Content Knowledge

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.

Young Mathematicians: Expanding an Innovative and Promising Model Across Learning Environments to Promote Preschoolers' Mathematics Knowledge

The goal of this design and development project is to address the critical need for innovative resources that transform the mathematics learning environments of preschool children from under-resourced communities by creating a cross-context school-home intervention.

Award Number: 
1907904
Funding Period: 
Mon, 07/01/2019 to Fri, 06/30/2023
Full Description: 

Far too many children in the U.S. start kindergarten lacking the foundational early numeracy skills needed for academic success. This project contributes to the goal of enhancing the learning and teaching of early mathematics in order to build a STEM-capable workforce and STEM-literate citizenry, which are both crucial to our nation's prosperity and competitiveness. Preparation for the STEM-workforce must start early, as young children's mathematics development undergirds cognitive development, building brain architecture, and supporting problem-solving, puzzling, and persevering, while strongly impacting and predicting future success in school. Preschool children from low socio-economic backgrounds are particularly at risk, as their mathematics knowledge may be up to a full year behind their middle-income peers. Despite agreements about the importance of mathematics-rich interactions for young children's learning and development, most early education teachers and families are not trained in evidence-based methods that can facilitate these experiences, making preschool learning environments (such as school and home) a critical target for intervention. The benefit of this project is that it will develop a robust model for a school-based intervention in early mathematics instruction. The model has the potential to broaden participation by providing instructional materials that support adult-child interaction and engagement in mathematics, explicitly promoting school-home connections in mathematics, and addressing educators' and families' attitudes toward mathematics while promoting children's mathematical knowledge and narrowing opportunity gaps.

The goal of this design and development project is to address the critical need for innovative resources that transform the mathematics learning environments of preschool children from under-resourced communities by creating a cross-context school-home intervention. To achieve this goal, qualitative and quantitative research methodologies will be employed, integrating data from multiple sources and stakeholders. Specifically, the project will: (1) engage in a materials design and development process that includes an iterative cycle of design, development, and implementation, collaborating with practitioners and families in real-world settings; (2) collect and analyze data from at least 40 Head Start classrooms, implementing the mathematics materials to ensure that the classroom and family mathematics materials and resources are engaging, usable, and comprehensible to preschoolers, teachers, and families; and (3) conduct an experimental study that will measure the impact of the intervention on preschool children's mathematics learning. The researchers will analyze collected data using hierarchical linear regression modeling to account for the clustering of children within classrooms. The researchers will also use a series of regression models and multi-level models to determine whether the intervention promotes student outcomes and whether it supports teachers' and families' positive attitudes toward mathematics.

Using Animated Contrasting Cases to Improve Procedural and Conceptual Knowledge in Geometry

This project aims to support stronger student outcomes in the teaching and learning of geometry in the middle grades through engaging students in animated contrasting cases of worked examples. The project will design a series of animated geometry curricular materials on a digital platform that ask students to compare different approaches to solving the same geometry problem. The study will measure changes in students' procedural and conceptual knowledge of geometry after engaging with the materials and will explore the ways in which teachers implement the materials in their classrooms.

Award Number: 
1907745
Funding Period: 
Thu, 08/01/2019 to Sun, 07/31/2022
Full Description: 

This project aims to support stronger student outcomes in the teaching and learning of geometry in the middle grades through engaging students in animated contrasting cases of worked examples. Animated contrasting cases are a set of two worked examples for the same geometry problem, approached in different ways. The animations show the visual moves and annotations students would make in solving the problems. Students are asked to compare and discuss the approaches. This theoretically-grounded approach extends the work of cognitive scientists and mathematics educators who have shown this approach supports strong student learning in algebra. The project will design a series of animated geometry curricular materials on a digital platform that ask students to compare different approaches to solving the same geometry problem. The study will measure changes in students' procedural and conceptual knowledge of geometry after engaging with the materials and will explore the ways in which teachers implement the materials in their classrooms. This work is particularly important as geometry is an understudied area in mathematics education, and national and international assessments at the middle school level consistently identify geometry as a mathematics content area in which students score the lowest.

