Achievement/Growth

How Deep Structural Modeling Supports Learning with Big Ideas in Biology (Collaborative Research: Capps)

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2010223
Funding Period: 
Sat, 08/01/2020 to Wed, 07/31/2024
Full Description: 

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. This need is forcefully advanced by policy leaders including the National Research Council and the College Board. They point out that learning is more effective when students organize and link information within a consistent knowledge framework, which is what big ideas should provide. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology. In DSM, students learn a big idea as the underlying, or "deep" structure of a set of examples that contain the structure, but with varying outward details. As learners begin to apprehend the deep structure (i.e., the big idea) within the examples, they use the tools and procedures of scientific modeling to express and develop it. According to theories of learning that undergird DSM, the result of this process should be a big idea that is flexible, meaningful, and easy to express, thus providing an ideal framework for making sense of new information learners encounter (i.e., learning with the big idea). To the extent that this explanation is born out in rigorous research tests and within authentic curriculum materials, it contributes important knowledge about how teaching and learning can be organized around big ideas, and not only for deep structural modeling but for other instructional approaches as well.

This project has twin research and prototype development components. Both are taking place in the context of high school biology, in nine classrooms across three districts, supporting up to 610 students. The work focuses on three design features of DSM: (1) embedding model source materials with intuitive, mechanistic ideas; (2) supporting learners to abstract those ideas as a deep structure shared by a set of sources; and (3) representing this deep structure efficiently within the model. In combination, these features support students to understand an abstract, intuitively rich, and efficient knowledge structure that they subsequently use as a framework to interpret, organize, and link disciplinary content. A series of five research studies build on one another to develop knowledge about whether and how the design features bring about these anticipated effects. Earlier studies in the sequence are small-scale classroom experiments randomly assigning students to either deep structural modeling or to parallel, non modeling controls. Measures discriminate for the anticipated effects during learning and on posttests. Later studies use qualitative methods to carefully trace the anticipated effects over time and across topics. As a group, these studies are contributing generalized knowledge of how learners can effectively abstract and represent big ideas and how these ideas can be leveraged as frameworks for learning content with understanding. Two research-tested biology curriculum prototypes are being developed as the studies evolve: a quarter-year DSM biology curriculum centered on energy; and an eighth-year DSM unit centered on natural selection.

How Deep Structural Modeling Supports Learning with Big Ideas in Biology (Collaborative Research: Shemwell)

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2010334
Funding Period: 
Sat, 08/01/2020 to Wed, 07/31/2024
Full Description: 

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. This need is forcefully advanced by policy leaders including the National Research Council and the College Board. They point out that learning is more effective when students organize and link information within a consistent knowledge framework, which is what big ideas should provide. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology. In DSM, students learn a big idea as the underlying, or "deep" structure of a set of examples that contain the structure, but with varying outward details. As learners begin to apprehend the deep structure (i.e., the big idea) within the examples, they use the tools and procedures of scientific modeling to express and develop it. According to theories of learning that undergird DSM, the result of this process should be a big idea that is flexible, meaningful, and easy to express, thus providing an ideal framework for making sense of new information learners encounter (i.e., learning with the big idea). To the extent that this explanation is born out in rigorous research tests and within authentic curriculum materials, it contributes important knowledge about how teaching and learning can be organized around big ideas, and not only for deep structural modeling but for other instructional approaches as well.

This project has twin research and prototype development components. Both are taking place in the context of high school biology, in nine classrooms across three districts, supporting up to 610 students. The work focuses on three design features of DSM: (1) embedding model source materials with intuitive, mechanistic ideas; (2) supporting learners to abstract those ideas as a deep structure shared by a set of sources; and (3) representing this deep structure efficiently within the model. In combination, these features support students to understand an abstract, intuitively rich, and efficient knowledge structure that they subsequently use as a framework to interpret, organize, and link disciplinary content. A series of five research studies build on one another to develop knowledge about whether and how the design features bring about these anticipated effects. Earlier studies in the sequence are small-scale classroom experiments randomly assigning students to either deep structural modeling or to parallel, non modeling controls. Measures discriminate for the anticipated effects during learning and on posttests. Later studies use qualitative methods to carefully trace the anticipated effects over time and across topics. As a group, these studies are contributing generalized knowledge of how learners can effectively abstract and represent big ideas and how these ideas can be leveraged as frameworks for learning content with understanding. Two research-tested biology curriculum prototypes are being developed as the studies evolve: a quarter-year DSM biology curriculum centered on energy; and an eighth-year DSM unit centered on natural selection.

