Projects

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 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.

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 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.

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 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.

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 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.

This project will develop a set of educative resources, assessment tools and teacher professional development (PD) activities to support teachers in developing knowledge of CS standards and improving their instructional pedagogy. Teachers will learn to use formative assessments related to these standards to determine student understanding. Improved CS instruction that is responsive to the needs and challenges of the student population is particularly critical in school districts with a large population of students who are typically underserved and under-represented in computer science. The project, a partnership between SRI International and the Milwaukee Public School District, will provide professional development experiences tied to standards instead of a specific curriculum in order to support diverse teachers teaching a variety of computer science curricula using different programming languages. Teachers will receive training via a combination of virtual webinars and face-to-face instruction. Teachers will have opportunities to evaluate their own teaching and measure their students' progress towards the standards.

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 project will study five elementary STEM schools from across the U.S. that are inclusive of students from underrepresented groups in order to determine what defines these schools and will use an iterative case study replication design to study the design and implementation of five exemplary eSTEM schools with the goal of developing a logic model that highlights the commonalities in core components and target outcomes across the schools, despite the different school contexts.

Artificial intelligence (AI) is transforming numerous industries and catalyzing scientific discoveries and engineering innovations. To prepare for an AI-ready workforce, young people must be introduced to core AI concepts and practices early to develop fundamental understandings and productive attitudes. Neural networks, a key approach in AI development, have been introduced to secondary students using various approaches. However, more work is needed to address the interpretability of neural networks and human-machine collaboration in the development process. This exploratory project will develop and test a digital learning tool for secondary students to learn how to interpret neural networks and collaborate with the algorithm to improve AI systems. The learning tool will allow students to interact with complex concepts visually and dynamically. It will also leverage students’ knowledge and intuition of natural languages by contextualizing neural networks in natural language processing systems.

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.

This project will study a model of pre-service teacher preparation that is designed to to increase teachers' and students' skills and confidence with computational thinking and develop teachers as designers of inclusive learning environments to promote computational thinking. The project will engage elementary (grades K-5) pre-service teachers (who are concurrently involved in school-based teacher preparation programs) as facilitators in an existing family technology program called Family Creative Learning (FCL).

This project will create a portable training system that can be easily deployed in middle grades (5th-7th grade) as a prototype for increasing students' spatial reasoning skills. The project will study gender differences in spatial reasoning and examine how learning experiences can be designed to develop spatial skills using Minecraft as a platform.

This project will address the need for engineering resources by applying an innovative pedagogy called Imaginative Education (IE) to create middle school engineering curricula. In IE, developmentally appropriate narratives are used to design learning environments that help learners engage with content and organize their knowledge productively. This project will combine IE with transmedia storytelling.

This project will address the need for engineering resources by applying an innovative pedagogy called Imaginative Education (IE) to create middle school engineering curricula. In IE, developmentally appropriate narratives are used to design learning environments that help learners engage with content and organize their knowledge productively. This project will combine IE with transmedia storytelling.

This project investigated the professional development needed to make teachers comfortable teaching with multi-user simulations and communications that students use every day. The enactment with OpenSim (an open source, modular, expandable platform used to create simulated 3D spaces with customizable terrain, weather and physics) also provides an opportunity to demonstrate the level of planning and preparation that go into fashioning modules with all selected cyber-enabled cognitive tools framed by constructivism, such as GoogleEarth and Biologica.

This project explores the potential of information and communications technologies (ICT) as cognitive tools for engaging students in scientific inquiry and for enhancing teacher learning. A comprehensive professional development program of over 240 hours, along with follow-up is used to determine how teachers can be supported to use ICT tools effectively in classroom instruction to create meaningful learning experiences for students, reduce the gap between formal and informal learning, and improve student learning outcomes.

This Culturally Responsive Indigenous Science project seeks to advance this knowledge base through research and by catalyzing new approaches to Indigenous science, technology, engineering, and mathematics (ISTEM) learning. Using an ISTEM focused model, the project will develop, test, and implement a culturally responsive land-based curriculum that integrates Western science, multimodal technologies and digital tools, and Native American tribal knowledge, cultures and languages to investigate and address local environmental science and sustainability concerns.

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 will develop a cloud-based platform that enables high school students, teachers, and scientists to conduct original neuroscience research in school classrooms.

This award is for the funding of a regional conference to study the future of STEM education, the impact of underrepresented and disadvantaged groups with regards to STEM, and STEM job growth and workforce development in a regional, as opposed to a national, context.

This five-year project investigates how to provide continuous assessment and feedback to guide students' understanding during science inquiry-learning experiences, as well as detailed guidance to teachers and administrators through a technology-enhanced system. The assessment system integrates validated automated scorings for students' written responses to open-ended assessment items into the "Web-based Inquiry Science Environment" (WISE) program.

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.