Women/Girls

Looking Back and Looking Forward: Increasing the Impact of Educational Research on Practice

The focus of this conference is to carefully examine past and current research with an eye toward improving its impact on practice and to create concrete steps that could shape the nature and impact of mathematics education research.

Lead Organization(s): 
Award Number: 
1941494
Funding Period: 
Sun, 09/01/2019 to Mon, 08/31/2020
Full Description: 

The focus of the proposed conference is to carefully examine past and current research with an eye toward improving its impact on practice. This conference is designed to create concrete steps that could shape the nature and impact of mathematics education research for years to come. A diverse group of 50 participants will be invited to participate. Participants include 10 experienced K-12 educators whose perspectives will be used to anchor the conference in problems of practice. Other participants represent senior through more junior scholars who have demonstrated a commitment to addressing the disconnect between research and practice, along with technology experts to advise participants on capabilities and innovative uses of modern technologies for instruction, assessment and data management.

The overarching goal for the conference is to help the field of mathematics education think deeply about the most productive ways to answer the following questions: [1] Why hasn't past research had a more direct impact on practice? What can be learned from this historical analysis for future research? [2] What is a possible vision for research that would have a more direct impact on practice? What questions should be asked? What methods should be used? What concrete steps can be taken to launch the new research programs? [3] What are the implications of adopting new kinds of research programs? If they gain traction, how will such changes affect the broader education community and infrastructure, including preservice teacher education, teacher professional development, and the training of future researchers? How should the roles of researchers and teachers change? What incentive structures might motivate these changes? How will new programs of research interact with existing programs?

The Developmental Emergence and Consequences of Spatial and Math Gender Stereotypes

This project will investigate the development and emergence of spatial gender stereotypes (and their relation to math gender stereotypes) in elementary school-aged children and their impact on parent-child interactions in the pre-school period.

Lead Organization(s): 
Award Number: 
1920732
Funding Period: 
Thu, 08/01/2019 to Sun, 07/31/2022
Full Description: 

There is currently a gender gap in STEM fields, such that females participate at lower rates and have lower career attainment than their male counterparts. While much research has focused on gender differences in math attitudes, little work has explored how attitudes in a closely related STEM domain, spatial reasoning, may also contribute to the observed gender gap. The proposed research will characterize the acquisition of gender stereotypes in childhood in two key domains critical to success and participation in STEM fields: math and spatial skills. Recent evidence suggests that children acquire math gender stereotypes (i.e., the belief that "math is for boys") as early as 1st - 2nd grades, but less is known about children's attitudes about spatial abilities. This project will be one of the first to investigate the development and emergence of spatial gender stereotypes (and their relation to math gender stereotypes) in elementary school-aged children, and their impact on parent-child interactions in the pre-school period.

Eight behavioral studies involving 1290 children (Pre-K - 4th graders), 240 caregivers, and 180 adults will participate in studies that evaluate an integrated theoretical model of the relations between gender, gender stereotypes, attitudes, and abilities in the domains of math and space. In Series 1, studies will characterize the emergence of and assumptions behind spatial- and math- gender stereotypes in 1st - 4th graders, while determining how they may be acquired. In Series 2, studies will explore the real-world impacts of spatial-gender stereotypes on STEM participation and achievement in childhood. Lastly, Series 3 studies will explore the malleability of these stereotypes in the hopes of identifying ways to ameliorate their impact early in development. The project will provide training for doctoral graduate and undergraduate students. Moreover, this project will support new and ongoing collaborations with local children's museums, which facilitate interactions and communication with families, educators, and the public about the research findings. By being some of the first work to uncover the developmental origins and consequences of math and spatial stereotypes, this work may inform possible future interventions to reduce and/or eliminate the perpetuation of these stereotypes in children, long before they can have greater lifelong impacts.

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

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

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

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

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

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

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

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

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

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

Validation of the Equity and Access Rubrics for Mathematics Instruction (VEAR-MI)

The main goal of this project is to validate a set of rubrics that attend to the existence and the quality of instructional practices that support equity and access in mathematics classes. The project team will clarify the relationships between the practices outlined in the rubrics and aspects of teachers' perspectives and knowledge as well as student learning outcomes.