Responsive Instruction for Emergent Bilingual Learners in Biology Classrooms

This project seeks to support emergent bilingual students in high school biology classrooms. The project team will study how teachers make sense of and use an instructional model that builds on students' cultural and linguistic strengths to teach biology in ways that are responsive. The team will also study how such a model impacts emergent bilingual students' learning of biology and scientific language practices, as well as how it supports students' identities as knowers/doers of science.

Lead Organization(s): 
Award Number: 
2010153
Funding Period: 
Wed, 07/01/2020 to Fri, 06/30/2023
Full Description: 

The population of students who are emergent bilinguals in the US is not only growing in number but also, historically, has been underrepresented in STEM fields. Emergent bilingual students have not had access to the same high-quality science education as their peers, despite bringing rich academic, linguistic and cultural strengths to their learning. Building on smaller pilot studies and ideas that have shown to be successful in supporting emergent bilingual students' learning of elementary science, this project seeks to support emergent bilingual students in high school biology classrooms. The project team will study how teachers make sense of and use an instructional model that builds on students' cultural and linguistic strengths to teach biology in ways that are responsive. The team will also study how such a model impacts emergent bilingual students' learning of biology and scientific language practices, as well as how it supports students' identities as knowers/doers of science. The collaboration will include two partner districts that will allow the project work to impact about 11,000 high school students and 30 biology teachers in Florida. Over time, the project team plans to enact and study three cohorts of teachers and students; use the information learned to improve the instructional model; and develop lessons, a website, and other materials that can be applied to other contexts to support emergent bilingual students' learning of biology. This project will increase emergent bilingual students' participation in biology classes, improve their achievement and engagement in science and engineering practices, extend current research-based practices, and document how to build on emergent bilingual students' strengths and prior experiences.

In two previous pilot studies through the collaboration of an interdisciplinary team, the project team developed an instructional model that they found supported emergent bilingual students to have high-quality opportunities for science learning. The model builds on research related to culturally responsive instruction; funds of knowledge (including work on identity affirmation and collaboration); and linguistically responsive instruction (including using students' home languages and multiple modalities, and explicit attention to academic language). Using design-based research, the project team will gather data from two primary settings: their professional development program and biology teachers' classrooms. They will use these data both to improve the instructional model and professional development for biology teachers. Additionally, the project team will study how teachers use the model to support emergent bilingual students' biology engagement and achievement, as well as study how biology teachers enact the instructional model in two school districts. The project will work toward three main outcomes: a) to develop new knowledge related to how diverse learners develop language and content knowledge in biology through engaging in science and engineering practices; b) to generate new knowledge about how biology teachers can adapt responsive instruction to local contexts and student populations; and c) to articulate an instructional model for biology teachers of emergent bilingual students that is rigorous, yet practical. The dissemination and sustainability include publishing and presenting findings at a range of conferences and journals; making available the refined instructional framework and professional development materials on a website; communication with district leaders and policymakers; and white papers that can be more widely distributed.

Paving the Way for Fractions: Identifying Foundational Concepts in First Grade (Collaborative Research: Newcombe)

The goal of this project is to investigate the extent to which individual differences in informal fraction-related knowledge in first-grade children are associated with short- and longer-term fractions and math outcomes, and to see whether there is a causal link between level of informal fraction-related knowledge and the ability to profit from fractions instruction that directly builds on this knowledge.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2000424
Funding Period: 
Mon, 06/01/2020 to Fri, 05/31/2024
Full Description: 

