Middle School

Supporting Teacher Customizations of Curriculum Materials for Equitable Student Sensemaking in Secondary Science (Collaborative Researcher: McNeill)

This project is developing and researching customization tools to support teachers’ instructional shifts to achieve equitable sensemaking in middle school science classrooms. These tools will help teachers to better notice and leverage the ideas and experiences of non-dominant students to support all students in equitable sensemaking.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2101384
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

This project is developing and researching tools to support teachers’ instructional shifts to achieve equitable sensemaking in middle school science classrooms. Sensemaking involves students building and using science ideas to address questions and problems they identify, rather than solely learning about the science others have done. Despite it being a central goal of recent national policy documents, such meaningful engagement with science knowledge building remains elusive in many classrooms. Students from non-dominant communities frequently do not see themselves as “science people” because their ways of knowing and experiences are often not valued in science classrooms. Professional learning grounded in teachers’ use of innovative high quality curriculum materials can help teachers learn to teach in new ways. Yet teachers need guidance to customize curriculum materials to fit their own local contexts and leverage students’ ideas and experiences while maintaining the goals of recent policy documents. This project is researching and developing customization tools to support teachers in their principled use and adaptation of materials for their classrooms. These customization tools will help teachers to better notice and leverage the ideas and experiences of non-dominant students to support all students in equitable sensemaking. During the project, 74 teachers from diverse schools will participate in professional learning using these customization tools. After testing, the customization tools and illustrative cases will be disseminated broadly to support teachers enacting any science curriculum in leveraging the ideas and experiences that students bring into the classroom. In addition, the research results in the form of design principles will inform future design of curriculum materials and professional learning resources for science.

A key element in science education reform efforts includes shifting the epistemic and power structures in the classroom so that teachers and students work together to build knowledge. Research shows that shifts in science teaching are challenging for teachers. Researchers and practitioners have collaborated to develop curriculum materials that begin to support teachers in this work. But teachers need to interpret these materials and customize the tasks and strategies for their own context as they work with their own students. Curriculum enactment is not prescriptive, but rather a “participatory relationship” between the teacher, curriculum materials, students and context, where teachers interpret the materials and the goals of the reform, and customize them to adapt the tasks and activity structures to meet the needs and leverage the resources of their students. The field needs to better understand how teachers learn from and navigate this participatory relationship and what supports can aid in this work. This project will include design-based research examining teachers’ customization processes and the development of tools to support teachers in adapting curriculum materials for their specific school context to facilitate equitable science sensemaking for all students, where all students engage in ambitious science knowledge building. The major components of the research program will include: (1) Empirical study of teachers’ customization processes; (2) Theoretical model of teacher thinking and learning that underlies customization of curriculum materials; (3) Tools to support principled customization consistent with the goals of the reform; and (4) Empirical study of how tools influence teachers’ customization processes. The project is addressing the urgent need for scalable support for teacher learning for recent shifts in science education in relation to both a vision of figuring out and equity.

Dimensions of Success: Transforming Quality Assessment in Middle School Science and Engineering

This project represents a new approach to quality assessment of K-12 science and engineering learning experiences. By updating and expanding the Dimensions of Success (DoS) observation tool initially established for informal science learning settings to middle school science and engineering classrooms (DoS-MSSE), the project will create and implement a sustainable and scalable system of support for teachers who are learning how to implement the Next Generation Science Standards (NGSS) Framework for K-12 effectively and equitably.

Lead Organization(s): 
Award Number: 
2101554
Funding Period: 
Sat, 05/15/2021 to Wed, 04/30/2025
Full Description: 

