathematics teachers, and researchers; and the impact of art-integrated activities on students' data literacy. This project will reach 12 teachers and their students across 6 New York city schools. By building capacity and knowledge about how to initiate and sustain teachers' interdisciplinary curriculum collaborations, the project will have broader impact. Refined project materials, including pedagogical approaches, toolkits and adaptable classroom activities, will be disseminated to facilitate classroom adoption by other educators who wish to undertake similar art-integrated data literacy curriculum design collaborations, and will thus ultimately broaden participation in data science among diverse youth within and beyond New York City.

Building Students' Data Literacy through the Co-design of Curriculum by Mathematics and Art Teachers (Collaborative Research: Vacca)

The aim of this project is to enact and study a process in which middle school teachers of mathematics and visual arts co-design and teach activities that combine math and art to teach data science.

Lead Organization(s): 
Award Number: 
1908142
Funding Period: 
Mon, 07/01/2019 to Wed, 06/30/2021
Full Description: 

The aim of this project is to enact and study a process in which middle school teachers of mathematics and visual arts co-design and teach activities that combine math and art to teach data science. Many existing efforts to promote data literacy are grounded in mathematical concepts of central tendency and variation, and typically are narrowly focused in single subject domains. Taking an art-based perspective on data science has the potential to promote student relevance, accessibility, engagement, reasoning, and meaning-making with data science. Moreover, visualization technology has advanced to a degree that the relation between the information in data and visual aesthetic can be leveraged easily. To explore the opportunity this offers, research on this project will examine how to equip teachers to develop such interdisciplinary pedagogical approaches to cultivate their students' data literacy. This exploratory project will provide support for 12 teachers during summer workshops and during the school year as these teachers implement their co-designed units in their classrooms. The work addresses the following questions: (1) How do we support effective co-design of data literacy units among art teachers, mathematics teachers, and researchers? (2) How are teachers able to use the unit materials in their classrooms to engage students in data literacy? And (3) How does an art-based approach support students' data literacy? Answers to these questions will build an understanding of how to support interdisciplinary curriculum design collaborations among researchers and teachers. They will also show how art-integrated, maker-oriented activities can support middle school learners' data literacy development; and how to design technologies that are accessible and powerful to teachers and learners in these interdisciplinary environments.

Through summer workshops and year-round design collaborations, the project will iteratively design, test and refine four units for middle school classrooms, including activities, tools, and assessments, to promote students' data literacy. Data will be collected from co-design sessions as well as classroom-enactments, and will include observations, video/audio recordings, student- and teacher-generated artifacts, and pre and post assessments of students' knowledge and self-efficacy. Mixed methods analyses of these data, and syntheses of findings across participants, classroom enactments, and project years, will explore effective ways to support co-design among art teachers, mathematics teachers, and researchers; and the impact of art-integrated activities on students' data literacy. This project will reach 12 teachers and their students across 6 New York city schools. By building capacity and knowledge about how to initiate and sustain teachers' interdisciplinary curriculum collaborations, the project will have broader impact. Refined project materials, including pedagogical approaches, toolkits and adaptable classroom activities, will be disseminated to facilitate classroom adoption by other educators who wish to undertake similar art-integrated data literacy curriculum design collaborations, and will thus ultimately broaden participation in data science among diverse youth within and beyond New York City.

Building Students' Data Literacy through the Co-design of Curriculum by Mathematics and Art Teachers (Collaborative Research: Silander)

The aim of this project is to enact and study a process in which middle school teachers of mathematics and visual arts co-design and teach activities that combine math and art to teach data science.