Although fractions represent a crucial topic in early childhood education, many students develop only a tenuous grasp of fraction concepts, even after several years of fraction instruction that is aligned with current standards. The goal of this project, led by a team of researchers at the University of Delaware and Temple University, is to answer important questions about the informal understandings of fractions young children have before they come to school and what their relations are to fraction learning in more formal instructional settings. Proficiency with fractions dramatically increases the likelihood of students succeeding in math, which in turn increases participation in the STEM workforce. Importantly, large individual differences in fraction understandings are apparent at the start of fractions instruction in the intermediate grades. Early fraction misunderstandings cascade into more severe math weaknesses in later grades, especially when instruction may shift abruptly from whole numbers to fractions. There is a critical need to understand the roots of individual differences that arise before formal instruction takes place. Young children possess important informal fraction understandings before they come to school, but the range of these abilities and their role in formal fraction learning and development is not well understood. The goal of this project is: a) to investigate the extent to which individual differences in informal fraction-related knowledge in first-grade children are associated with short- and longer-term fractions and math outcomes; and b) to see whether there is a causal link between level of informal fraction-related knowledge and the ability to profit from fractions instruction that directly builds on this knowledge. The findings from the project hold promise for informing early childhood educators how fractions can be incorporated in the first-grade curriculum in new and meaningful ways. Though the findings should be beneficial to all students, the project will specifically target members of groups underrepresented in STEM fields, including ethnic and racial minority and low-income students.

The project design includes both an observational study and an experimental study. The observational study will: (1) document individual differences in informal fraction-related knowledge in first grade; (2) determine concurrent relations between this informal knowledge and general cognitive and whole number competencies; and (3) examine whether informal fraction-related knowledge at the beginning of first grade uniquely predicts math outcomes at the end. The experimental study will explore the extent to which first graders' informal and formal fraction concepts can be affected by training. The researchers will test whether training on the number line, which is continuous and closely aligned with the mental representation of the magnitude of all real numbers, will help students capitalize on their informal fraction understandings of proportionality, scaling, and equal sharing as well as their experience with integers to learn key fraction concepts. Together, the synergistic studies will pinpoint the role informal fraction knowledge in learning key fraction concepts. All data will be collected in Delaware schools serving socioeconomically and ethnically diverse populations of students. Primary measures include assessments of informal fraction knowledge (proportional reasoning, spatial scaling, equal sharing), executive functioning, vocabulary, whole number knowledge, whole number/fraction number line estimation, formal fraction knowledge, and broad mathematics achievement (calculation, fluency, applied problems).

Pandemic Learning Loss in U.S. High Schools: A National Examination of Student Experiences

As a result of the COVID-19 pandemic, schools across much of the U.S. have been closed since mid-March of 2020 and many students have been attempting to continue their education away from schools. Student experiences across the country are likely to be highly variable depending on a variety of factors at the individual, home, school, district, and state levels. This project will use two, nationally representative, existing databases of high school students to study their experiences in STEM education during the COVID-19 pandemic.

Lead Organization(s): 
Award Number: 
2030436
Funding Period: 
Fri, 05/15/2020 to Fri, 04/30/2021
Full Description: 

As a result of the COVID-19 pandemic, schools across much of the U.S. have been closed since mid-March of 2020 and many students have been attempting to continue their education away from schools. Student experiences across the country are likely to be highly variable depending on a variety of factors at the individual, home, school, district, and state levels. This project will use two, nationally representative, existing databases of high school students to study their experiences in STEM education during the COVID-19 pandemic. The study intends to ascertain whether students are taking STEM courses in high school, the nature of the changes made to the courses, and their plans for the fall. The researchers will identify the electronic learning platforms in use, and other modifications made to STEM experiences in formal and informal settings. The study is particularly interested in finding patterns of inequities for students in various demographic groups underserved in STEM and who may be most likely to be affected by a hiatus in formal education.

This study will collect data using the AmeriSpeak Teen Panel of approximately 2,000 students aged 13 to 17 and the Infinite Campus Student Information System with a sample of approximately 2.5 million high school students. The data sets allow for relevant comparisons of student experiences prior to and during the COVID-19 pandemic and offer unique perspectives with nationally representative samples of U.S. high school students. New data collection will focus on formal and informal STEM learning opportunities, engagement, STEM course taking, the nature and frequency of instruction, interactions with teachers, interest in STEM, and career aspirations. Weighted data will be analyzed using descriptive statistics and within and between district analysis will be conducted to assess group differences. Estimates of between group pandemic learning loss will be provided with attention to demographic factors.