This project represents a new approach to quality assessment of K-12 science and engineering learning experiences. By updating and expanding the Dimensions of Success (DoS) observation tool initially established for informal science learning settings to middle school science and engineering classrooms (DoS-MSSE), the project will create and implement a sustainable and scalable system of support for teachers who are learning how to implement the Next Generation Science Standards (NGSS) Framework for K-12 effectively and equitably. The project’s goals are as follows. (1) Develop and test the DoS-MSSE observation tool, including alignment to the NGSS and equity, to ensure scores are valid and reliable across all dimensions. (2) Establish a video scoring method to increase access to continuous improvement systems of support. (3) Create profiles of STEM quality for schools and districts to inform policy decisions, professional development opportunities, practice guidelines, and other efforts. (4) Develop and implement a training program to certify teachers and staff in the use of the tool and provide professional development. Extending DoS to middle schools will support and advancing educational practice by identifying schools’ strengths and challenges in science and engineering learning, making equity more concrete, and enhancing school and teacher capacity through established DoS systems of support. The tool will be developed to assess learning experiences for quality improvement, not used for accountability or comparison. DoS-MSSE will also support research and evaluation by providing a validated quality assessment tool, specific to middle school science and engineering, that is flexible and can be applied to a variety of proposals and projects, enhancing research infrastructure. Finally, it will improve the STEM education field by providing stakeholders with “quality profiles” to guide policy and approaches. By promoting equitable, high-quality science and engineering learning inside and outside of school, the expanded DoS framework will strengthen efforts across sectors and help communities provide the inspiration, knowledge, and skills youth need to thrive in the workforce and in life.

Over four years, this project will transform the DoS framework to address multiple educational priorities for formal middle school settings by: (1) creating a new domain that aligns to science and engineering practices, disciplinary core ideas, and cross-cutting concepts from the NGSS/Framework for K-12; (2) identifying observable and measurable diversity, equity, inclusion, and access practices (and related indicators, including social-emotional learning and development) in the context of science and engineering in classrooms, and further revising rubric criteria. The project will build a validity argument for DoS-MSSE using established methods for observation protocols, and analyze the psychometric properties of all dimensions and domains using item-response theory (IRT) methods (e.g., Many-Faceted Rasch Measurement, to model the data which will allow for estimation of teachers’ effectiveness, rater severity, and the difficulty of each dimension). The rubrics will be informed by content experts and pilot observations; scores will be analyzed across dimensions, observers, disciplinary domains, and time; and scores will be compared to other data, including student and teacher self-report and observation scores collected with other established measures. The project will culminate in a larger-scale validation study, collecting observational and survey data from three geographically different school districts (N=30 schools). This effort will characterize the strength of evidence for indicators of classroom quality and provide data to identify support needs across districts, schools, and teachers. Given the ongoing need for remote learning, and the general need to increase school capacity for non-punitive assessment, the tool will be expanded to support both live and recorded modes of data collection, establishing a video scoring method. A training and certification system will be field-tested in the fourth year of the project to assure accessibility, scalability, and sustainability.

Connecting Elementary Mathematics Teaching to Real-World Issues (Collaborative Research: Felton)

This project will engage students and teachers in rich, real-world math tasks; will support future teachers and mathematics educators in adapting, designing, and implementing similar tasks; and will provide a basis for further research on the most effective ways to design and implement real-world tasks in the mathematics classroom.

Lead Organization(s): 
Award Number: 
2101456
Funding Period: 
Thu, 07/01/2021 to Sun, 06/30/2024
Full Description: 

There are long-standing calls to make mathematics more meaningful, relevant, and applicable both inside and outside of the K-12 classroom. In particular, there is a growing recognition that mathematics is a valuable tool for helping students understand important real-world issues that affect their lives and society. Further, mathematics can support students in becoming mathematically literate and engaged democratic citizens. Despite the increased interest in connecting mathematics to real-world issues in the classroom, many teachers feel unprepared to do so. This project will engage students and teachers in rich, real-world math tasks; will support future teachers and mathematics educators in adapting, designing, and implementing similar tasks; and will provide a basis for further research on the most effective ways to design and implement real-world tasks in the mathematics classroom.