This project draws on prior work that documents the impact of comparison on students' learning in algebra. Providing students with opportunities to compare multiple strategies is recommended by a range of mathematics policy documents, as research has shown this approach promotes flexibility and enhances conceptual knowledge and procedural fluency. More specifically, the approach allows students to compare the effectiveness and efficiency of mathematical arguments in the context of problem solving. An initial pilot study on non-animated contrasting cases in geometry shows promise for the general approach and suggests that animating the cases has the potential for stronger student learning gains. This study will examine the extent to which the animated cases improve students' conceptual and procedural knowledge of geometry and identify factors that relate to changes in knowledge. The project team will develop 24 worked example contrasting cases based on design principles from the prior work in algebra. The materials will be implemented in four treatment classrooms in the first cycle, revised, and then implemented in eight treatment classrooms. Students' written work will be collected along with data on the nature of the classroom discussions and small-group interviews with students. Teachers' perspectives on lessons will also be collected to support revision and strengthening of the materials. Assessments of students' geometry knowledge will be developed using measures with demonstrated validity and reliability to measure changes in student learning.

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.

Teacher Professional Learning to Support Student Motivational Competencies During Science Instruction (Collaborative Research: Linnenbrink-Garcia)

This project will bring together a multi-disciplinary team of researchers and science teachers to identify a set of practices that science teachers can readily incorporate into their planning and instruction. The project will design, develop, and test a research-based professional learning approach to help middle school science teachers effectively support and sustain student motivational competencies during science instruction.

Lead Organization(s): 
Award Number: 
1813047
Funding Period: 
Sat, 09/01/2018 to Wed, 08/31/2022
Full Description: 

Science teachers identify fostering student motivation to learn as a pressing need, yet teacher professional learning programs rarely devote time to helping teachers understand and apply motivational principles in their instruction. This project will bring together a multi-disciplinary team of researchers and science teachers to identify a set of practices that science teachers can readily incorporate into their planning and instruction. The project will design, develop, and test a research-based professional learning approach to help middle school science teachers effectively support and sustain student motivational competencies during science instruction. The approach will include use of materials addressing student motivational processes and how to support them, evaluation tools to measure student motivational competencies, lesson planning tools, and instruments for teacher self-evaluation. The translation to practice will include recognition of student diversity and consider ways to facilitate context-specific integration of disciplinary and motivational knowledge in practice. The project will focus on middle school science classrooms because this period is an important motivational bridge between elementary and secondary science learning. This project will enhance understanding of teacher pedagogical content knowledge (PCK) in that it frames knowledge about supporting motivational competencies in science as PCK rather than general pedagogical knowledge.

This early stage design and development project will iteratively develop and study a model of teacher professional learning that will help middle school science teachers create, modify, and implement instruction that integrates support for students' motivational competencies with the science practices, crosscutting concepts, and disciplinary core ideas specified in science curriculum standards. A design-based research approach will be used to develop and test four resources teachers will use to explicitly include attention to student motivational competencies in their lesson planning efforts. The resources will include: 1) educational materials about students' motivational processes with concrete examples of how to support them; 2) easy-to-implement student evaluation tools for teachers to gauge students' motivational competencies; 3) planning tools to incorporate motivational practices into science lesson planning; and 4) instruments for teacher self-evaluation. A collaborative group of educational researchers will partner with science teachers from multiple school districts having diverse student populations to jointly develop the professional learning approach and resources. This project will contribute to systemic change by moving motivational processes from an implicit element of educating students, to an explicit and intentional set of strategies teachers can enact. Research questions will focus on how teachers respond to the newly developed professional learning model, and how students respond to instruction developed through implementing the model.

Translating a Video-based Model of Teacher Professional Development to an Online Environment

This project will adapt an effective in-person teacher professional development model to an online approach. A defining feature of the Science Teachers Learning from Lesson Analysis (STeLLA) Professional Development program is its use of videos of classroom instruction and examples of student work to promote teacher learning. Adapting the STeLLA program to an online learning model can reach a broader and more diverse audience, such as teachers working in rural school districts and underserved communities.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
1813127
Funding Period: 
Sat, 09/01/2018 to Tue, 08/31/2021
Full Description: 

Improving the quality of teaching is essential to improving student outcomes. But what are the most effective ways to support teachers' professional development?  BSCS Science Learning and the University of Minnesota STEM Education Program Area explore this question by adapting an effective teacher professional development model -- that meets face-to-face in real-time -- to an online approach. A defining feature of the Science Teachers Learning from Lesson Analysis (STeLLA) Professional Development program is its use of videos of classroom instruction and examples of student work to promote teacher learning. Skilled facilitators guide teachers' analysis and discussion of other teachers' work; then, teachers begin to apply the analytical techniques they have learned to their own teaching. Adapting the STeLLA program to an online learning model is important because it can reach a broader and more diverse audience such as teachers working in rural school districts and underserved communities. To further promote the reach of STeLLA, the online version of STeLLA will engage and prepare teacher leaders to support their peers' engagement and understanding.

