Projects

This Exploratory Project is developing two prototype innovative instructional modules for grades 9-12 modules, and testing them extensively for usability and impact. These modules will emphasize the role of mathematics and computer science in planning for sustainability.

This project addresses the need for new electronic materials and associated processes for applications in microelectronics, optics and sensors. Materials growth methods, electrical, chemical and physical characterization, pattern generation, device fabrication, and theory/modeling are invoked to ensure holistic and interdisciplinary approaches to the development and investigation of novel materials and devices.

Education researchers, practitioners, industry representatives, and policymakers are increasingly committed to making engineering education accessible to all K-12 students and teachers. This project is designed to learn what type of collaborative infrastructure would best support NSF awardees in engaging in the innovative, synergistic research, development, and dissemination activities that will enable engineering to fulfill this important role in K-12 teaching and learning. 

This project is using data from interviews with 160 K-12 students and 20 adults to describe common understandings and progressions of development for negative number concepts and operations. The project is motivated by the widely acknowledged finding that students have difficulty mastering key concepts and skills involved in work with integers.

The focus of this conference is to carefully examine past and current research with an eye toward improving its impact on practice and to create concrete steps that could shape the nature and impact of mathematics education research.

EDC is developing a high school capstone course in linear algebra. Student resources contain a core semester that develops two- and three-dimensional geometry using vectors and that treats matrix algebra and its applications to geometry; a semester of material that completes a typical undergraduate course (exploring bases, determinants and eigentheory); and 5 stand-alone modules that develop applications of this core to mathematics, engineering, science, and other STEM fields.

This project will develop an online curriculum module for high school biology. It has three main goals: 1) Demonstrate how a story like malaria can integrate the teaching of multiple science topics and facilitate the diffusion of biodiversity and evolution across curriculum; 2) Model for students how to think like a scientist and show science as worthy of career consideration; and 3) Provide versatile multimedia as an alternative to textbook-centered instruction.

The core research questions of the project are: (1) What is the nature of high-leverage student thinking that teachers have available to them in their classrooms? (2) How do teachers use student thinking during instruction and what goals, orientations and resources underlie that use? (3) What is the learning trajectory for the teaching practice of productively using student thinking? and (4) What supports can be provided to move teachers along that learning trajectory?

The core research questions of the project are: (1) What is the nature of high-leverage student thinking that teachers have available to them in their classrooms? (2) How do teachers use student thinking during instruction and what goals, orientations and resources underlie that use? (3) What is the learning trajectory for the teaching practice of productively using student thinking? and (4) What supports can be provided to move teachers along that learning trajectory?

LOCUS (Levels of Conceptual Understanding in Statistics) is an NSF Funded DRK12 project (NSF#118618) focused on developing assessments of statistical understanding. These assessments will measure students’ understanding across levels of development as identified in the Guidelines for Assessment and Instruction in Statistics Education (GAISE). The intent of these assessments is to provide teachers and researchers with a valid and reliable assessment of conceptual understanding in statistics consistent with the Common Core State Standards (CCSS).

This project designs, develops and tests a digital gaming environment for high school students that fosters and measures science learning within alternate reality games about saving Earth's ecosystems. Players work together to solve scientific challenges using a broad range of tools including a centralized web-based gaming site and social networking tools, along with handheld smart-phones, and an avatar-based massively multiplayer online environment. The game requires players to contribute to a scientific knowledge building community.

This project will investigate the role of collaborative design in supporting teachers' professional growth around productive epistemic discourse in high school science classrooms. The project will examine an activity that is often used for the generation of curricular materials, collaborative design, and explore its promise in fostering biology teachers' professional growth as part of a larger professional development experience focused on epistemic practice.

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 is developing teaching modules that engage high school students in learning and using mathematics. Using geo-spatial technologies, students explore their city with the purpose of collecting data they bring back to the formal classroom and use as part of their mathematics lessons. This place-based orientation helps students connect their everyday and school mathematical thinking. Researchers are investigating the impact of place-based learning on students' attitudes, beliefs, and self-concepts about mathematics in urban schools.

In this project, researchers will collaborate to enhance understanding of influences on learning, and improve teaching and learning in high school and middle school STEM classes. They will leverage the latest tools for data processing and many different streams of data that can be collected in technology-rich classrooms to (1) identify classroom factors that affect learning and (2) explore how to use that data to automatically track development of students' understanding and capabilities over time.

This project will develop and test two curriculum units on the topic of evolution for high school general biology courses, with one unit focusing primarily on human case studies to teach evolution and one unit focusing primarily on case studies of evolution in other species. The two units will be compared to examine how different approaches to teaching evolution affect students and teachers.

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.

This project is testing the effectiveness of the 'Learning Assistant Model' for recruiting, preparing, and retaining STEM K-12 teachers by developing a suite of survey instruments that can be used by researchers interested in testing the effectiveness of teacher preparation programs, course transformations, or conceptual or pedagogical knowledge. It focuses on teacher certification programs,K-12 contexts and students' experiences in STEM departments and the role of STEM research faculty in preparing future teachers.

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.

This is a large-scale, cross-sectional, and longitudinal study aimed at understanding and supporting the teaching of science and engineering practices and academic language development of middle and high school students (grades 7-10) with a special emphasis on English language learners (ELLs) and a focus on biotechnology.

This project provides a virtual environment in which high school physics students can engage in the cutting edge science of studying exoplanets. Using online telescopes and learning software, students gain a deeper understanding of science inquiry, including reasoning from models, gathering assessing, and interpreting authentic data, and drawing conclusions from multiple line of evidence. The research advances our understanding of ways to increase students' knowledge of data literacy.

This project is evaluating existing knowledge about STEM teachers in professional learning communities (PLCs), both prospective teachers and classroom teachers across grades K-12. It will comprehensively synthesize peer-reviewed research but will also examine additional types of knowledge that influence the field. The project methods adapt those of Knowledge Management and Dissemination project, funded by NSF MSP and seeks to further advance the scope and rigor of knowledge synthesis.

The objective of this study is to examine the impact of ITEAMS intervention strategies on student persistence in high school STEM course-taking and career expectations, and the value that students place on STEM careers.

This is a quasi-experimental study of the effects of attending an inclusive STEM high school in three key geographic regions and comparing outcomes for students in these schools with those of their counterparts attending other types of schools in the same states. The study's focus is on the extent to which inclusive STEM high schools contribute to improved academic outcomes, interests in STEM careers, and expectations for post secondary study.