Student Attitudes/Beliefs

Supporting Teachers to Develop Equitable Mathematics Instruction Through Rubric-Based Coaching (Collaborative Research: Hill)

This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics.

Lead Organization(s): 
Award Number: 
2100961
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Creating supportive middle school mathematics learning spaces that foster students' self-efficacy and mathematics learning is a critical need in the United States. This need is particularly urgent for mathematics classrooms with students who have been historically marginalized in such spaces. While many instructional improvement efforts have focused on broadening access to mathematical ideas, fewer efforts have paid explicit attention to the ways instructional practices may serve to marginalize students. Supporting teachers in identifying and refining their equitable mathematics instructional practices is a persistent challenge. This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project's work integrates the EAR-MI rubrics into the MQI Coaching model with 24 middle grades mathematics coaches supporting 72 teachers at grades 5-8. The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

The project makes use of a delayed-treatment experimental design to investigate effects on teacher beliefs and practices and student achievement and sense of belonging. A cohort of 14 coaches are randomly selected to participate in the coaching in Years 2 and 3, with the remaining 10 coaches assigned to a business-as-usual model in Year 2 and engaging in the training in Year 3. Coaches engage in a 4-day summer training to become acquainted with the model with coaching cycles and follow-up meetings during the school year. Each coach will engage teachers in 8-10 coaching cycles in treatment years. Data on the nature of the coaching includes logs and surveys from the coaches. Teachers submit surveys related to their beliefs and practices and two lessons each at the start and end of the academic year for analysis. Student assessment data, course grades, and administrative data, combined with survey data from students on classroom belonging and perceptions of ability and confidence in mathematics, are used to describe student outcomes. Teacher outcomes are captured through the analysis of classroom video, surveys about ethnic-racial identity and racial attitudes, beliefs about students and instruction, and beliefs about and efficacy for culturally responsive teaching. The project uses a set of survey measures with established reliability and validity, adapting some instruments to include specific indicators related to the equity and access rubrics. Analysis of the data uses a multi-level model accounting for the clustering of teachers within schools and students within classrooms and schools.

Supporting Teachers to Develop Equitable Mathematics Instruction Through Rubric-based Coaching (Collaborative Research: Litke)

This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics.

Lead Organization(s): 
Award Number: 
2100793
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Creating supportive middle school mathematics learning spaces that foster students' self-efficacy and mathematics learning is a critical need in the United States. This need is particularly urgent for mathematics classrooms with students who have been historically marginalized in such spaces. While many instructional improvement efforts have focused on broadening access to mathematical ideas, fewer efforts have paid explicit attention to the ways instructional practices may serve to marginalize students. Supporting teachers in identifying and refining their equitable mathematics instructional practices is a persistent challenge. This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project's work integrates the EAR-MI rubrics into the MQI Coaching model with 24 middle grades mathematics coaches supporting 72 teachers at grades 5-8. The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

The project makes use of a delayed-treatment experimental design to investigate effects on teacher beliefs and practices and student achievement and sense of belonging. A cohort of 14 coaches are randomly selected to participate in the coaching in Years 2 and 3, with the remaining 10 coaches assigned to a business-as-usual model in Year 2 and engaging in the training in Year 3. Coaches engage in a 4-day summer training to become acquainted with the model with coaching cycles and follow-up meetings during the school year. Each coach will engage teachers in 8-10 coaching cycles in treatment years. Data on the nature of the coaching includes logs and surveys from the coaches. Teachers submit surveys related to their beliefs and practices and two lessons each at the start and end of the academic year for analysis. Student assessment data, course grades, and administrative data, combined with survey data from students on classroom belonging and perceptions of ability and confidence in mathematics, are used to describe student outcomes. Teacher outcomes are captured through the analysis of classroom video, surveys about ethnic-racial identity and racial attitudes, beliefs about students and instruction, and beliefs about and efficacy for culturally responsive teaching. The project uses a set of survey measures with established reliability and validity, adapting some instruments to include specific indicators related to the equity and access rubrics. Analysis of the data uses a multi-level model accounting for the clustering of teachers within schools and students within classrooms and schools.

Supporting Teachers to Develop Equitable Mathematics Instruction Through Rubric-based Coaching (Collaborative Research: Wilson)

This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics.