Guided by theories of situated cognition and cognitive apprenticeship this project focuses on two questions: How can the STeLLA professional development model be adapted to an online environment? and Does participation in the online model show meaningful teacher and student outcomes related to science teaching and learning? Challenges related to adaptation include understanding the duration and intensity of teacher engagement, the quality of their science content learning experiences, and how teacher learning is scaffolded across the online and traditional model. The project will unfold in two phases. Phase 1 uses a design-based research approach to rapidly enact, test, and revise online program components while remaining true to the design principles underlying the traditional STeLLA PD program. Phase 2 uses a quasi-experimental approach to test STeLLA Online's influence on teacher content knowledge, pedagogical content knowledge, practice and on upper elementary student science achievement. Comparisons will be made between STeLLA Online, face-to-face STeLLA, and a traditional professional development program that emphasizes deepening content knowledge only. This comparison leverages data from a previously-completed cluster randomized trial of STeLLA funded by the NSF.

Supporting Teachers in Responsive Instruction for Developing Expertise in Science (Collaborative Research: Linn)

This project takes advantage of advanced technologies to support science teachers to rapidly respond to diverse student ideas in their classrooms. Students will use web-based curriculum units to engage with models, simulations, and virtual experiments to write multiple explanations for standards-based science topics. The project will also design planning tools for teachers that will make suggestions relevant research-proven instructional strategies based on the real-time analysis of student responses.

Partner Organization(s): 
Award Number: 
1813713
Funding Period: 
Sat, 09/01/2018 to Wed, 08/31/2022
Full Description: 

Many teachers want to adapt their instruction to meet student learning needs, yet lack the time to regularly assess and analyze students' developing understandings. The Supporting Teachers in Responsive Instruction for Developing Expertise in Science (STRIDES) project takes advantage of advanced technologies to support science teachers to rapidly respond to diverse student ideas in their classrooms. In this project students will use web-based curriculum units to engage with models, simulations, and virtual experiments to write multiple explanations for standards-based science topics. Advanced technologies (including natural language processing) will be used to assess students' written responses and summaries their science understanding in real-time. The project will also design planning tools for teachers that will make suggestions relevant research-proven instructional strategies based on the real-time analysis of student responses. Research will examine how teachers make use of the feedback and suggestions to customize their instruction. Further we will study how these instructional changes help students develop coherent understanding of complex science topics and ability to make sense of models and graphs. The findings will be used to refine the tools that analyze the student essays and generate the summaries; improve the research-based instructional suggestions in the planning tool; and strengthen the online interface for teachers. The tools will be incorporated into open-source, freely available online curriculum units. STRIDES will directly benefit up to 30 teachers and 24,000 students from diverse school settings over four years.

Leveraging advances in natural language processing methods, the project will analyze student written explanations to provide fine-grained summaries to teachers about strengths and weaknesses in student work. Based on the linguistic analysis and logs of student navigation, the project will then provide instructional customizations based on learning science research, and study how teachers use them to improve student progress. Researchers will annually conduct at least 10 design or comparison studies, each involving up to 6 teachers and 300-600 students per year. Insights from this research will be captured in automated scoring algorithms, empirically tested and refined customization activities, and data logging techniques that can be used by other research and curriculum design programs to enable teacher customization.

Project Videos

2020 STEM for All Video Showcase

Title: STRIDES: Customizing Online Curricula for Distance Learning

Presenter(s): Libby Gerard, Sarah Bichler, Phillip Boda, Allison Bradford, Emily Harrison, Jennifer King Chen, Jonathan Lim-Breitbart, Marcia Linn, & Korah Wiley

Building Middle School Students' Understanding of Heredity and Evolution

This project will develop and test the impact of heredity and evolution curriculum units for middle school grades that are aligned with the Next Generation Science Standards (NGSS). The project will advance science teaching by investigating the ways in which two curriculum units can be designed to incorporate science and engineering practices, cross-cutting concepts, and disciplinary core ideas, the three dimensions of science learning described by the NGSS. The project will also develop resources to support teachers in implementation of the new modules.

