Students

Building a Flexible and Comprehensive Approach to Supporting Student Development of Whole Number Understanding

The purpose of this project is to develop and conduct initial studies of a multi-grade program targeting critical early math concepts. The project is designed to address equitable access to mathematics and STEM learning for all students, including those with or at-risk for learning disabilities and underrepresented groups.

Lead Organization(s): 
Award Number: 
2101308
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

A critical goal for the nation is ensuring all students have a successful start in learning mathematics. While strides have been made in supporting at-risk students in mathematics, significant challenges still exist. These challenges include enabling access to and learning of advanced mathematics content, ensuring that learning gains don’t fade over time, and providing greater support to students with the most severe learning needs. One way to address these challenges is through the use of mathematics programs designed to span multiple grades. The purpose of this project is to develop and conduct initial studies of a multi-grade program targeting critical early math concepts. The project is designed to address equitable access to mathematics and STEM learning for all students, including those with or at-risk for learning disabilities and underrepresented groups.

The three aims of the project are to: (1) develop a set of 10 Bridging Lessons designed to link existing kindergarten and first grade intervention programs (2) develop a second grade intervention program that in combination with the kindergarten and first grade programs will promote a coherent sequence of whole number concepts, skills, and operations across kindergarten to second grade; and (3) conduct a pilot study of the second grade program examining initial promise to improve student mathematics achievement. To accomplish these goals multiple methods will be used including iterative design and development process and the use of a randomized control trial to study potential impact on student math learning. Study participants include approximately 220 kindergarten through second grade students from 8 schools across three districts. Study measures include teacher surveys, direct observations, and student math outcome measures. The project addresses the need for research developed intervention programs focused on advanced whole number content. The work is intended to support schools in designing and deploying math interventions to provide support to students both within and across the early elementary grades as they encounter and engage with critical mathematics content.

Learning about Viral Epidemics through Engagement with Different Types of Models

The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models.

Award Number: 
2101083
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

The project will develop new curriculum and use it to research how high school students learn about viral epidemics while developing competencies for scientific modeling. The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models. This project will address the gap by studying student learning with different types of models and will use these findings to develop and study new curriculum materials that incorporate multiple models for teaching about viral epidemics in high school biology classes. COVID-19 caused devasting impacts, and marginalized groups including the Latinx community suffered disproportionately negative outcomes. The project will directly recruit Latinx students to ensure that design products are culturally responsive and account for Latinx learner needs. The project will create new pathways for engaging Latinx students in innovative, model-based curriculum about critically important issues. Project research and resources will be widely shared via publications, conference presentations, and professional development opportunities for teachers.

The project will research three aspects of student learning: a) conceptual understandings about viral epidemics, b) epistemic understandings associated with modeling, and c) model-informed reasoning about viral epidemics and potential solutions. The research will be conducted in three phases. Phase 1 will explore how students make sense of viral epidemics through different types of models. This research will be conducted with small groups of students as they work through learning activities and discourse opportunities associated with viral epidemic models. Phase 2 will research how opportunities to engage in modeling across different types of models should be supported and sequenced for learning about viral epidemics. These findings will make it possible to revise the learning performance which will be used to develop a curricular module for high school biology classes. Phase 3 will study the extent to which students learn about viral epidemics through engagement in modeling practices across different models. For this final phase, teachers will participate in professional development about viral epidemics and modeling and then implement the viral epidemic module in their biology classes. A pre- and post-test research design will be used to explore student conceptual understandings, model-informed reasoning, and epistemic understandings.