The three goals of the Connecting Elementary Mathematics to the World project are: (1) To explore how mathematics teachers adapt, design, and enact tasks that connect mathematics to the real world. We will study the teaching practices of the project team as they engage in this work in two summer camps and in elementary classrooms at two sites. (2) To develop a collection of exemplar tasks and rich records of practice for each task. These records of practice will detail the mathematical and real-world learning goals, background knowledge needed for both goals, common student responses, and videos or vignettes of the task in progress. A team of six teachers at two sites will be recruited to collaborate with the team throughout the project. Teachers will provide input and feedback on the design of, appropriateness of, and relevance of the tasks and the support materials needed to implement the real-world tasks. Initial tasks will be field tested with elementary students and additional tasks will be developed for subsequent week-long summer camps and for teaching in elementary classrooms. (3) To research both the development and enactment of these tasks. We will develop a theoretical framework for creating and implementing real-world tasks that can inform future practice and research in this area. The research products of this project will result in (a) an understanding of effective teaching and design practices for connecting mathematics to real-world issues, (b) a theoretical framework of how these practices are interconnected, and (c) how these practices differ from practices when teaching typical school mathematics tasks.

Connecting Elementary Mathematics Teaching to Real-World Issues (Collaborative Research: Thanheiser)

This project will engage students and teachers in rich, real-world math tasks; will support future teachers and mathematics educators in adapting, designing, and implementing similar tasks; and will provide a basis for further research on the most effective ways to design and implement real-world tasks in the mathematics classroom.

Lead Organization(s): 
Award Number: 
2101463
Funding Period: 
Thu, 07/01/2021 to Sun, 06/30/2024
Full Description: 

There are long-standing calls to make mathematics more meaningful, relevant, and applicable both inside and outside of the K-12 classroom. In particular, there is a growing recognition that mathematics is a valuable tool for helping students understand important real-world issues that affect their lives and society. Further, mathematics can support students in becoming mathematically literate and engaged democratic citizens. Despite the increased interest in connecting mathematics to real-world issues in the classroom, many teachers feel unprepared to do so. This project will engage students and teachers in rich, real-world math tasks; will support future teachers and mathematics educators in adapting, designing, and implementing similar tasks; and will provide a basis for further research on the most effective ways to design and implement real-world tasks in the mathematics classroom.

The three goals of the Connecting Elementary Mathematics to the World project are: (1) To explore how mathematics teachers adapt, design, and enact tasks that connect mathematics to the real world. We will study the teaching practices of the project team as they engage in this work in two summer camps and in elementary classrooms at two sites. (2) To develop a collection of exemplar tasks and rich records of practice for each task. These records of practice will detail the mathematical and real-world learning goals, background knowledge needed for both goals, common student responses, and videos or vignettes of the task in progress. A team of six teachers at two sites will be recruited to collaborate with the team throughout the project. Teachers will provide input and feedback on the design of, appropriateness of, and relevance of the tasks and the support materials needed to implement the real-world tasks. Initial tasks will be field tested with elementary students and additional tasks will be developed for subsequent week-long summer camps and for teaching in elementary classrooms. (3) To research both the development and enactment of these tasks. We will develop a theoretical framework for creating and implementing real-world tasks that can inform future practice and research in this area. The research products of this project will result in (a) an understanding of effective teaching and design practices for connecting mathematics to real-world issues, (b) a theoretical framework of how these practices are interconnected, and (c) how these practices differ from practices when teaching typical school mathematics tasks.

Supporting Instructional Decision Making: The Potential of Automatically Scored Three-Dimensional Assessment System (Collaborative Research: Krajcik)

This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.

Lead Organization(s): 
Award Number: 
2100964
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems. Led by collaborators from University of Georgia, Michigan State University, University of Illinois at Chicago, and WestEd, the project team will develop computer scoring algorithms, a suite of AutoRs, and an array of pedagogical content knowledge supports (PCKSs). These products will assist middle school science teachers in the use of 3D assessments, making informative instructional changes, and improve students’ 3D learning. The project will generate knowledge about teachers’ uses of 3D assessments and examine the potential of automatically scored 3D assessments.
 