Award Number: 
1908030
Funding Period: 
Mon, 07/01/2019 to Wed, 06/30/2021
Full Description: 

The aim of this project is to enact and study a process in which middle school teachers of mathematics and visual arts co-design and teach activities that combine math and art to teach data science. Many existing efforts to promote data literacy are grounded in mathematical concepts of central tendency and variation, and typically are narrowly focused in single subject domains. Taking an art-based perspective on data science has the potential to promote student relevance, accessibility, engagement, reasoning, and meaning-making with data science. Moreover, visualization technology has advanced to a degree that the relation between the information in data and visual aesthetic can be leveraged easily. To explore the opportunity this offers, research on this project will examine how to equip teachers to develop such interdisciplinary pedagogical approaches to cultivate their students' data literacy. This exploratory project will provide support for 12 teachers during summer workshops and during the school year as these teachers implement their co-designed units in their classrooms. The work addresses the following questions: (1) How do we support effective co-design of data literacy units among art teachers, mathematics teachers, and researchers? (2) How are teachers able to use the unit materials in their classrooms to engage students in data literacy? And (3) How does an art-based approach support students' data literacy? Answers to these questions will build an understanding of how to support interdisciplinary curriculum design collaborations among researchers and teachers. They will also show how art-integrated, maker-oriented activities can support middle school learners' data literacy development; and how to design technologies that are accessible and powerful to teachers and learners in these interdisciplinary environments.

Through summer workshops and year-round design collaborations, the project will iteratively design, test and refine four units for middle school classrooms, including activities, tools, and assessments, to promote students' data literacy. Data will be collected from co-design sessions as well as classroom-enactments, and will include observations, video/audio recordings, student- and teacher-generated artifacts, and pre and post assessments of students' knowledge and self-efficacy. Mixed methods analyses of these data, and syntheses of findings across participants, classroom enactments, and project years, will explore effective ways to support co-design among art teachers, mathematics teachers, and researchers; and the impact of art-integrated activities on students' data literacy. This project will reach 12 teachers and their students across 6 New York city schools. By building capacity and knowledge about how to initiate and sustain teachers' interdisciplinary curriculum collaborations, the project will have broader impact. Refined project materials, including pedagogical approaches, toolkits and adaptable classroom activities, will be disseminated to facilitate classroom adoption by other educators who wish to undertake similar art-integrated data literacy curriculum design collaborations, and will thus ultimately broaden participation in data science among diverse youth within and beyond New York City.

Improving Grades 6-8 Students' Mathematics Achievement in Modeling and Problem Solving through Effective Sequencing of Instructional Practices

This project will provide structured and meaningful scaffolds for teachers in examining two research-based teaching strategies hypothesized to positively impact mathematics achievement in the areas of mathematical modeling and problem solving. The project investigates whether the order in which teachers apply these practices within the teaching of mathematics content has an impact on student learning.

Project Email: 
Lead Organization(s): 
Award Number: 
1907840
Funding Period: 
Mon, 07/01/2019 to Fri, 06/30/2023
Project Evaluator: 
Kurt Steuck
Full Description: 

The Researching Order of Teaching project will provide structured and meaningful scaffolds for teachers in examining two research-based teaching strategies hypothesized to positively impact mathematics achievement in the areas of mathematical modeling and problem solving. The first strategy, Explicit Attention to Concepts (EAC), is a set of practices that draw students' attention specifically to mathematical concepts in ways that extend beyond memorization, procedures, or application of skills. This strategy may include teachers asking students to connect multiple mathematical representations, compare solution strategies, discuss mathematical reasoning underlying procedures, or to identify a main mathematical idea in a lesson and how it fits into the broader mathematical landscape. The second strategy, Student Opportunities to Struggle (SOS), entails providing students with time and space to make sense of graspable content, overcoming confusion points, stimulating personal sense-making, building perseverance, and promoting openness to challenge. This strategy may include teachers assigning problems with multiple solution strategies, asking students to look for patterns and make conjectures, encouraging and promoting discourse around confusing or challenging ideas, and asking students for extended mathematical responses. This project investigates whether the order in which teachers apply these practices within the teaching of mathematics content has an impact on student learning. This study builds on previous work that had identified an interaction between the EAC and SOS instructional strategies, and associated teacher reporting of stronger use of the practices with higher student mathematics achievement.

