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.
Projects
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.
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 project is exploring teachers' capacity to manage student epistemic uncertainty as a pedagogical resource that supports student’s productive struggle and the development of conceptual knowledge during project-based learning instruction in middle school science classrooms.
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.
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.
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.
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 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.
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.
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.
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.
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 addresses a longstanding problem in informal science education: how to increase the likelihood of consequential STEM learning from short duration experiences such as field trips. The project seeks to harness the power and potential of visual representations (e.g., graphs, drawings, charts, maps, etc.) for enhancing learning and encouraging effective reflection during and after science learning experiences, and provide new and actionable informal science learning practices that promote engagement with visual representations and reflection, and science understandings that can be applied broadly by informal science institutions.
This project addresses a longstanding problem in informal science education: how to increase the likelihood of consequential STEM learning from short duration experiences such as field trips. The project seeks to harness the power and potential of visual representations (e.g., graphs, drawings, charts, maps, etc.) for enhancing learning and encouraging effective reflection during and after science learning experiences, and provide new and actionable informal science learning practices that promote engagement with visual representations and reflection, and science understandings that can be applied broadly by informal science institutions.
This project addresses a longstanding problem in informal science education: how to increase the likelihood of consequential STEM learning from short duration experiences such as field trips. The project seeks to harness the power and potential of visual representations (e.g., graphs, drawings, charts, maps, etc.) for enhancing learning and encouraging effective reflection during and after science learning experiences, and provide new and actionable informal science learning practices that promote engagement with visual representations and reflection, and science understandings that can be applied broadly by informal science institutions.
In this project, we examine middle-school students’ understandings of coordinate systems and frames of reference prior to examining their graph construction and interpretation. This focus allows us to design instructional materials that can support students’ graphing understandings in ways that avoid or mitigate how persistent challenges in students’ graphing understandings identified in the research literature.
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 aims to create and study an Equitable and Interactive Mathematical Modeling (EIM2) program that positions students as decision makers in their own learning. Despite the value of connecting students’ life experiences with their mathematical learning, the practical implementation of this strategy has proven challenging in a classroom setting. EIM2 addresses this issue by supporting students to engage in equitable mathematical modeling, a process of using mathematics to analyze and quantify scenarios through a lens of equity.
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 will design and research a professional development (PD) model in which elementary teachers experience integrated, place-based, culturally sustaining STEM curriculum focused on local watersheds and grounded in local Native American cultural values and knowledge. The teachers will then design and implement their own culturally relevant STEM unit, guided by the PD, which is situated within their local watershed and Indigenous 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.
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.