Award Number: 
1908481
Funding Period: 
Mon, 07/15/2019 to Fri, 06/30/2023
Full Description: 

High-quality mathematics instruction remains uncommon and opportunities for students to develop the mathematical understanding are not distributed equally. This is particularly true for students of color and students for whom English is not their first language. While educational research has made progress in identifying practices that are considered high-quality, little attention has been given to specific instructional practices that support historically marginalized groups of students particularly as they participate in more rigorous mathematics. The main goal is to validate a set of rubrics that attend to the existence and the quality of instructional practices that support equity and access in mathematics classes. In addition, the project team will clarify the relationships between the practices outlined in the rubrics and aspects of teachers' perspectives and knowledge as well as student learning outcomes.

This project will make use of two existing large-scale datasets focusing on mathematics teachers to develop rubrics on mathematics instructional quality. The datasets include nearly 3,000 video-recorded mathematics lessons and student achievement records from students in Grades 3 through 8. The four phases of this research and development project include training material development, an observation and rubric generalizability study, a coder reliability study, and structural analysis. Data analysis plans involve case studies, exploratory and confirmatory factor analyses, and cognitive interviews. 

Students and Teachers Learning from Nature: Studying Biologically Inspired Design in High School Engineering Education

In this project, high school engineering teachers will spend five weeks in a research lab devoted to biologically-inspired design, as they partner with cutting-edge engineers and scientists to study animal features and behavior and their applications to engineering designs. After this lab experience, the high school teachers will receive three six- to ten-week curricular units, tailored for tenth- through twelfth-grade students, which teach biologically-inspired design in the context of problems that are relevant to youth.

Award Number: 
1907906
Funding Period: 
Thu, 08/01/2019 to Mon, 07/31/2023
Full Description: 

Scientists and engineers often learn from nature to develop new products that benefit society, a process called biologically-inspired design. Aerospace engineers, for example, have studied the intricate folding patterns in ladybugs' wings to gain ideas for designing more compact satellites. In this project, high school engineering teachers will spend five weeks in a research lab devoted to biologically-inspired design, as they partner with cutting-edge engineers and scientists to study animal features and behavior and their applications to engineering designs. After this lab experience, the high school teachers will receive three six- to ten-week curricular units, tailored for tenth- through twelfth-grade students, which teach biologically-inspired design in the context of problems that are relevant to youth. The teachers will also participate in ongoing professional development sessions that demonstrate strategies for teaching these units. The research team will study whether and how the lab and professional development experiences influence the teachers' understandings of engineering and perspectives toward nature, among other outcomes. Additionally, the research team will study whether the curricular units are associated with positive learning outcomes for students. The curricula and professional development modules will be shared publicly through online resources and teacher workshops, and research findings will be widely disseminated through journals. Because previous research has suggested that biologically-inspired design is a promising approach for attracting and retaining women in engineering careers, this project is likely to result in products that foster high school girls' interest in engineering during a critical period when they are imagining their future career trajectories. Moreover, these products are likely to fuel national innovation by teaching students how to look to nature to find answers to pressing problems, and by generating knowledge about motivational educational approaches that encourage a wider range of high school students to pursue engineering careers.

This project addresses the persistent underrepresentation of girls in engineering careers by developing and testing three sets of curricula that are expected to lead to positive outcomes among high school females. These curricula incorporate biologically-inspired engineering, humanistic engineering, a focus on sustainability and ideation, and authentic design contexts. Ten high school teachers will participate in extensive professional development experiences that prepare them to effectively teach the curricula. These experiences include a five-week lab experience with scientists who are applying biologically-inspired design; a one-week workshop demonstrating strategies for teaching the units; weekly implementation meetings; and web-based professional development modules. To study the effect of the professional development on teachers, researchers will collect curriculum design logs, teacher enactment surveys, and engineering teaching self-efficacy surveys; they will also conduct classroom observations and interviews. Qualitative analyses of these sources will indicate whether and how the professional development affected teachers' understanding of the engineering design process, engineering teaching self-efficacy, and perspective toward the natural and designed world. To study the effect of the curricula on over 1,100 high school students, researchers will use a pre-post design with validated measures to determine whether the curricula are associated with greater understanding and use of the engineering design process; ability to generate well-formulated engineering design problems; engineering self-efficacy; attitudes toward the natural and designed world; sustainability awareness; and intent to persist in engineering. Subsequently, a quasi-experimental design with a matched comparison group will enable the researchers to determine whether the treatment group outperformed the comparison group on pre-post measures. Qualitative analysis of focus groups and interviews with a sub-set of high school girls will indicate whether and how the curricula supported their sense of belonging in engineering. This project is designed to advance knowledge and practice in engineering education for high school students, especially among girls, ultimately resulting in broadening participation in engineering pathways.