Award Number: 
2100830
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Creating supportive middle school mathematics learning spaces that foster students' self-efficacy and mathematics learning is a critical need in the United States. This need is particularly urgent for mathematics classrooms with students who have been historically marginalized in such spaces. While many instructional improvement efforts have focused on broadening access to mathematical ideas, fewer efforts have paid explicit attention to the ways instructional practices may serve to marginalize students. Supporting teachers in identifying and refining their equitable mathematics instructional practices is a persistent challenge. This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project's work integrates the EAR-MI rubrics into the MQI Coaching model with 24 middle grades mathematics coaches supporting 72 teachers at grades 5-8. The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

The project makes use of a delayed-treatment experimental design to investigate effects on teacher beliefs and practices and student achievement and sense of belonging. A cohort of 14 coaches are randomly selected to participate in the coaching in Years 2 and 3, with the remaining 10 coaches assigned to a business-as-usual model in Year 2 and engaging in the training in Year 3. Coaches engage in a 4-day summer training to become acquainted with the model with coaching cycles and follow-up meetings during the school year. Each coach will engage teachers in 8-10 coaching cycles in treatment years. Data on the nature of the coaching includes logs and surveys from the coaches. Teachers submit surveys related to their beliefs and practices and two lessons each at the start and end of the academic year for analysis. Student assessment data, course grades, and administrative data, combined with survey data from students on classroom belonging and perceptions of ability and confidence in mathematics, are used to describe student outcomes. Teacher outcomes are captured through the analysis of classroom video, surveys about ethnic-racial identity and racial attitudes, beliefs about students and instruction, and beliefs about and efficacy for culturally responsive teaching. The project uses a set of survey measures with established reliability and validity, adapting some instruments to include specific indicators related to the equity and access rubrics. Analysis of the data uses a multi-level model accounting for the clustering of teachers within schools and students within classrooms and schools.

Accessible Computational Thinking in Elementary Science Classes within and across Culturally and Linguistically Diverse Contexts (Collaborative Research: Nelson)

This research project aims to enhance elementary teacher education in science and computational thinking pedagogy through the use of Culturally Relevant Teaching, i.e. teaching in ways that are relevant to students from different cultural and linguistic backgrounds. The project will support 60 elementary teachers in summer professional development and consistent learning opportunities during the school year to learn about and enact culturally relevant computational thinking into their science instruction.

Lead Organization(s): 
Award Number: 
2101039
Funding Period: 
Sun, 08/15/2021 to Wed, 07/31/2024
Full Description: 

Currently, students who are white, affluent, and identify as male tend to develop a greater interest in and pursuit of science and computing-related careers compared to their Black, Latinx, Native American, and female-identifying peers. Yet, science, computing, and computational thinking drive societal decision-making and problem-solving. The lack of cultural and racial diversity in science and computing-related careers can lead to societal systems and decision-making structures that fail to consider a wide range of perspectives and expertise. Teachers play a critical role in preparing students to develop these skills and succeed in a technological and scientific world. For this reason, it is crucial to investigate how teachers can help culturally and linguistically diverse students develop a greater understanding of and interest in science and computers. This research project aims to enhance elementary teacher education in science and computational thinking pedagogy through the use of Culturally Relevant Teaching, i.e. teaching in ways that are relevant to students from different cultural and linguistic backgrounds. The project will support 60 elementary teachers in summer professional development and consistent learning opportunities during the school year to learn about and enact culturally relevant computational thinking into their science instruction. In doing so, the project aims to increase both the quantity and quality of computing experiences for all elementary students and support NSF’s commitment in broadening participation in the STEM workforce. The project will also produce resources, measures, and tools to support elementary teachers to do this kind of work, which will be shared with other STEM researchers and teacher educators.

The goal of this research project is to design and promote teaching practices that integrate computational thinking in the elementary science classroom in culturally relevant ways. This project will seek to empower practicing elementary teachers’ approaches to meaningfully and effectively integrate and adapt computational thinking into their regular science teaching practice so that all students can access the curriculum. It will also explore the impact of these approaches on student learning and self-efficacy. The scope of this project will include working with multiple highly distinct school settings in Maryland, Arizona, and Washington DC across three years, reaching approximately 60 elementary teachers and 1,200 students. To achieve the project objectives, the research team will leverage concurrent mixed methods approaches that include teacher and student interviews, reflections, observations, descriptive case study reports as well as regression and multilevel modeling. The project’s findings will inform the fields’ understanding of: (a) teachers’ conceptualization of computational thinking; (b) the barriers elementary teachers encounter when trying to integrate computational thinking with culturally relevant teaching practices; (c) the types of support that are effective in teacher professional development experiences  and throughout the school year; and (d) the development of a cohort of teachers that can maintain integration efforts in different districts.

