Projects

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.

The Common Core State Standards for Mathematics (CCSSM) problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests.

This study addresses two open questions in mathematics education and teacher learning research related to groupwork monitoring. Using contemporary information visualization techniques and open-source tools, alongside a video-based coaching activity, teachers will a) analyze classroom video records featuring group math discussions and b) uncover and investigate their specific interactions with student groups as well as their overall approach to this important phase of their lessons. Through these tools, teachers will develop strategic and integrated understandings of effective groupwork monitoring strategies. As a result of this work, teachers and researchers will be able to better connect teachers’ monitoring choices to students’ peer-to-peer math talk.

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.

This project aims to support teachers to engage their students in mathematical problem posing (problem-posing-based learning, or P-PBL). P-PBL is a powerful approach to the teaching and learning of mathematics, and provides students with opportunities to engage in authentic mathematical practices.

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.

Using high school statewide longitudinal data from Maryland from 2012-2022, this study will first document who has taught STEM-CTE courses over this period. After exploring the teaching landscape, the study will then explore whether qualifications (i.e., education, credentials, teaching experience) of teachers in STEM-CTE high school courses were associated with their students’ success.

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.

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.

Widely-adopted science education standards have expanded expectations for students to learn science research processes. To address these needs, the project will research and develop curricular materials and classroom practices that teachers can use to bring authentic science into their classes and engage students as active science researchers. The project, called MothEd, will focus on the study of moths, which are well-suited to the project’s goal of having students conduct authentic scientific investigations.

This research project aims to enhance elementary teacher education in science and computational thinking pedagogy through the use of Culturally Relevant Teaching, i.e. teaching in ways that are relevant to students from different cultural and linguistic backgrounds. The project will support 60 elementary teachers in summer professional development and consistent learning opportunities during the school year to learn about and enact culturally relevant computational thinking into their science instruction.

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.

This research project aims to enhance elementary teacher education in science and computational thinking pedagogy through the use of Culturally Relevant Teaching, i.e. teaching in ways that are relevant to students from different cultural and linguistic backgrounds. The project will support 60 elementary teachers in summer professional development and consistent learning opportunities during the school year to learn about and enact culturally relevant computational thinking into their science instruction.

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 brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

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 the ways in which thoughtfully designed simulations can provide preservice teachers with formative assessment opportunities that serve as a complement to, or alternative to as needed, feedback derived from field placement contexts. A set of simulations will be designed with a focus on eliciting and interpreting student thinking. These simulations will be used with preservice teachers in three elementary teacher preparation programs of varying size and demographics.

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 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.

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 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.

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 brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

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.