Learning Trajectories as a Complete Early Mathematics Intervention: Achieving Efficacies of Economies at Scale

The purpose of this project is to test the efficacy of the Learning and Teaching with Learning Trajectories (LT2) program with the goal of improving mathematics teaching and thereby increasing young students' math learning. LT2 is a professional development tool and a curriculum resource intended for teachers to be used to support early math instruction and includes the mathematical learning goal, the developmental progression, and relevant instructional activities.

Lead Organization(s): 
Award Number: 
1908889
Funding Period: 
Mon, 07/01/2019 to Sun, 06/30/2024
Full Description: 

U.S. proficiency in mathematics continues to be low and early math performance is a powerful predictor of long-term academic success and employability. However, relatively few early childhood degree programs have any curriculum requirements focused on key mathematics topics. Thus, teacher professional development programs offer a viable and promising method for supporting and improving teachers' instructional approaches to mathematics and thus, improving student math outcomes. The purpose of this project is to test the efficacy of the Learning and Teaching with Learning Trajectories (LT2) program with the goal of improving mathematics teaching and thereby increasing young students' math learning. LT2 is a professional development tool and a curriculum resource intended for teachers to be used to support early math instruction. The LT2 program modules uniquely include the mathematical learning goal, the developmental progression, and relevant instructional activities. All three aspects are critical for high-quality and coherent mathematics instruction in the early grades.

This project will address the following research questions: 1) What are the medium-range effects of LT2 on student achievement and the achievement gap? 2) What are the short- and long-term effects of LT2 on teacher instructional approach, beliefs, and quality? and 3) How cost effective is the LT2 intervention relative to the original Building Blocks intervention? To address the research questions, this project will conduct a multisite cluster randomized experimental design, with 90 schools randomly assigned within school districts to either experimental or control groups. Outcome measures for the approximately 250 kindergarten classrooms across these districts will include the Research-based Elementary Math Assessment, observations of instructional quality, a questionnaire focused on teacher beliefs and practices, in addition to school level administrative data. Data will be analyzed using multi-level regression models to determine the effect of the Learning Trajectories intervention on student learning.

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

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

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

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

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

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

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

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

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

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

Engaging High School Students in Computer Science with Co-Creative Learning Companions (Collaborative Research: Magerko)

This research investigates how state-of-the-art creative and pedagogical agents can improve students' learning, attitudes, and engagement with computer science. The project will be conducted in high school classrooms using EarSketch, an online computer science learning environments that engages learners in making music with JavaScript or Python code.

Award Number: 
1814083
Funding Period: 
Sat, 09/15/2018 to Wed, 08/31/2022
Full Description: 
This research investigates how state-of-the-art creative and pedagogical agents can improve students' learning, attitudes, and engagement with computer science. The project will be conducted in high school classrooms using EarSketch, an online computer science learning environments that engages over 160,000 learners worldwide in making music with JavaScript or Python code. The researchers will build the first co-creative learning companion, Cai, that will scaffold students with pedagogical strategies that include making use of learner code to illustrate abstraction and modularity, suggesting new code to scaffold new concepts, providing help and hints, and explaining its decisions. This work will directly address the national need to develop computing literacy as a core STEM skill.
 
The proposed work brings together an experienced interdisciplinary team to investigate the hypothesis that adding a co-creative learning companion to an expressive computer science learning environment will improve students' computer science learning (as measured by code sophistication and concept knowledge), positive attitudes towards computing (self-efficacy and motivation), and engagement (focused attention and involvement during learning). The iterative design and development of the co-creative learning companion will be based on studies of human collaboration in EarSketch classrooms, the findings in the co-creative literature and virtual agents research, and the researchers' observations of EarSketch use in classrooms. This work will address the following research questions: 1) What are the foundational pedagogical moves that a co-creative learning companion for expressive programming should perform?; 2) What educational strategies for a co-creative learning companion most effectively scaffold learning, favorable attitudes toward computing, and engagement?; and 3) In what ways does a co-creative learning companion in EarSketch increase computer science learning, engagement, and positive attitudes toward computer science when deployed within the sociocultural context of a high school classroom? The proposed research has the potential to transform our understanding of how to support student learning in and broaden participation through expressive computing environments.

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