Projects

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 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.

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 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.

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.

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 connects interdisciplinary researchers and experts from four tribal nation partners to develop and implement an in-service teacher professional certificate program that integrates Indigenous Knowledge into STEM teaching. This multi-sited teacher professional development model will enroll K-12 teachers in four different Native-serving regions of the rural West into a 12-month certificate program that combines Indigenous science, Coupled Human and Natural Systems, and Land education concepts into an experiential learning cycle with local and broad study of learning with the Land. The project will add knowledge about the transferability of local epistemologies and practices and national science standards within four specific Indigenous contexts and expand space for tribal-lead professional development to transform teacher classroom practice.

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.

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.

Students of color must have access to robust and meaningful opportunities to learn science in classrooms that center their assets and humanity. This project aims to cultivate such spaces through designing and studying teacher professional learning focused on pedagogical practices that engage students of color meaningfully in science learning. These practices leverage students’ assets to foster growth in science and scientific habits of mind. This project will support pre-service and practicing teachers in developing tools for practice and reflection that focus on equity and highlighting the assets of students of color in secondary science.

This project is developing curricular materials that utilize best teaching practices in improving student understanding of statistics and data science for use in high school Algebra I, Algebra II, and Geometry courses.  Although teachers are encouraged to integrate statistics and data science in these kinds of high school courses, teachers do not have sufficient access to resources to accomplish this effectively. The distinctive feature of these curricular materials is the use of simulation-based inference methods, data visualization, and the entire statistical investigation process to improve students’ understanding of the relevance and power of statistics because these approaches are central to statistical thinking and practice.

This project supports school-based science teachers and students in conducting community-based science research on the causes and effects of extreme heat/urban islands in racially and ethnically diverse communities. Teachers will participate in professional learning experiences that support their development of content knowledge, scientific research practices, and critical pedagogies needed to design and implement research projects in their classroom. Students will identify locally-relevant issues related to this phenomenon, conduct investigations to explore the issue, share their findings through arts-based community narratives, and advocate for change. This project will broaden access to empowering youth-centered approaches that support learning and identity construction in science.

Building on the team's prior research from early in the pandemic, this project team will continue to collect data from families and aims to understand parents’ perspectives on the educational impacts of COVID-19 by leveraging a nationally representative, longitudinal study, the Understanding America Study (UAS). The study will track educational experiences during the spring and summer of 2022 and into the 2022-23 school year. The team will analyze student and family overall and for key demographic groups of interest as schooling during the pandemic continues. This RAPID project allows critically important data to continue to be collected and contribute to continued understanding of the impacts of and responses to the pandemic by American families.

This project advances the understanding of teaching and learning of algebra in grades 6 through 12 by using a methodology that leverages the cumulative power of an analysis of many studies on a topic. This work will synthesize results aggregated from 40 years of research in the field of mathematics education and develop a unified framework to inform parents, students, teachers, other educators, and researchers.

This study will further the field's understanding of the role that science teachers play in adapting their instruction during a public health crisis, how they address emergent ideas throughout the unfolding of the pandemic, and the impacts that the pandemic has had on science teachers themselves.

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.

The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs. The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.

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.

The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs. The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.

The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs. The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.

The project will develop and research an innovative model for rural science teacher professional development via technology-mediated lesson study (TMLS). This approach supports translating professional learning into classroom practice by developing a technology-based, social support system among rural teachers.

High school students in many rural school districts have limited access to advanced STEM coursework and advanced technologies, including high-speed Internet. Rural school districts face difficulties in recruiting and retaining STEM teachers. In many cases, rural STEM teachers need additional training and support. The project will identify these, and other barriers rural teachers face and create professional development for teachers.

The goal of this project is to study the design and development of community-centered, job-embedded professional development for classroom teachers that supports bias reduction. The project team will partner with three school districts serving racially, ethnically, linguistically, and socio-economically diverse communities, for a two-year professional development program. The aim is to reduce bias through: analyzing and designing mathematics teaching with colleagues, students, and families to create classrooms and schools based on community-centered mathematics; engaging in anti-bias teaching routines; and building relationships with parents, caretakers, and community members.