Projects

Teachers of mathematics engage in curricular reasoning as they design and interact with their students, choose curricular materials, and implement curriculum standards in the service of high-quality instruction. Currently, there is no shared measure of curricular reasoning of middle school teacher classroom decision making in mathematics. In this research project, the team develops and validates two measures of middle school teachers’ curricular reasoning in mathematics as practiced. The first measure looks at curriculum reasoning from the perspective of the teacher, the second measure attends to the perspectives of the mathematics education research community.

Teachers of mathematics engage in curricular reasoning as they design and interact with their students, choose curricular materials, and implement curriculum standards in the service of high-quality instruction. Currently, there is no shared measure of curricular reasoning of middle school teacher classroom decision making in mathematics. In this research project, the team develops and validates two measures of middle school teachers’ curricular reasoning in mathematics as practiced. The first measure looks at curriculum reasoning from the perspective of the teacher, the second measure attends to the perspectives of the mathematics education research community.

This project aims to deepen understanding of how to support and develop early childhood science learning by articulating science and engineering practices observed in children’s play. It also aims to develop early childhood educators’ abilities to identify and support nascent science and engineering practices with young children. Through this project early childhood educators will engage in professional learning using a refined version of the Science and Engineering Practices Observation Protocol (SciEPOP), an observation tool that allows researchers to identify and describe high-quality play-based engagement with science and engineering practices. Through video-rich professional learning along with peer-based coaching, early childhood educators will grow in their ability to prepare play environments, identify nascent science and engineering practices, enhance and extend investigations through play, and record and reflect upon this learning.

This project explores the effectiveness of two different versions of professional development (PD) designed to enhance middle school mathematics teachers’ understanding of fractions and proportions, and their teaching of these mathematical concepts to students. The PD uses an approach that engages teachers with web-based apps that allow them to test and experiment with their mathematical ideas. The apps, combined with guiding questions that challenge teachers’ thinking about fractions and proportions, serve both to promote critical thinking about the concepts and to further developing their understandings of the concepts. The researchers will use an innovative approach, topic modeling, to examine the effectiveness of each of version of the PD.

This project uses neural and behavioral measures of learning as a basis for making improvements to an immersive high school course that trains students in flexible spatial cognition and data analysis. Tracking students into college, the project measures long-term effects of improved spatial cognition resulting from the modified geospatial course curriculum.

This study will investigate factors influencing teacher change after professional learning (PL) experiences and will examine the extent to which modest supports for science and engineering teaching in grades 3-5 sustain PL outcomes over the long term, such as increases in instructional time devoted to science, teacher self-efficacy in science, and teacher use of reform-oriented instructional strategies aligned with the Next Generation Science Standards.

The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.

The project will design and research the Cultural Connections Process Model (CCPM), a place-based, culturally sustaining STEM educational resources and model that will engage Alaska Native and other high school students in STEM. The project approach is strongly informed by Indigenous knowledge systems (i.e., knowledge embedded in the cultural traditions of regional, Indigenous or local communities) and incorporates relevant arctic scientific research.

Teachers of mathematics engage in curricular reasoning as they design and interact with their students, choose curricular materials, and implement curriculum standards in the service of high-quality instruction. Currently, there is no shared measure of curricular reasoning of middle school teacher classroom decision making in mathematics. In this research project, the team develops and validates two measures of middle school teachers’ curricular reasoning in mathematics as practiced. The first measure looks at curriculum reasoning from the perspective of the teacher, the second measure attends to the perspectives of the mathematics education research community.

Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.

The project will design, develop, and test a research-based professional development (PD) approach that will ensure that teachers, and ultimately their middle-school students, have the knowledge to act in a way that promotes zero net loss of biodiversity in their communities. Through their participation in the PD, teachers will be equipped to plan for and implement NGSS-aligned instruction, facilitate student identification and understanding of biodiversity and environmental justice issues in their local community, and foster student capacity to take action. Students will come to understand that biodiversity is a global issue that they can influence at the local level, and will become empowered, in both their knowledge and their agency, to be leaders in solving biodiversity problems in their communities.

This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.

Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.