Accessible Computational Thinking in Elementary Science Classes within and across Culturally and Linguistically Diverse Contexts (Collaborative Research: Ketelhut)

This research project aims to enhance elementary teacher education in science and computational thinking pedagogy through the use of Culturally Relevant Teaching, i.e. teaching in ways that are relevant to students from different cultural and linguistic backgrounds. The project will support 60 elementary teachers in summer professional development and consistent learning opportunities during the school year to learn about and enact culturally relevant computational thinking into their science instruction.

Partner Organization(s): 
Award Number: 
2101526
Funding Period: 
Sun, 08/15/2021 to Wed, 07/31/2024
Full Description: 

Currently, students who are white, affluent, and identify as male tend to develop a greater interest in and pursuit of science and computing-related careers compared to their Black, Latinx, Native American, and female-identifying peers. Yet, science, computing, and computational thinking drive societal decision-making and problem-solving. The lack of cultural and racial diversity in science and computing-related careers can lead to societal systems and decision-making structures that fail to consider a wide range of perspectives and expertise. Teachers play a critical role in preparing students to develop these skills and succeed in a technological and scientific world. For this reason, it is crucial to investigate how teachers can help culturally and linguistically diverse students develop a greater understanding of and interest in science and computers. This research project aims to enhance elementary teacher education in science and computational thinking pedagogy through the use of Culturally Relevant Teaching, i.e. teaching in ways that are relevant to students from different cultural and linguistic backgrounds. The project will support 60 elementary teachers in summer professional development and consistent learning opportunities during the school year to learn about and enact culturally relevant computational thinking into their science instruction. In doing so, the project aims to increase both the quantity and quality of computing experiences for all elementary students and support NSF’s commitment in broadening participation in the STEM workforce. The project will also produce resources, measures, and tools to support elementary teachers to do this kind of work, which will be shared with other STEM researchers and teacher educators.

The goal of this research project is to design and promote teaching practices that integrate computational thinking in the elementary science classroom in culturally relevant ways. This project will seek to empower practicing elementary teachers’ approaches to meaningfully and effectively integrate and adapt computational thinking into their regular science teaching practice so that all students can access the curriculum. It will also explore the impact of these approaches on student learning and self-efficacy. The scope of this project will include working with multiple highly distinct school settings in Maryland, Arizona, and Washington DC across three years, reaching approximately 60 elementary teachers and 1,200 students. To achieve the project objectives, the research team will leverage concurrent mixed methods approaches that include teacher and student interviews, reflections, observations, descriptive case study reports as well as regression and multilevel modeling. The project’s findings will inform the fields’ understanding of: (a) teachers’ conceptualization of computational thinking; (b) the barriers elementary teachers encounter when trying to integrate computational thinking with culturally relevant teaching practices; (c) the types of support that are effective in teacher professional development experiences  and throughout the school year; and (d) the development of a cohort of teachers that can maintain integration efforts in different districts.

Using Natural Language Processing to Inform Science Instruction (Collaborative Research: Linn)

This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. The project will conduct a comprehensive research program to develop and test technology that will empower students to use their ideas as a starting point for deepening science understanding. Researchers will use a technology that detects student ideas that go beyond a student's general knowledge level to adapt to a student's cultural and linguistic understandings of a science topic.

Partner Organization(s): 
Award Number: 
2101669
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

Often, middle school science classes do not benefit from participation of underrepresented students because of language and cultural barriers. This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. This work continues a partnership among the University of California, Berkeley, Educational Testing Service, and science teachers and paraprofessionals from six middle schools enrolling students from diverse racial, ethnic, and language groups whose cultural experiences may be neglected in science instruction. The partnership will conduct a comprehensive research program to develop and test technology that will empower students to use their ideas as a starting point for deepening science understanding. Researchers will use a technology that detects student ideas that go beyond a student's general knowledge level to adapt to a student's cultural and linguistic understandings of a science topic. The partnership leverages a web-based platform to implement adaptive guidance designed by teachers that feature dialog and peer interaction. Further, the platform features teacher tools that can detect when a student needs additional help and alert the teacher. Teachers using the technology will be able to track and respond to individual student ideas, especially from students who would not often participate because of language and cultural barriers.

This project develops AI-based technology to help science teachers increase their impact on student science learning. The technology is aimed to provide accurate analysis of students' initial ideas and adaptive guidance that gets each student started on reconsidering their ideas and pursuing deeper understanding. Current methods in automated scoring primarily focus on detecting incorrect responses on test questions and estimating the overall knowledge level in a student explanation. This project leverages advances in natural language processing (NLP) to identify the specific ideas in student explanations for open-ended science questions. The investigators will conduct a comprehensive research program that pairs new NLP-based AI methods for analyzing student ideas with adaptive guidance that, in combination, will empower students to use their ideas as starting points for improving science understanding. To evaluate the idea detection process, the researchers will conduct studies that investigate the accuracy and impact of idea detection in classrooms. To evaluate the guidance, the researchers will conduct comparison studies that randomly assign students to conditions to identify the most promising adaptive guidance designs for detected ideas. All materials are customizable using open platform authoring tools.

