This project envisions a future of work where advanced technologies provide automated, job-embedded, individualized feedback to drive professional learning of the future worker. To achieve this goal, it addresses a fundamental question: Are evaluative or non-evaluative feedback systems more effective in driving professional learning? This question will be tested on professionals where objective, fine-grained feedback is especially critical to improvement--the teaching professions. This research will be situated within English and language arts (ELA) instruction in middle and high school classrooms, where underperformance and inequality in literacy outcomes are persistent problems facing the U.S. Current methods of supporting teacher learning through feedback are sparse, cumbersome, subjective, and evaluative. Thus, a major reconceptualization is needed to provide feedback mechanisms that- meaningfully affect teacher practice and are accessible to all. In partnership with TeachFX, an industry leader in technology-enabled instructional feedback, this project will work with teachers to design and test systems of automated feedback. Insights from the study will lead to feedback systems that empower teaching professionals, generate continued professional learning, and ultimately, increase student achievement.
Projects
Teachers are extraordinarily important to student learning, but researchers have surprisingly little data about what teachers do moment-to-moment with students. What are the instructional moves and improvisational responses that characterize highly effective practice? To better understand and support U.S. K-12 STEM teachers, this Incubator project will develop a network of "tutor observatories." Tutor observatories are learning environments that record teacher engagements with students along with information about the context of the interaction. From these data, researchers will be able to gain a deeper understanding of STEM teacher practice, identify highly effective practices, and develop training data that can inform a new generation of artificially intelligent tools to support teachers and student learning.
This project investigates the STEM teacher pipeline and examine qualifications, from teacher candidates who express interest in teaching STEM through to the eventual career paths of teachers in the workforce. In doing so, the project examines how the supply of STEM teachers has changed over time, whether the supply is adequate in meeting the needs of a changing nation, the qualifications and credentials of STEM teachers, and the implications of the STEM teacher career paths for equity and serving high needs contexts and students.
Online STEM credit courses have become attractive to school leaders as a way to support students who fail STEM courses in face-to-face school year settings. However, there is little research about the processes involved in how schools make decisions regarding student credit recovery. The available research focuses solely on student results and is not definitive enough to support important policy decisions at the district level. This research brings redress to this policy dilemma.
This project contributes to advancing knowledge on STEM education focusing on societal challenges by harnessing the convergence of STEM subjects, including data science and computer science, to empower a minoritized student group—multilingual middle-school learners.
This exploratory study aims to design, implement, and test climate science and history professional learning materials and experiences for high school teachers. By leveraging existing science and history/social science materials, the program will develop curricular planning tools and lessons to help teachers integrate climate literacy into their instructional units. The goal is to provide students with the knowledge to understand and respond to the social and environmental issues associated with the climate crisis.
This project will study learning associated with elementary teachers' engagement in professional learning and elementary students' learning related to quantum science, quantum thinking, and careers. The knowledge base required for elementary teachers and students to learn quantum will be identified in order to explore and compare how elementary students and teachers conceptualize and make sense of quantum science concepts.
This project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
This project builds capacity for middle school teachers to enact and adapt integrated STEM curriculum units with their students. The units will focus on biomimicry—examining structures and functions found in nature and applying these to solve human problems, which combines science, engineering, and technology. The project enables teachers to design activities that are personally authentic to their students by supporting teachers to examine their students' assets, needs, and interests and center these during unit design.
A long-standing challenge for education and learning sciences is sharing the distinct knowledge bases of researchers and teachers with each other. The goal of this project is to support teachers, STEM coaches, and researchers in sharing that knowledge so that they can learn from one another.
This project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
This synthesis study includes a comprehensive systematic review and meta-analysis of research published since 2001 evaluating the impact of family engagement interventions on student STEM outcomes. The goal of this project is to (a) determine the effectiveness of family engagement interventions on STEM outcomes, (b) identify practices/components within interventions that are most effective for promoting STEM outcomes, and (c) reveal the extent to which the effects of family engagement interventions vary as a function of study quality and/or certain child, family, and community characteristics.
This project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
A long-standing challenge for education and learning sciences is sharing the distinct knowledge bases of researchers and teachers with each other. The goal of this project is to support teachers, STEM coaches, and researchers in sharing that knowledge so that they can learn from one another.
This project will provide rural STEM middle school teachers and career counselors professional development and the support needed to collaborate with each other and local community assets in designing, integrating, and implementing effective STEM content and career development activities. Local teams will co-develop project-based learning units that incorporate a place-based education perspective involving STEM assets, careers, and stakeholders from the local communities for middle school rural youth that intentionally infuse STEM careers in their area with STEM content.
This project will develop, enact, and study a critical climate technology journalism curriculum to support multilingual sixth grade students’ knowledge and practices in engineering. Synthesizing expertise in climate technology, communication, and multilingual education, the project will engage students in investigating, designing, and communicating critical engineering knowledge about community-based technological systems. Students will learn engineering as they construct and convey messages about climate technology in their community for an audience of family members, community groups, and civic leaders.
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.