This project will design and study an online, portable mentor teacher professional development (PD) program that target mentors’ teaching and feedback skills in elementary mathematics. The project aims to (1) promote educator development by generating new knowledge about how to help mentors support teacher candidate learning; (2) broaden participation in mathematics by historically marginalized and minoritized youth, who are far more likely than their peers to be taught by a first year teacher; and (3) enhance infrastructure for research and education by generating PD materials and measures that can be used and studied at scale.

This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.

This project builds on a successful introductory computer science curriculum, called Scratch Encore, to explore ways to support teachers in bringing together—or harmonizing—existing Scratch Encore instructional materials with themes that reflect the interests, cultures, and experiences of their students, schools, and communities. In designing these harmonized lessons, teachers create customized activities that resonate with their students while retaining the structure and content of the original Scratch Encore lesson.

This project aims to meet this need by developing PreK-5, equity-oriented, field-based, interdisciplinary curricular materials that support students' socioecological reasoning and sustainable decision making. The science learning experiences will be integrated across disciplines from literacy to civic and social studies lessons. The curricular materials will be part of a science education model that facilitates family engagement in ways that transform relations between educators, families, and students' science learning. The curricular activities will be co-designed with teachers while using local nature and culture as a resource.

This project will develop and investigate mathematics language routines focused on data science topics in middle and high school. The study will investigate teachers’ use of mathematics language routines and a professional development model to support teachers’ learning. The educational integration plan in the project will build mathematics teacher expertise and create video cases to support teacher professional development.

With increased focus on STEM education for students with extensive support needs ESN, engineering practices highlight the importance of problem-solving skills (e.g., systems thinking, creativity), and engineering lessons/units may provide a viable format for systematically planned math and science instruction that naturally embeds opportunities to teach students skills promoting increased self-regulated learning. Due to lack of prior experience teaching engineering, little is known about how teachers of students with ESN scaffold instruction to build their students’ engineering practices. Thus, this project focuses on teachers’ development of engineering practices, including how teachers support their students’ development of engineering-focused behaviors and mindsets through instruction.

This project is working to develop, implement, and research the introduction of data experiences and practices into a series of interdisciplinary, middle school project-based learning modules. The project examines how interdisciplinary data education can provide opportunities for students to take more control of their own learning and develop positive identities related to data, through integration with social studies and science topics. Curriculum modules and teaching resources produced by the project serve as guides for subsequent efforts at integrating data science concepts into teaching and learning in various subject areas.

This project builds on a successful introductory computer science curriculum, called Scratch Encore, to explore ways to support teachers in bringing together—or harmonizing—existing Scratch Encore instructional materials with themes that reflect the interests, cultures, and experiences of their students, schools, and communities. In designing these harmonized lessons, teachers create customized activities that resonate with their students while retaining the structure and content of the original Scratch Encore lesson.

This project aims to meet this need by developing PreK-5, equity-oriented, field-based, interdisciplinary curricular materials that support students' socioecological reasoning and sustainable decision making. The science learning experiences will be integrated across disciplines from literacy to civic and social studies lessons. The curricular materials will be part of a science education model that facilitates family engagement in ways that transform relations between educators, families, and students' science learning. The curricular activities will be co-designed with teachers while using local nature and culture as a resource.

Teachers’ beliefs influence their instructional decisions and these decisions shape the mathematical learning opportunities for all students. This is particularly important when considering the learning opportunities for groups that have historically been marginalized in mathematics, including girls and students of color. There are few validated, mathematics-specific instruments that measure teachers’ beliefs about mathematics learning related to race, ethnicity, and gender. This project seeks to investigate teachers’ beliefs related to how they explain the systemic racial and gender differences in mathematics education outcomes by developing and validating a survey instrument and to explore how those beliefs might impact their teaching.

Covariational reasoning, or the ability to reason about relationships as quantities change together, is one way of thinking that can provide a foundation for students to build their more abstract algebraic knowledge. This research builds a foundation for integrating education and research at the intersection of students’ developing algebraic knowledge, covariational reasoning, and new educational technologies to create a new path into algebra. This path can help remove barriers that have historically restricted access to mathematics and STEM coursework and careers.

This project examines the development of statistical literacy that combines statistical reasoning and thinking. The project will use professional learning communities for teachers to learn about statistical literacy and develop learning experiences for their students. The project will engage students and teachers in finding meaningful ways to use statistical reasoning to make data-based arguments and reason about patterns they observe in society.