Developing and Evaluating Assessments of Problem-Solving in Computer Adaptive Testing Environments (Collaborative Research: Bostic)

The Common Core State Standards for Mathematics (CCSSM) problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2100988
Funding Period: 
Sun, 08/01/2021 to Fri, 07/31/2026
Full Description: 

Problem solving has been a priority within K-12 mathematics education for over four decades and is reflected throughout the Common Core State Standards for Mathematics (CCSSM) initiative, which have been adopted in some form by 41 states. Broadly defined, problem solving involves the mathematical practices in which students engage as they solve intellectually-challenging mathematical tasks. In prior research, problem-solving measures aligned to CCSSM for grades 3-5 were developed and validated to supplement previously established problem-solving measures in grades 6-8. The problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests. Few measures designed to assess students’ mathematical problem-solving ability use this technology. Shorter tests require less in-class time for assessment than current paper-pencil problem-solving measures and increase classroom instruction time. The computer-adaptive problem-solving measures have sufficient reliability and strong validity evidence, and may limit test-taker fatigue. Finally, the project will benchmark current grades 6-8 instruments using an objective standard-setting method, which allows for improved score interpretations with content-related feedback. Immediate results of student- and class-level reports will be produced through the computer adaptive testing system allowing for teachers to modify instruction to improve students’ learning.

This five-year project aims to advance the use of computer adaptive testing and assessment development for use in mathematics instruction. The project applies an iterative and stakeholder-informed design science-based methodology as well as employs the use of Rasch modeling for the psychometric analysis during item development and validation. The project aims to: (a) benchmark the previously established grades 6-8 problem-solving measures; (b) develop, calibrate, and validate criterion-referenced computer adaptive testing for each measure; (c) construct student- and class-level score reports for integration into the computer adaptive testing system; and (d) investigate teachers’ capacity for implementing, interpreting, and using the assessments and results in STEM learning settings. The project addresses the following set of research questions: (RQ1) What benchmark performance standards define different proficiency levels on problem-solving measures for each grade level? (RQ2) What are the psychometric properties of new problem-solving measures items developed for the computer adaptive testing item bank? (RQ3) Is there significant item drift across student populations on the new problem-solving measure items? (RQ4) To what extent are problem-solving measures item calibrations stable within the computer adaptive testing system? (RQ5) What recommendations for improvements do teachers and students have for the new problem-solving measures items, computer adaptive testing platform and reporting system, if any? (RQ6) To what extent do teachers interact with, perceive, and make sense of the assessment information generated for use in practice? and (RQ7) Does an online learning module build teacher capacity for problem solving measures, computer adaptive testing implementation, interpretation, and use of student assessment outcomes in STEM learning settings? An experimental design will be utilized to investigate teachers’ capacity for implementing, interpreting, and using problem solving measures in a computer adaptive testing system. The project has the potential to impact the field by providing school districts and researchers a means to assess students’ mathematical problem-solving performance at one time or growth over time efficiently and effectively; address future online learning needs; and improve classroom teaching through more precise information about students’ strengths with less class time focused on assessment.

Developing and Evaluating Assessments of Problem-Solving in Computer Adaptive Testing Environments (Collaborative Research: Sondergeld)

The Common Core State Standards for Mathematics (CCSSM) problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2101026
Funding Period: 
Sun, 08/01/2021 to Fri, 07/31/2026
Full Description: 

Problem solving has been a priority within K-12 mathematics education for over four decades and is reflected throughout the Common Core State Standards for Mathematics (CCSSM) initiative, which have been adopted in some form by 41 states. Broadly defined, problem solving involves the mathematical practices in which students engage as they solve intellectually-challenging mathematical tasks. In prior research, problem-solving measures aligned to CCSSM for grades 3-5 were developed and validated to supplement previously established problem-solving measures in grades 6-8. The problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests. Few measures designed to assess students’ mathematical problem-solving ability use this technology. Shorter tests require less in-class time for assessment than current paper-pencil problem-solving measures and increase classroom instruction time. The computer-adaptive problem-solving measures have sufficient reliability and strong validity evidence, and may limit test-taker fatigue. Finally, the project will benchmark current grades 6-8 instruments using an objective standard-setting method, which allows for improved score interpretations with content-related feedback. Immediate results of student- and class-level reports will be produced through the computer adaptive testing system allowing for teachers to modify instruction to improve students’ learning.