Using Natural Language Processing to Inform Science Instruction (Collaborative Research: Riordan)

This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. The project will conduct a comprehensive research program to develop and test technology that will empower students to use their ideas as a starting point for deepening science understanding. Researchers will use a technology that detects student ideas that go beyond a student's general knowledge level to adapt to a student's cultural and linguistic understandings of a science topic.

Lead Organization(s): 
Award Number: 
2101670
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

Often, middle school science classes do not benefit from participation of underrepresented students because of language and cultural barriers. This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. This work continues a partnership among the University of California, Berkeley, Educational Testing Service, and science teachers and paraprofessionals from six middle schools enrolling students from diverse racial, ethnic, and language groups whose cultural experiences may be neglected in science instruction. The partnership will conduct a comprehensive research program to develop and test technology that will empower students to use their ideas as a starting point for deepening science understanding. Researchers will use a technology that detects student ideas that go beyond a student's general knowledge level to adapt to a student's cultural and linguistic understandings of a science topic. The partnership leverages a web-based platform to implement adaptive guidance designed by teachers that feature dialog and peer interaction. Further, the platform features teacher tools that can detect when a student needs additional help and alert the teacher. Teachers using the technology will be able to track and respond to individual student ideas, especially from students who would not often participate because of language and cultural barriers.

This project develops AI-based technology to help science teachers increase their impact on student science learning. The technology is aimed to provide accurate analysis of students' initial ideas and adaptive guidance that gets each student started on reconsidering their ideas and pursuing deeper understanding. Current methods in automated scoring primarily focus on detecting incorrect responses on test questions and estimating the overall knowledge level in a student explanation. This project leverages advances in natural language processing (NLP) to identify the specific ideas in student explanations for open-ended science questions. The investigators will conduct a comprehensive research program that pairs new NLP-based AI methods for analyzing student ideas with adaptive guidance that, in combination, will empower students to use their ideas as starting points for improving science understanding. To evaluate the idea detection process, the researchers will conduct studies that investigate the accuracy and impact of idea detection in classrooms. To evaluate the guidance, the researchers will conduct comparison studies that randomly assign students to conditions to identify the most promising adaptive guidance designs for detected ideas. All materials are customizable using open platform authoring tools.

DataX: Exploring Justice-Oriented Data Science with Secondary School Students

This project will develop an integrated, justice-oriented curriculum and a digital platform for teaching secondary students about data science in science and social studies classrooms. The platform will help students learn about data science using real-world data sets and problems. This interdisciplinary project will also help students meaningfully analyze real-world data sets, interpret social phenomena, and engage in social change.

Award Number: 
2101413
Funding Period: 
Thu, 07/01/2021 to Fri, 06/30/2023
Full Description: 

Understanding data is critical for informed citizens. Data science is a growing and emerging field that can incorporate statistics, mathematics, and computer science to develop disciplinary knowledge and address societal challenges. This project will develop an integrated, justice-oriented curriculum and a digital platform for teaching secondary students about data science in science and social studies classrooms. The platform will help students learn about data science using real-world data sets and problems. This project includes science and social studies teachers in the design of the resources and in testing them in secondary school classrooms. Research and development in data science education is needed to understand how students can learn more about the use of data in meaningful and authentic ways. This interdisciplinary project will also help students meaningfully analyze real-world data sets, interpret social phenomena, and engage in social change.

During a two-year project period, we aim to iteratively advance three design components of the DataX program: (a) a justice-oriented data science curriculum integrated in secondary science and social studies; (b) a web-based learning platform that extends the Common Online Data Analysis Platform (CODAP) to support collaboration and sophisticated data practices; and (c) pedagogical practices that involve learners to work collectively as community. The guiding research question is: What scaffolds and resources are necessary to support the co-development of data, disciplinary, and critical literacies in secondary classrooms? To address this, the project will use participatory design research with science and social studies teachers to develop and test the curriculum, the learning platform, and the pedagogical practices. The data collected will include qualitative sources gathered from participatory design workshops and classrooms, as well as quantitative data from questionnaires and system logs. Using the data, we examine students' data science skills, data dispositions, and social participation in collaborative data investigations.

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.

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