The project will achieve the research goals using a mixed-methods design in three phases. Phase I: Develop AutoRs. Machine scoring models for the 3D assessment tasks will be developed using existing data. To support teachers’ interpretation and use of automatic scores, the project team will develop AutoRs and examine how teachers make use of these initial reports. Based on observations and feedback from teachers, AutoRs will be refined using an iterative procedure so that teachers can use them with more efficiency and productivity. Phase II: Develop and test PCKSs. Findings from Phase I, the literature, and interviews with experienced teachers will be employed to develop PCKSs. The project will provide professional learning with teachers on how to use the AutoRs and PCKSs. The project will research how teachers use AutoRs and PCKSs to make instructional decisions. The findings will be used to refine the PCKSs. Phase III: Classroom implementation. In this phase a study will be conducted with a new group of teachers to explore the effectiveness and usability of AutoRs and PCKSs in terms of supporting teachers’ instructional decisions and students’ 3D learning. This project will create knowledge about and formulate a theory of how teachers interpret and attend to students’ performance on 3D assessments, providing critical information on how to support teachers’ responsive instructional decision making. The collaborative team will widely disseminate various products, such as 3D assessment scoring algorithms, AutoRs, PCKSs, and the corresponding professional development programs, and publications to facilitate 3D instruction and learning.

Supporting Instructional Decision Making: The Potential of Automatically Scored Three-Dimensional Assessment System (Collaborative Research: Zhai)

This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.

Lead Organization(s): 
Award Number: 
2101104
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems. Led by collaborators from University of Georgia, Michigan State University, University of Illinois at Chicago, and WestEd, the project team will develop computer scoring algorithms, a suite of AutoRs, and an array of pedagogical content knowledge supports (PCKSs). These products will assist middle school science teachers in the use of 3D assessments, making informative instructional changes, and improve students’ 3D learning. The project will generate knowledge about teachers’ uses of 3D assessments and examine the potential of automatically scored 3D assessments.
 
The project will achieve the research goals using a mixed-methods design in three phases. Phase I: Develop AutoRs. Machine scoring models for the 3D assessment tasks will be developed using existing data. To support teachers’ interpretation and use of automatic scores, the project team will develop AutoRs and examine how teachers make use of these initial reports. Based on observations and feedback from teachers, AutoRs will be refined using an iterative procedure so that teachers can use them with more efficiency and productivity. Phase II: Develop and test PCKSs. Findings from Phase I, the literature, and interviews with experienced teachers will be employed to develop PCKSs. The project will provide professional learning with teachers on how to use the AutoRs and PCKSs. The project will research how teachers use AutoRs and PCKSs to make instructional decisions. The findings will be used to refine the PCKSs. Phase III: Classroom implementation. In this phase a study will be conducted with a new group of teachers to explore the effectiveness and usability of AutoRs and PCKSs in terms of supporting teachers’ instructional decisions and students’ 3D learning. This project will create knowledge about and formulate a theory of how teachers interpret and attend to students’ performance on 3D assessments, providing critical information on how to support teachers’ responsive instructional decision making. The collaborative team will widely disseminate various products, such as 3D assessment scoring algorithms, AutoRs, PCKSs, and the corresponding professional development programs, and publications to facilitate 3D instruction and learning.

Supporting Instructional Decision Making: The Potential of Automatically Scored Three-Dimensional Assessment System (Collaborative Research: Weiser)

This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.

Lead Organization(s): 
Award Number: 
2101112
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems. Led by collaborators from University of Georgia, Michigan State University, University of Illinois at Chicago, and WestEd, the project team will develop computer scoring algorithms, a suite of AutoRs, and an array of pedagogical content knowledge supports (PCKSs). These products will assist middle school science teachers in the use of 3D assessments, making informative instructional changes, and improve students’ 3D learning. The project will generate knowledge about teachers’ uses of 3D assessments and examine the potential of automatically scored 3D assessments.
 
The project will achieve the research goals using a mixed-methods design in three phases. Phase I: Develop AutoRs. Machine scoring models for the 3D assessment tasks will be developed using existing data. To support teachers’ interpretation and use of automatic scores, the project team will develop AutoRs and examine how teachers make use of these initial reports. Based on observations and feedback from teachers, AutoRs will be refined using an iterative procedure so that teachers can use them with more efficiency and productivity. Phase II: Develop and test PCKSs. Findings from Phase I, the literature, and interviews with experienced teachers will be employed to develop PCKSs. The project will provide professional learning with teachers on how to use the AutoRs and PCKSs. The project will research how teachers use AutoRs and PCKSs to make instructional decisions. The findings will be used to refine the PCKSs. Phase III: Classroom implementation. In this phase a study will be conducted with a new group of teachers to explore the effectiveness and usability of AutoRs and PCKSs in terms of supporting teachers’ instructional decisions and students’ 3D learning. This project will create knowledge about and formulate a theory of how teachers interpret and attend to students’ performance on 3D assessments, providing critical information on how to support teachers’ responsive instructional decision making. The collaborative team will widely disseminate various products, such as 3D assessment scoring algorithms, AutoRs, PCKSs, and the corresponding professional development programs, and publications to facilitate 3D instruction and learning.