Lead Organization(s): 
Award Number: 
1814194
Funding Period: 
Sat, 09/01/2018 to Wed, 08/31/2022
Full Description: 

This project will develop and test the impact of heredity and evolution curriculum units for middle school grades that are aligned with the Next Generation Science Standards (NGSS). The project will advance science teaching by investigating the ways in which two curriculum units can be designed to incorporate science and engineering practices, cross-cutting concepts, and disciplinary core ideas, the three dimensions of science learning described by the NGSS. The project will also develop resources to support teachers in implementation of the new modules. The planned research will also examine whether student understanding of evolution depends on the length and time of exposure to learning about heredity prior to learning about evolution.

This Early Stage Design and Development project will develop two new 3-week middle school curriculum units, with one focusing on heredity and the other focusing on evolution. The units will include embedded formative and summative assessment measures and online teacher support materials. These units will be developed as part of a curriculum learning progression that will eventually span the elementary grades through high school. This curriculum learning progression will integrate heredity, evolution, data analysis, construction of scientific explanations, evidence-based argumentation, pattern recognition, and inferring cause and effect relationships. To inform development and iterative revisions of the units, the project will conduct nation-wide beta and pilot tests, selecting schools with broad ranges of student demographics and geographical locations. The project will include three rounds of testing and revision of both the student curriculum and teacher materials. The project will also investigate student understanding of evolution in terms of how their understanding is impacted by conceptual understanding of heredity. The research to be conducted by this project is organized around three broad research questions: (a) In what ways can two curriculum units be designed to incorporate the three dimensions of science learning and educative teacher supports to guide students' conceptual understanding of heredity and evolution? (b) To what extent does student understanding of evolution depend on the length and timing of heredity lessons that preceded an evolution unit? And (c) In what ways do students learn heredity and evolution?

Supporting Teachers in Responsive Instruction for Developing Expertise in Science (Collaborative Research: Riordan)

This project takes advantage of advanced technologies to support science teachers to rapidly respond to diverse student ideas in their classrooms. Students will use web-based curriculum units to engage with models, simulations, and virtual experiments to write multiple explanations for standards-based science topics. The project will also design planning tools for teachers that will make suggestions relevant research-proven instructional strategies based on the real-time analysis of student responses.

Lead Organization(s): 
Award Number: 
1812660
Funding Period: 
Sat, 09/01/2018 to Wed, 08/31/2022
Full Description: 

Many teachers want to adapt their instruction to meet student learning needs, yet lack the time to regularly assess and analyze students' developing understandings. The Supporting Teachers in Responsive Instruction for Developing Expertise in Science (STRIDES) project takes advantage of advanced technologies to support science teachers to rapidly respond to diverse student ideas in their classrooms. In this project students will use web-based curriculum units to engage with models, simulations, and virtual experiments to write multiple explanations for standards-based science topics. Advanced technologies (including natural language processing) will be used to assess students' written responses and summaries their science understanding in real-time. The project will also design planning tools for teachers that will make suggestions relevant research-proven instructional strategies based on the real-time analysis of student responses. Research will examine how teachers make use of the feedback and suggestions to customize their instruction. Further we will study how these instructional changes help students develop coherent understanding of complex science topics and ability to make sense of models and graphs. The findings will be used to refine the tools that analyze the student essays and generate the summaries; improve the research-based instructional suggestions in the planning tool; and strengthen the online interface for teachers. The tools will be incorporated into open-source, freely available online curriculum units. STRIDES will directly benefit up to 30 teachers and 24,000 students from diverse school settings over four years.

Leveraging advances in natural language processing methods, the project will analyze student written explanations to provide fine-grained summaries to teachers about strengths and weaknesses in student work. Based on the linguistic analysis and logs of student navigation, the project will then provide instructional customizations based on learning science research, and study how teachers use them to improve student progress. Researchers will annually conduct at least 10 design or comparison studies, each involving up to 6 teachers and 300-600 students per year. Insights from this research will be captured in automated scoring algorithms, empirically tested and refined customization activities, and data logging techniques that can be used by other research and curriculum design programs to enable teacher customization.

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