This five-year project aims to advance the use of computer adaptive testing and assessment development for use in mathematics instruction. The project applies an iterative and stakeholder-informed design science-based methodology as well as employs the use of Rasch modeling for the psychometric analysis during item development and validation. The project aims to: (a) benchmark the previously established grades 6-8 problem-solving measures; (b) develop, calibrate, and validate criterion-referenced computer adaptive testing for each measure; (c) construct student- and class-level score reports for integration into the computer adaptive testing system; and (d) investigate teachers’ capacity for implementing, interpreting, and using the assessments and results in STEM learning settings. The project addresses the following set of research questions: (RQ1) What benchmark performance standards define different proficiency levels on problem-solving measures for each grade level? (RQ2) What are the psychometric properties of new problem-solving measures items developed for the computer adaptive testing item bank? (RQ3) Is there significant item drift across student populations on the new problem-solving measure items? (RQ4) To what extent are problem-solving measures item calibrations stable within the computer adaptive testing system? (RQ5) What recommendations for improvements do teachers and students have for the new problem-solving measures items, computer adaptive testing platform and reporting system, if any? (RQ6) To what extent do teachers interact with, perceive, and make sense of the assessment information generated for use in practice? and (RQ7) Does an online learning module build teacher capacity for problem solving measures, computer adaptive testing implementation, interpretation, and use of student assessment outcomes in STEM learning settings? An experimental design will be utilized to investigate teachers’ capacity for implementing, interpreting, and using problem solving measures in a computer adaptive testing system. The project has the potential to impact the field by providing school districts and researchers a means to assess students’ mathematical problem-solving performance at one time or growth over time efficiently and effectively; address future online learning needs; and improve classroom teaching through more precise information about students’ strengths with less class time focused on assessment.

Supporting High School Students and Teachers with a Digital, Localizable, Climate Education Experience

This partnership of BSCS Science Learning, Oregon Public Broadcasting, and the National Oceanic and Atmospheric Administration advances curriculum materials development for high quality units that are intentionally designed for adaptation by teachers for their local context. The project will create a base unit on carbon cycling as a foundation for understanding how and why the Earth's climate is changing, and it will study the process of localizing the unit for teachers to implement across varied contexts to incorporate local phenomena, problems, and solutions.

Lead Organization(s): 
Award Number: 
2100808
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

Teachers regularly adapt curriculum materials to localize for their school or community context, yet curriculum materials are not always created to support this localization. Developing materials that are intentionally designed for localization has potential to support rich science learning across different contexts, especially for a topic like climate change where global change can have varied local effects. This partnership of BSCS Science Learning, Oregon Public Broadcasting, and the National Oceanic and Atmospheric Administration advances curriculum materials development for high quality units that are intentionally designed for adaptation by teachers for their local context. It will develop and test a design process bringing together national designers and teachers across the country. Teachers will be supported through professional learning to adapt from the base unit to create a local learning experience for their students. The project will create a base unit on carbon cycling as a foundation for understanding how and why the Earth's climate is changing, and it will study the process of localizing the unit for teachers to implement across varied contexts to incorporate local phenomena, problems, and solutions. The unit will be fully digital with rich visual experiences, simulations, and computer models that incorporate real-time data and the addition of localized data sets. These data-based learning experiences will support students in reasoning with data to ask and answer questions about phenomena. Research will study the unit development and localization process, the supports appropriate for teachers and students, and the impact on classroom practice.

The project will adopt an iterative design process to create a Storyline base unit, aligned to Next Generation Science Standards, for localization, piloting, and an implementation study with 40 teachers. To support teacher learning, the project adopts the STeLLA teacher professional learning model. To support student learning, the project addresses climate change content knowledge with a focus on socioscientific issues and students’ sense of agency with environmental science. The project will research how the educative features in the unit and the professional development impact teachers’ practice, including their content knowledge, comfort for teaching a socioscientific issue, and their ability to productively localize materials from a base unit. The study uses a cohort-control quasi-experimental design to examine the impact of the unit and professional learning experience on dimensions of students' sense of agency with environmental science. The study will also include exploratory analyses to examine whether all students benefit from the unit. It uses a pre-post design to examine impacts on teacher knowledge and practice.