Supporting Instructional Decision Making: The Potential of Automatically Scored Three-Dimensional Assessment System (Collaborative Research: Yin)

This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.

Award Number: 
2101166
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems. Led by collaborators from University of Georgia, Michigan State University, University of Illinois at Chicago, and WestEd, the project team will develop computer scoring algorithms, a suite of AutoRs, and an array of pedagogical content knowledge supports (PCKSs). These products will assist middle school science teachers in the use of 3D assessments, making informative instructional changes, and improve students’ 3D learning. The project will generate knowledge about teachers’ uses of 3D assessments and examine the potential of automatically scored 3D assessments.
 
The project will achieve the research goals using a mixed-methods design in three phases. Phase I: Develop AutoRs. Machine scoring models for the 3D assessment tasks will be developed using existing data. To support teachers’ interpretation and use of automatic scores, the project team will develop AutoRs and examine how teachers make use of these initial reports. Based on observations and feedback from teachers, AutoRs will be refined using an iterative procedure so that teachers can use them with more efficiency and productivity. Phase II: Develop and test PCKSs. Findings from Phase I, the literature, and interviews with experienced teachers will be employed to develop PCKSs. The project will provide professional learning with teachers on how to use the AutoRs and PCKSs. The project will research how teachers use AutoRs and PCKSs to make instructional decisions. The findings will be used to refine the PCKSs. Phase III: Classroom implementation. In this phase a study will be conducted with a new group of teachers to explore the effectiveness and usability of AutoRs and PCKSs in terms of supporting teachers’ instructional decisions and students’ 3D learning. This project will create knowledge about and formulate a theory of how teachers interpret and attend to students’ performance on 3D assessments, providing critical information on how to support teachers’ responsive instructional decision making. The collaborative team will widely disseminate various products, such as 3D assessment scoring algorithms, AutoRs, PCKSs, and the corresponding professional development programs, and publications to facilitate 3D instruction and learning.

Crowd-Sourced Online Nexus for Developing Assessments of Middle-School Physical Science Disciplinary Core Ideas

This project will develop and test a web-based platform to increase the quality of teacher-administered tests in science classrooms. It draws on classroom teacher knowledge while employing the rigorous statistical methods used in standardized assessment creation and validation. The content focus is on the disciplinary core ideas for grades 6-8 physical science in the Next Generation Science Standards (NGSS).

Lead Organization(s): 
Award Number: 
2101493
Funding Period: 
Wed, 09/01/2021 to Sat, 08/31/2024
Full Description: 

This project will develop and test a web-based platform to increase the quality of teacher-administered tests in science classrooms. It draws on classroom teacher knowledge while employing the rigorous statistical methods used in standardized assessment creation and validation. The content focus is on the disciplinary core ideas for grades 6-8 physical science in the Next Generation Science Standards (NGSS). Teachers now spend an estimate 20% of their time in assessment, yet have relatively few tools to draw upon when creating them. Over time, they learn to adapt items from available curriculum materials and textbooks. On the other hand, standardized assessment developers have the benefit of expert item writers, long development cycles, a large and diverse student population, and sophisticated psychometric tools. This project combines these two approaches, drawing upon teachers to contribute their best items, then immediately piloting them using crowdsourced subjects. Psychometric analysis generates measures of item quality and then “recycles” items to participating teachers for improvement. In this way, a large test item bank will be constructed utilizing teacher input with each item possessing: appropriate reading levels, NGSS alignment, scientific accuracy, appropriate difficulty, high statistical discrimination, and negligible difference by gender, race, or ethnicity. Involvement in this project has potential benefits for teachers lacking formal training in assessment, familiarizing participants with the NGSS, and with the elements of high-quality test development.