This RAPID award is made by the DRK-12 program in the Division of Research on Learning. The Discovery Research PreK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics by preK-12 students and teachers, through the research and development of new innovations and approaches. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for the projects.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

 

 

 

 

Comparing the Efficacy of Collaborative Professional Development Formats for Improving Student Outcomes of a Student-Teacher-Scientist Partnership Program

The goal of this project is to study how the integration of an online curriculum, scientist mentoring of students, and professional development for both teachers and scientist mentors can improve student outcomes. In this project, teachers and scientist mentors will engage collaboratively in a professional development module which focuses on photosynthesis and cellular respiration and is an example of a student-teacher-scientist partnership.

Lead Organization(s): 
Award Number: 
2010556
Funding Period: 
Tue, 09/01/2020 to Sun, 08/31/2025
Full Description: 

Science classrooms in the U.S. today increasingly expect students to engage in the practices of science in a way that help them form a deeper understanding of disciplinary core ideas and the practices by which science is done. To do this, students should learn how scientists work and communicate. It also calls for changes in how teachers teach science, which in turn creates a need for high-quality professional development so they can be more effective in the classroom. Professional scientists can also benefit from training preparing them to support teachers, motivate students, and model for students how scientists think and work. Preparing teachers and scientists through collaborative professional development can help maximize the impact they can have on student outcomes. To have the broadest impact, such professional development should be cost-effective and available to teachers in rural or underserved areas. This project focuses on high school life science (biology) teachers and their students. It will make use of an online mentoring platform, a student-teacher-scientist partnership program established in 2005. That study found that implementing in combination with high-quality, in-person collaborative teacher/scientist professional development resulted in positive and statistically significant effects on student achievement and attitudes versus business-as-usual methods of teaching the same science content. This project has two main components: 1) a replication study to determine if findings of the previous successful study hold true; and 2) adding an online format for delivering collaborative professional development to teachers and scientists enabling one to compare the effectiveness of online professional development and in-person professional development delivery formats for improving student outcomes.

The goal of this project is to study how the integration of an online curriculum, scientist mentoring of students, and professional development for both teachers and scientist mentors can improve student outcomes. In this project, teachers and scientist mentors will engage collaboratively in a professional development module which focuses on photosynthesis and cellular respiration and is an example of a student-teacher-scientist partnership. Teachers will use their training to teach the curriculum to their students with students receiving mentoring from the scientists through an online platform. Evaluation will examine whether this curriculum, professional development, and mentoring by scientists will improve student achievement on science content and attitudes toward scientists. The project will use mixed-methods approaches to explore potential factors underlying efficacy differences between in-person and online professional development. An important component of this project is comparing in-person professional development to an online delivery of professional development, which can be more cost-effective and accessible by teachers, especially those in rural and underserved areas.

The Discovery Research K-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering, and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models, and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Generalized Embodied Modeling to Support Science through Technology Enhanced Play (Collaborative Research: Danish)

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
1908632
Funding Period: 
Thu, 08/01/2019 to Sun, 07/31/2022
Full Description: 

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students. GEM stands for Generalized Embodied Modeling. Through these embodied, play-as-modeling activities, students will learn the core concepts of science, and the conceptual skills of modeling and systematic measurement. MR environments use new sensing technologies to help transform young children's physical actions during pretend play into a set of symbolic representations and parameters in a science simulation. As students physically move around the classroom, the computer will track their motion and interactions with selected objects and translate their physical activity into a shared display. For example, students pretend they are water particles and work together to model different states of matter. The children see their activity projected onto a computer simulation where a model of a water particle is displayed over the video of themselves. As students collectively reflect upon the nature of a water molecule, they refine their understanding of water as ice, a liquid or a gas. The proposed innovation allows the students to program and revise their own mixed reality simulations as part of their modeling cycle. Embodied and computational modeling will help students to reflect on their models in a unique way that will make their models more computationally accurate and enhance their understanding of the underlying concepts.