The project will have four key design features. First, the project will adopt and extend the research-based EAC/SOS conceptual framework, and explicitly responds to the call for further research on the interactions. Second, the project will focus on the mathematical areas of modeling and problem solving, two complex and critical competencies for all students in the middle grades. Third, the project will position teachers as collaborators in the research with needed expertise. Finally, the project will make use of research methods from crossover clinical trials to implementation in classrooms. The project aims to identify the affordances and constraints of the EAC/SOS framework in the design and development of instructional practices, to identify student- and teacher-level factors associated with changes in modeling and problem solving outcomes, to analyze teachers' implementations EAC and SOS in teaching modeling and problem solving and to associate those implementation factors with student achievement changes, and to determine whether the ordering of these two strategies correlates with differences in achievement. The project will collect classroom observation data and make use of existing tools to obtain reliable and valid ratings of the EAC and SOS strategies in action.The design of the study features a randomized 2 x 2 cluster crossover trial with a sample of teachers for 80% power. The project builds on existing state infrastructure and relationships with a wide array of school districts in the context of professional development, and aims to create a formal Teacher-Researcher Alliance for Investigating Learning as a part of the project work.

Developing Organizational Capacity to Improve K-8 Mathematics Teaching and Learning

This project will develop and test a leadership model to improve K-8 mathematics teaching and learning by involving stakeholders across the K-8 spectrum. The project will support teachers, teacher leaders, and administrators in collectively identifying and addressing problems of practice in the teaching and learning of mathematics, and in turn develop plans to improve school and district organizational capacities to support stronger mathematics teaching.

Award Number: 
1907681
Funding Period: 
Mon, 07/01/2019 to Sun, 06/30/2024
Full Description: 

The Developing Organizational Capacity to Improve K-8 Mathematics Teaching and Learning is a 4-year implementation and improvement project. The project will develop and test a leadership model to improve K-8 mathematics teaching and learning by involving stakeholders across the K-8 spectrum. The project will support teachers, teacher leaders, and administrators in collectively identifying and addressing problems of practice in the teaching and learning of mathematics, and in turn develop plans to improve school and district organizational capacities to support stronger mathematics teaching. At the heart of the project is the Elementary Mathematics Leadership (EML) model, which is designed to improve stakeholder understandings of effective math teaching practices. The EML model involves collaboratively identifying classroom-based problems of practice with school and district personnel, designing and implementing professional development aligned with the problems of practice, and iterating those cycles of development, implementation, and revision to assess the model's effectiveness.

The EML model operates at the teacher, school, and district level using a design-based implementation research approach. At the district level, leadership teams in conjunction with researchers will identify problems of practice for which work on those problems will lead to a more coherent mathematics instruction in the district. Following this, professional development and coaching at the teacher level will be designed and implemented to target the problem of practice, with a focus on big ideas within the Common Core State Standards for Mathematics. This phase of the model also includes professional development aimed at school leaders and district administrators to strengthen organizational capacity to support and lead change related to the problem of practice. The final phase of the model calls on researchers, district, and school personnel to engage in an annual redesign of the intervention, making use of data gathered during the school year and evidence about what is happening in classrooms. This design acknowledges the broader policy context in which schools and districts operate as they work towards instructional change. To evaluate the effectiveness of the overall EML model, the project will collect a wide variety of data, including student achievement outcomes using standardized tests; assessments of teachers' mathematical knowledge, instructional practices, and efficacy measures; and measures of leader, administrator, and organizational capacities to support high-quality mathematics instruction. Four districts will be recruited to participate, enacting the model in pairs with a staggered start for one pair of districts to be able to measure treatment effects, using a variation of a switching replications design. Classroom practice and teacher outcomes will be assessed using a variety of MKT assessments, the Mathematical Quality of Instruction (MQI), and the Instructional Quality Assessment (IQA). School level outcomes will be collected via a leadership assessment and interview data, and district level outcomes will be assessed through the use of interview and documentary data. Analysis will include a statistical analysis of the EML model using hierarchical linear modeling, MANOVA/ANOVA, and regression as appropriate at the level of students and teachers, and qualitative analysis and descriptive statistics will be used at the school and district level due to small sample size.

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