Projects

In this project, the research team will create a computer-mediated design environment that enables students in grades 7-10 to collaboratively explore, make connections, generate, and evaluate design ideas that address environmental science challenges. A unique feature of the project is its use of an artificial intelligent (AI) design mentor that relies on Design Heuristics, a research-based creativity tool that guides students through exploration of ideas and “learns” from students’ design processes to better assist them. The project will examine students’ perceptions of science and engineering, their ability to integrate academic and personal or community knowledge, their confidence for engaging in engineering, and their design thinking.

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.

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.

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.

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 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 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 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.

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.

CADRE is the resource network that supports researchers and developers who participate in DRK-12 projects on teaching and learning in the science, technology, engineering and mathematics disciplines. CADRE works with projects to strengthen and share methods, findings, results and products, helping to build collaboration around a strong portfolio of STEM education resources, models and technologies. CADRE raises external audiences’ awareness and understanding of the DRK-12 program, and builds new knowledge.

This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.

This project explores how to help teachers identify and support early elementary children’s emergent computational thinking. The project will engage researchers, professional development providers, and early elementary teachers (K-2) in a collaborative research and development process to design a scalable professional development experience for grade K-2 teachers. The project will field test and conduct research on the artifacts, facilitation strategies, and modes of interaction that effectively prepare K-2 teachers to learn about their students’ emergent use of computational thinking strategies.

This project focuses on supporting emerging scholars who have new ideas and approaches for approaching racial equity in their scholarship and work. The workshop, implemented as a series of sessions over the course of a year, will support early career scholars in STEM education and the learning sciences in preparing proposals to submit to the National Science Foundation.

This project will investigate the challenges, needs, and support for Historically Black Colleges and Universities (HBCUs) to succeed in applying for educational research support from the National Science Foundation (NSF), in particular the Division of Research on Learning in Informal and Formal Settings (DRL). The project will investigate what changes and/or supports would contribute to significantly increasing the number of applications and successful grant awards for STEM educational research project proposed by HBCUs.

The Learning by Evaluating (LbE) project will develop, refine, and test an educational innovation in which 9th grade students evaluate sample work as a starting point in engineering design cycles. Students will compare and discuss the quality and fit to context of completed design artifacts. Teachers will collaboratively review and refine the LbE approaches and map the LbE materials into the curriculum.

The Framework for K-12 Science Education has set forth an ambitious vision for science learning by integrating disciplinary science ideas, scientific and engineering practices, and crosscutting concepts, so that students could develop competence to meet the STEM challenges of the 21st century. Achieving this vision requires transformation of assessment practices from relying on multiple-choice items to performance-based knowledge-in-use tasks. However, these performance-based constructed-response items often prohibit timely feedback, which, in turn, has hindered science teachers from using these assessments. Artificial Intelligence (AI) has demonstrated great potential to meet this assessment challenge. To tackle this challenge, experts in assessment, AI, and science education will gather for a two-day conference at University of Georgia to generate knowledge of integrating AI in science assessment.

Understanding the impact of STEM education efforts requires researchers to have cutting-edge knowledge of advanced research methods and the ability to translate research knowledge to multiple and diverse stakeholder audiences. The Evidence Quality and Reach (EQR) Hub project will work explicitly to strengthen these two competencies through focused work with the Discovery Research PreK-12 research community. The hub will develop and implement workshops and learning opportunities for researchers in the community, convene communities of practice to discuss specific research methods, and engage in individualized consultations with DRK-12 projects.

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.

This project addresses a critical need to help middle school teachers learn to incorporate data science in their teaching. It uses an open-source platform called the Common Online Data Analysis Platform (CODAP) as a tool for teachers to learn about data science and develop resources for students’ learning. The project team will develop a framework for teachers’ knowledge of data science teaching and learning. Insights from the project will help develop effective practices for teaching data science and understanding how students learn data science.

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.

This project represents a new approach to quality assessment of K-12 science and engineering learning experiences. By updating and expanding the Dimensions of Success (DoS) observation tool initially established for informal science learning settings to middle school science and engineering classrooms (DoS-MSSE), the project will create and implement a sustainable and scalable system of support for teachers who are learning how to implement the Next Generation Science Standards (NGSS) Framework for K-12 effectively and equitably.

This conference focuses on the use of virtual/mixed reality simulation in the preparation of secondary science teachers. The conference convenes experts in simulation in teacher preparation, practicing high school teachers, and teacher candidates to engage in a design process related to mixed reality simulations. Conference attendees will identify important gaps in science teacher preparation and design prototype simulation environments for addressing those gaps.

The goal of this planning grant is to explicitly focus on broadening participation in the K-12 STEM teaching workforce, with the theory of action that diversifying the K-12 STEM teaching workforce would in the long term help more students see STEM as accessible to them and then be more likely to choose a STEM degree or career.

This project will explore PK-2 teachers' content knowledge by investigating their understanding of the design and implementation of culturally relevant computer science learning activities for young children. The project team will design a replicable model of PK-2 teacher professional development to address the lack of research in early computer science education.

The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.