The project will research how using the body as a component of the modeling cycle differs from and interacts with the articulation of a scientific model through more structured computational means. The project will investigate the benefits of combining embodiment with computational elements in GEM:STEP by studying the range of concepts that students can learn in this manner. Lessons will be developed to address different disciplinary core ideas, such as states of matter, pollination as a complex system, or decomposition, as well as cross-cutting concepts of systems thinking, and energy/matter flow, all of which link directly to upper elementary science curriculum. Project research will gather data to understand what kinds of models students develop, what learning processes are supported using GEM:STEP, and what learning results. The data will include: (1) documenting and analyzing what students modeled and how accurate the models are; (2) recording student activity using audio and voice to code their activity to document learning processes and to look at how different forms of modeling interact with one another to promote learning; and (3) pre-post content measures to assess learning. All of the software that is developed for GEM:STEP will be made available as Open Source projects, allowing other researchers to build upon and extend this work. The results of the research will be disseminated in academic conferences and peer reviewed journals. The motion tracking software is already available on Github, a popular open-source repository. Once developed, the aim is to implement GEM:STEP in a wide range of classroom contexts, supported by a user-friendly interface, teacher guides, and professional development.

Generalized Embodied Modeling to Support Science through Technology Enhanced Play (Collaborative Research: Enyedy)

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
1908791
Funding Period: 
Thu, 08/01/2019 to Sun, 07/31/2022
Full Description: 

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students. GEM stands for Generalized Embodied Modeling. Through these embodied, play-as-modeling activities, students will learn the core concepts of science, and the conceptual skills of modeling and systematic measurement. MR environments use new sensing technologies to help transform young children's physical actions during pretend play into a set of symbolic representations and parameters in a science simulation. As students physically move around the classroom, the computer will track their motion and interactions with selected objects and translate their physical activity into a shared display. For example, students pretend they are water particles and work together to model different states of matter. The children see their activity projected onto a computer simulation where a model of a water particle is displayed over the video of themselves. As students collectively reflect upon the nature of a water molecule, they refine their understanding of water as ice, a liquid or a gas. The proposed innovation allows the students to program and revise their own mixed reality simulations as part of their modeling cycle. Embodied and computational modeling will help students to reflect on their models in a unique way that will make their models more computationally accurate and enhance their understanding of the underlying concepts.

The project will research how using the body as a component of the modeling cycle differs from and interacts with the articulation of a scientific model through more structured computational means. The project will investigate the benefits of combining embodiment with computational elements in GEM:STEP by studying the range of concepts that students can learn in this manner. Lessons will be developed to address different disciplinary core ideas, such as states of matter, pollination as a complex system, or decomposition, as well as cross-cutting concepts of systems thinking, and energy/matter flow, all of which link directly to upper elementary science curriculum. Project research will gather data to understand what kinds of models students develop, what learning processes are supported using GEM:STEP, and what learning results. The data will include: (1) documenting and analyzing what students modeled and how accurate the models are; (2) recording student activity using audio and voice to code their activity to document learning processes and to look at how different forms of modeling interact with one another to promote learning; and (3) pre-post content measures to assess learning. All of the software that is developed for GEM:STEP will be made available as Open Source projects, allowing other researchers to build upon and extend this work. The results of the research will be disseminated in academic conferences and peer reviewed journals. The motion tracking software is already available on Github, a popular open-source repository. Once developed, the aim is to implement GEM:STEP in a wide range of classroom contexts, supported by a user-friendly interface, teacher guides, and professional development.

Developing Leaders, Transforming Practice in K-5 Mathematics: An Examination of Models for Elementary Mathematics Specialists (Collaborative Research: Lewis)

This project will study the Developing Leaders Transforming Practice (DLTP) intervention, which aims to improve teachers' instructional practices, increase student mathematics understanding and achievement.