Fostering Computational Thinking through Neural Engineering Activities in High School Biology Classes

This project will develop and study a curriculum and app that support computational thinking (CT) in a high school biology unit. The project will engage students in rich data practices by gathering, manipulating, analyzing, simulating, and visualizing data of bioelectrical signals from neural sensors, and in so doing give the students opportunities to apply CT principles.

Lead Organization(s): 
Award Number: 
2101615
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Computational thinking (CT) is a set of processes to identify and solve problems using algorithms or steps, and can be applied not only in computer science but in other disciplines. This project will develop and study a curriculum and app that support CT in a high school biology unit. Through a month-long neural engineering unit, approximately 500 students in 18 classes will measure their own muscle and brain activity with a low-cost, portable, wearable technology. Students will then analyze the data and design a brain-computer interface to turn neural signals into real-world output (e.g., a mechanical claw controlled by brain activity). The curriculum will be supported by: (1) a web-based instructional application that will guide students through the neural engineering design process; (2) neuroscience and engineering PhD students and postdocs acting as STEM mentors; and (3) a professional development program for teachers and mentors. The goal is to increase the students’ knowledge and interest regarding neurobiology, engineering, and computational thinking. This can contribute to their long-term capacity to pursue STEM careers. By integrating CT education into high school science, this expands the accessibility of the engineering and computing experiences beyond other efforts that focus primarily on programming and computer science courses.

The project will engage students in rich data practices by gathering, manipulating, analyzing, simulating, and visualizing data of bioelectrical signals from neural sensors, and in so doing give the students opportunities to apply computational thinking principles. The project will produce curriculum materials for the neural sensors and associated data practices. It will develop an app to help students design and construct a brain-computer interface, including computational elements like coding blocks, sensor and data simulation, and connecting to external devices. The five proposed research questions of the study are: How does students’ CT change throughout their participation in the neural engineering design process? What is the cross-cultural validity of two CT scales in a sample of high school students in the US? How does the process of collecting and analyzing real-world data relate to students’ experience of he engineering design process? How do students’ attitudes toward STEM change over the course of their participation in a neural engineering design process? How does teachers’ self-efficacy for fostering CT in their students via engineering design change through their participation in professional development and in implementation of the proposed curriculum?

Empowering Teachers to See and Support Student Use of Crosscutting Concepts in the Life Sciences

The project focuses on the development of formative assessment tools that highlight assets of students’ use of crosscutting concepts (CCCs) while engaged in science and engineering practices in grades 9-12 Life Sciences.

Lead Organization(s): 
Award Number: 
2100822
Funding Period: 
Sun, 08/01/2021 to Wed, 07/31/2024
Full Description: 

The project focuses on the development of formative assessment tools that highlight assets of students’ use of crosscutting concepts (CCCs) while engaged in science and engineering practices in grades 9-12 Life Sciences. In response to the calls set forth by the Framework for K-12 Science Education and Next Generation Science Standards (NGSS), the field has most successfully researched and developed assessment tools for disciplinary core ideas and the science and engineering practices. The CCCs, which serve as the connective links across science domains, however, remain more abstractly addressed. Presently, science educators have little guidance for what student use of CCCs looks like or how to assess and nurture such use. This project, with its explicit attention to the CCCs, advances true three-dimensional scientific understanding in both research and the classroom. Leveraging formative assessment as a vehicle for student and teacher development taps into proven successful instructional strategies (e.g., sharing visions of successful learning, descriptive feedback, self-assessment), while also advancing formative assessment, itself, by strengthening and illustrating how these strategies may focus on the CCCs. Further, a strengths-based approach will center culturally related differences in students’ use of CCCs to achieve more equitable opportunities to engage in classroom sensemaking practices. This work impacts the field of science education by 1) enabling a more thorough realization of NGSS ideals, 2) strengthening teachers’ abilities to identify diverse demonstrations of CCCs, and 3) showcasing the impact of novel classroom tools to sharpen teachers’ abilities to solicit, notice, and act upon evidence of emergent student scientific thinking within their instructional practices.