The project will gauge the merits of a novel collaborative system for the development and validation of high-quality test items and assessment instruments. It will measure the degree to which teachers can generate effective items and improve existing items exhibiting problematic issues when given the guidance of rigorous psychometric measures that estimate item quality. It will build on earlier research showing that an adult, crowd-sourced sample works well as an initial proxy for grade 6-8 science students, allowing for extremely rapid feedback on item quality (often overnight), with item response theory computation used to establish item difficulty, item discrimination, guessing levels, and differential item functioning (gender and racial/ethnicity bias). In addition, computed measures of misconception strength, scientific correctness, reading level, and match to the NGSS will help to guide revision by teachers. Use of Bayesian futility analysis will “triage” items, minimizing costly testing of items when deemed unlikely to meet item quality criteria, lowering costs. Field testing with a large sample of grade 6-8 students will provide a final check on item quality. Items will be developed much more inexpensively than by methods used for standardized test development. Two pairs (public-release and secure for chemistry and physics) of assessment instruments will be constructed and be freely available to science teachers for classroom use and by education researchers and curriculum developers. A system that provides quick feedback on item quality could potentially transform university instruction and professional development opportunities in assessment. While starting with selected response (multiple-choice) items, the project will be able to implement a larger variety of formats in the future, incorporating automated approaches as they become available.

Supporting Teachers to Teach Mathematics through Problem Posing

This project aims to support teachers to engage their students in mathematical problem posing (problem-posing-based learning, or P-PBL). P-PBL is a powerful approach to the teaching and learning of mathematics, and provides students with opportunities to engage in authentic mathematical practices.

Lead Organization(s): 
Award Number: 
2101552
Funding Period: 
Sun, 08/01/2021 to Thu, 07/31/2025
Full Description: 

This project aims to support teachers to engage their students in mathematical problem posing (problem-posing-based learning, or P-PBL). P-PBL is a powerful approach to the teaching and learning of mathematics, and provides students with opportunities to engage in authentic mathematical practices. For example, conjecturing in mathematics, a form of problem posing, often plays an important role in solving complex problems, and problem posing is an important component of mathematical modeling. Yet despite its importance, widely used curriculum materials fail to incorporate P-PBL in substantial and consistent ways, leaving teachers with few resources to enact this process. This project will develop problem-posing lessons and illustrative cases of teachers implementing P-PBL that will not only support teachers to develop a vision of what P-PBL looks like and how to implement it in their own classrooms, but will also serve as rich resources for professional development (PD) providers. This project will generate valuable findings about teaching using problem posing for district administrators, mathematics teachers, educators, and researchers as well as curriculum developers and policy makers. The team will develop and pilot a set of 20−30 research-based P-PBL cases that provide critical details for the implementation of P-PBL and reveal “lessons learned” from the development process.

The project promises broader impact on the field of mathematics education as the first goal is to support teachers to teach mathematics through engaging their students in mathematical problem posing. By guiding students to construct and investigate their own problems, P-PBL both helps to create mathematical learning opportunities and develops students’ mathematical agency and positive mathematical identities. A networked improvement community of teachers and researchers will integrate problem posing into daily mathematics instruction and continuously improve the quality of P-PBL through iterative task and lesson design. The intellectual merit of this project is its contribution of new and important insights about teaching mathematics through problem posing. This will be realized through the second project goal which is to longitudinally investigate the promise of supporting teachers to teach with P-PBL for enhancing teachers’ instructional practice and students’ learning. A quasi-experimental design coupled with design-based research methodology and improvement science will be used to understand how, when, and why P-PBL works in practice. Specifically, we plan to follow a sample of 36 teachers and their approximately 3,600 students from six middle schools for multiple years to longitudinally explore the promise of P-PBL for developing teachers’ beliefs about problem posing, their beliefs about P-PBL, and their actual instructional practice. We will also investigate students’ learning as measured by problem-posing performance, problem-solving performance, and mathematics disposition. The findings of the project will add not only to the field’s understanding of the promise of supporting teachers to integrate P-PBL into their mathematics instruction, but also to its understanding of the challenges that teachers face when engaging in a networked improvement community that is focused on improving tasks and lessons by integrating P-PBL.

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