Lead Organization(s): 
Award Number: 
1906588
Funding Period: 
Sun, 09/01/2019 to Thu, 08/31/2023
Full Description: 

Minimal rigorous research has been conducted on the effect of various supports for quality mathematics instruction and providing guidance on the development and use of Elementary Mathematics Specialists (EMSs) on student achievement. Portland Public Schools (PPS), Portland State University, and RMC Research Corporation will study the Developing Leaders Transforming Practice (DLTP) intervention, which aims to improve teachers' instructional practices, increase student mathematics understanding and achievement. The project team will evaluate the efficacy and use of EMSs by testing four implementation models that consider the various ways EMSs are integrated into schools. DLTP builds on EMS research, investigating EMSs both as elementary mathematics teachers and coaches by articulating four models and examining their efficacy for both student and teacher learning. This study has the potential to provide benefits both within and beyond PPS as it informs the preparation and use of EMSs. Determining which model is best in certain contexts provides a focus for the expansion of mathematics support.

DLTP enhances the research base by examining the effect of teacher PD on student achievement through a rigorous quasi-experimental design. The project goals will be met by addressing 4 research questions: 1) What is the effect of the intervention on teacher leadership?; 2) What is the effect of the intervention on teachers' use of research-based instructional practices?; 3) What is the effect of the intervention on a school's ability to sustain ongoing professional learning for teachers?; and 4) What is the effect of the intervention on student mathematics achievement? Twelve elementary schools in PPS will select elementary teachers to participate in the DLTP and adopt an implementation model that ranges from direct to diffuse engagement with students: elementary mathematics teacher, grade level coach, grade-level and building-level coach, or building-level coach. The research team will conduct 4 major studies that include rigorous quasi-experimental designs and a multi-method approach to address the research questions: leadership study, instructional practices study, school study, and student achievement study. Several tools will be created by the project - a leadership rubric designed to measure changes in EMS mathematics leadership because of the project and a 5-part teacher survey designed capture EMS leadership skills, pedagogical content knowledge, use of research-based practices, and school climate for mathematics learning as well as implementation issues.

Developing Leaders, Transforming Practice in K-5 Mathematics: An Examination of Models for Elementary Mathematics Specialists Collaborative Research: Davis)

This project will study the Developing Leaders Transforming Practice (DLTP) intervention, which aims to improve teachers' instructional practices, increase student mathematics understanding and achievement.

Lead Organization(s): 
Award Number: 
1906565
Funding Period: 
Sun, 09/01/2019 to Thu, 08/31/2023
Full Description: 

Minimal rigorous research has been conducted on the effect of various supports for quality mathematics instruction and providing guidance on the development and use of Elementary Mathematics Specialists (EMSs) on student achievement. Portland Public Schools (PPS), Portland State University, and RMC Research Corporation will study the Developing Leaders Transforming Practice (DLTP) intervention, which aims to improve teachers' instructional practices, increase student mathematics understanding and achievement. The project team will evaluate the efficacy and use of EMSs by testing four implementation models that consider the various ways EMSs are integrated into schools. DLTP builds on EMS research, investigating EMSs both as elementary mathematics teachers and coaches by articulating four models and examining their efficacy for both student and teacher learning. This study has the potential to provide benefits both within and beyond PPS as it informs the preparation and use of EMSs. Determining which model is best in certain contexts provides a focus for the expansion of mathematics support.

DLTP enhances the research base by examining the effect of teacher PD on student achievement through a rigorous quasi-experimental design. The project goals will be met by addressing 4 research questions: 1) What is the effect of the intervention on teacher leadership?; 2) What is the effect of the intervention on teachers' use of research-based instructional practices?; 3) What is the effect of the intervention on a school's ability to sustain ongoing professional learning for teachers?; and 4) What is the effect of the intervention on student mathematics achievement? Twelve elementary schools in PPS will select elementary teachers to participate in the DLTP and adopt an implementation model that ranges from direct to diffuse engagement with students: elementary mathematics teacher, grade level coach, grade-level and building-level coach, or building-level coach. The research team will conduct 4 major studies that include rigorous quasi-experimental designs and a multi-method approach to address the research questions: leadership study, instructional practices study, school study, and student achievement study. Several tools will be created by the project - a leadership rubric designed to measure changes in EMS mathematics leadership because of the project and a 5-part teacher survey designed capture EMS leadership skills, pedagogical content knowledge, use of research-based practices, and school climate for mathematics learning as well as implementation issues.

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