Projects

This purpose of this project is to develop and validate a range of assessments with a focus on academic preparedness for higher education. The team will explore relevant qualities of assessments such as their differential predictive validity to ensure they are appropriate for underrepresented groups, the optimal grade level to begin assessing readiness, and measures that are most appropriate for predicting STEM-specific readiness.

With recent advances in artificial intelligence (AI), the United States needs to develop a diverse workforce with strong computational skills and the knowledge and capability to work with AI. Recent studies have raised questions about the extent to which youth are aware of AI and its application in industries of the future that may limit their interest in pursuing learning that lead toward careers in these industries. To address this challenge, learning trajectories (LTs) will be developed and researched for AI concepts that are challenging for middle and high school students. The project will design and pilot test learning activities and assessments targeting these concepts based on the LTs, offer teacher professional development on the LTs and related activities, and research the effectiveness of the LT-based activities when implemented by teachers during the regular school day.

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.

This project addresses the need for a computationally-enabled STEM workforce by equipping teachers with the skills necessary to prepare students for future endeavors as computationally-enabled scientists and citizens, and by investigating the most effective ways to provide this instruction to teachers. The project also addresses the immediate challenge presented by NGSS to prepare middle school science teachers to implement rich computational thinking experiences within science classes.

This project uses a new theoretical framework that specifies criteria for developing scientific thinking skills that include the value that people place on scientific aims, the cognitive engagement needed to evaluate scientific claims, and the scientific skills that will enable one to arrive at the best supported explanation of a scientific phenomenon. The project will work with high school biology teachers to investigate their own understanding of scientific thinking, how it can be improved through professional development, and how this improvement can translate into practice to support student learning.

SmartGraphs activities run in a web browser; there is no software to download or install. SmartGraphs allows students to interact with on-screen graphs to learn about linear equations, the motion of objects, population dynamics, global warming, or other STEM topics that use scatter plots or line graphs. Teachers and students may also use and share existing activities, which are released under a Creative Commons license (see http://www.concord.org/projects/smartgraphs#curriculum).

This project is focused on creating, testing, refining, and studying a computer-based, individualized, interactive learning system for intermediate/middle school students or by teachers in classrooms. This learning system is called Individualized Dynamic Geometry Instruction and will contain four instructional modules in geometry and measurement that reflect the recommendations of the Common Core State Standards.

This project helps teachers learn to use NSDL resources in ways that meaningfully affect their practice in STEM content areas while increasing their skills as designers of learning activities. The objectives of this three-year project are to: design and implement a teacher development model and STEM content development model; contribute teacher-designed learning activities to NSDL; and use evaluation and research to measure impact on teaching.

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.

Twelve fifth and sixth grade science teacher specialists and their students in a high needs district in Ohio are engaged in a design-based research project within a three-year professional development effort with faculty in several departments at the University of Cincinnati to study how the engineering design process can be used effectively as a pedagogical strategy in science instruction to improve student interest, learning and skill development.

This project will investigate how complex systems concepts supported by innovative curricular resources, technology applications and a comprehensive research and development structure can assist student learning in the domain of biology by providing a unifying theme across scales of time and space. The project seeks to address four areas of critical need in STEM education: biological sciences, complex systems, computational modeling, and equal access for all.

This project is conducting repeated randomized control trials of an approach to high school geometry that utilizes Dynamic Geometry (DG) software and supporting instructional materials to supplement ordinary instructional practices. It compares effects of that intervention with standard instruction that does not make use of computer drawing tools.

In this project, over 500 elementary education majors will team with engineering majors to teach engineering design to over 1,600 students from underrepresented groups. These standards-based lessons will emphasize student questioning, constructive student-to-student interactions, and engineering design processes, and they will be tailored to build from students' interests and strengths.

This is a planning effort to explore future directions and innovations related to educational design in science, technology, engineering, and mathematics education in partnership with the International Society for Design and Development in Education. The planning activity will engage a core group of ISDDE principals in the articulation and examination of design processes for the Transforming STEM Learning program at NSF with a goal of developing an agenda for further discussion and research conceptualization.

This project conducts interdisciplinary research to advance understanding of embodied learning as it applies to STEM topics across a range of current technology-based learning environments (e.g., desktop simulations, interactive whiteboards, and 3D interactive environments). The project has two central research questions: How are student knowledge gains impacted by the degree of embodied learning and to what extent do the affordances of different technology-based learning environments constrain or support embodied learning for STEM topics?

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.

Providing students with exposure to high quality computational thinking (CT) activities within science classes has the possibility to create transformative educational experiences that will prepare students to harness the power of CT for authentic problems. By building upon foundational research in human-AI partnership for classroom support and effective practices for integrating CT in science, this collaborative research project will advance understanding of how to empower teachers to lead computationally enriched science activities with adaptive pedagogical tools.

Providing students with exposure to high quality computational thinking (CT) activities within science classes has the possibility to create transformative educational experiences that will prepare students to harness the power of CT for authentic problems. By building upon foundational research in human-AI partnership for classroom support and effective practices for integrating CT in science, this collaborative research project will advance understanding of how to empower teachers to lead computationally enriched science activities with adaptive pedagogical tools.

This project develops and assesses the effectiveness of integrating three computation-based technologies into curricular modules: agent-based modeling (ABM), real-world sensing, and collaborative classroom networks. The STEM disciplines addressed are life sciences and physical sciences at middle and high school levels, specifically Evolution, Population Biology/Ecology, Kinetic Molecular Theory, and Electromagnetism.

This research investigates how state-of-the-art creative and pedagogical agents can improve students' learning, attitudes, and engagement with computer science. The project will be conducted in high school classrooms using EarSketch, an online computer science learning environments that engages learners in making music with JavaScript or Python code. The researchers will build the first co-creative learning companion, Cai, that will scaffold students with pedagogical strategies that include making use of learner code to illustrate abstraction and modularity, suggesting new code to scaffold new concepts, providing help and hints, and explaining its decisions.

Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse high schools. The goal of this project is to engage high-school students and teachers from underresourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow.

Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse high schools. The goal of this project is to engage high-school students and teachers from underresourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow.

Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse high schools. The goal of this project is to engage high-school students and teachers from underresourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow.

This project is revising and field testing six existing modules and developing, pilot testing, and field testing two engineering modules for required middle school science and mathematics classes: Catch Me if You Can! with a focus on seventh grade life science; and Creating Bioplastics targeting eighth grade physical science. Each module addresses an engineering design challenge of relevance to industries in the region and fosters the development of engineering habits of mind.

This project creates, tests and revises two-six week prototypical modules for middle school technology education classes, using the unifying themes and important social contexts of food and water. The modules employ engineering design as the core pedagogy and integrate content and practices from the standards for college and career readiness.