This design-based implementation research project will engage teachers in the iterative development and refinement of rubrics that support three-dimensional science understanding through formative assessment. The high school biology classrooms that compose the study site are engaged in ambitious science teaching-inspired instruction. An inductive, bottom-up approach (Brookhart, 2013) will allow researchers, teachers, and students to co-construct rubrics. Analysis of classroom observations, artifact collection, interviews with teachers and students, and expert-panel ratings will produce a rubric for each CCC that integrates relevant science and engineering practices and is applicable across a range of disciplinary core ideas. These rubrics will illustrate progressions of increasingly advanced use of each of the CCCs, to guide the construction, pursuit, and assessment of learning goals. There will be two design cycles that allow for the collection of validity evidence and produce rubrics with the potential for broad application by educators. Complementary lines of qualitative and quantitative (i.e., psychometric) analysis will contribute to development and validation of the rubrics and their formative uses. Project inquiry will focus on 1) how the rubrics can represent CCCs for key disciplinary practices, 2) the extent to which teachers’ and students’ understandings of the rubrics align, and 3) how implementation of the rubrics impacts teachers’ and students’ understandings of the CCCs.

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.

Exploratory Evidence on the Factors that Relate to Elementary School Science Learning Gains Among English Language Learners

This project will provide evidence on how school, classroom, teacher, and student factors shape elementary school science learning trajectories for English learners (ELs). The project will broaden ELs’ participation in STEM learning by investigating how individual, classroom, and school level situations such as instructional practices, learning environments, and characteristics of school personnel relate to EL elementary school science learning.

Lead Organization(s): 
Award Number: 
2100419
Funding Period: 
Sat, 05/15/2021 to Sun, 04/30/2023
Full Description: 

The nation’s schools are growing in linguistic and cultural diversity, with students identified as English learners (ELs) comprising more than ten percent of the student population. Unfortunately, existing research suggests that ELs lag behind other students in science achievement, even in the earliest grades of school. This project will provide evidence on how school, classroom, teacher, and student factors shape elementary school science learning trajectories for ELs. The project will broaden ELs’ participation in STEM learning by investigating how individual, classroom, and school level situations (inputs) such as instructional practices, learning environments, and characteristics of school personnel relate to EL elementary school science learning. Specifically, this study explores (1) a series of science inputs (time on science, content covered, availability of lab resources, and teacher training in science instruction), and (2) EL-specific inputs (classroom language use, EL instructional models, teacher certification and training, and the availability of EL support staff), in relation to ELs’ science learning outcomes from a national survey.

This study provides a comprehensive analysis of English learners’ (ELs) science learning in the early grades and the English learner instructional inputs and science instructional inputs that best predict early science outcomes (measured by both standardized science assessments and teacher-rated measures of science skills). The study uses the nationally representative Early Childhood Longitudinal Study (ECLS-K:2011) and employs a regression framework with latent class analysis to identify promising inputs that promote early science learning for ELs. Conceptually, rather than viewing the school-based inputs in isolation, the study explores how they combine to enhance students’ science learning trajectories. The study addresses the following research questions: How do science test performance trajectories vary across and within EL student groups in elementary school? How do access to school, teacher, and classroom level science and EL inputs vary across and within EL student groups in elementary school? Which school, teacher, and classroom level science and EL inputs are predictive of greater science test performance gains and teacher-rated science skills in elementary school? Are the relationships among these school, teacher, and classroom level inputs and student test performance and teacher-rated science skills different for subgroups of EL students, particularly by race/ethnicity or by immigration status? Are there particular combinations of school, teacher, and classroom level inputs that are predictive of science learning gains (test scores and teacher-rated skills) for ELs as compared to students more broadly?

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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