Projects

This project will investigate the professional development supports needed for teaching bioinformatics at the high school level. The project team will work with biology and mathematics teachers to co-design instructional modules to engage students with core bioinformatics concepts and computational literacies, by focusing on local community health issues supported through mobile learning activities. The overarching goal of the project is to help create an engage population of informatics-informed students who are capable of critically analyzing information and able to solve local problems related to their health and well-being.

The production of news stories and student-oriented instruction in the classroom are designed to increase student learning of STEM content through student-centered inquiry and reflections on metacognition. This project scales up the PBS NewsHour Student Reporting Labs (SRL), a model that trains teens to produce video reports on important STEM issues from a youth perspective.

As a result of the COVID-19 pandemic, schools across much of the U.S. have been closed since mid-March of 2020 and many students have been attempting to continue their education away from schools. Student experiences across the country are likely to be highly variable depending on a variety of factors at the individual, home, school, district, and state levels. This project will use two, nationally representative, existing databases of high school students to study their experiences in STEM education during the COVID-19 pandemic. The study intends to ascertain whether students are taking STEM courses in high school, the nature of the changes made to the courses, and their plans for the fall. The researchers will identify the electronic learning platforms in use, and other modifications made to STEM experiences in formal and informal settings. The study is particularly interested in finding patterns of inequities for students in various demographic groups underserved in STEM and who may be most likely to be affected by a hiatus in formal education.

The aim of this project is to examine opportunity structures provided to students by inclusive STEM-focused high schools, with an emphasis on studying schools that serve students from underrepresented groups. The project is studying inclusive STEM-focused high schools across the United States to determine what defines them. The research team initially identified ten candidate critical components that define STEM-focused high schools and is refining and further clarifying the critical components through the research study.

This project recruited high school African American males to begin preparation for science, technology, engineering and mathematics teaching careers. The goal of the program was to recruit and prepare students for careers in secondary mathematics and science teaching thus increasing the number of African Americans students in STEM. The research will explore possible reasons why the program is or is not successful for recruiting and retaining students in STEM Teacher Education programs  

Through this project, the North Carolina State University Data Science Academy will identify the key success components of a model for the recruitment and mentoring of a diverse cohort of postdoctoral fellows who will enter their professions with expertise in data science education research. This model is intended to train and support scholars who have differing levels of experience and strengths in STEM, STEM education, education research, or data science.

The project will develop modules for grades 9-12 that integrate mathematics, computing and science in sustainability contexts. The project materials also include information about STEM careers in sustainability to increase the relevancy of the content for students and broaden their understanding of STEM workforce opportunities. It uses summer workshops to pilot test materials and online support and field testing in four states. 

This project will develop a modified virtual world and accompanying curriculum for middle school students to help them learn to more deeply understand ecosystems patterns and the strengths and limitations of experimentation in ecosystems science. The project will build upon a computer world called EcoMUVE, a Multi-User Virtual Environment or MUVE, and will develop ways for students to conduct experiments within the virtual world and to see the results of those experiments.

Despite growing interest in supporting the integration of computational thinking (CT) in elementary education, there is not an agreed-upon definition of CT that is developmentally appropriate for early childhood, nor is there a clear understanding of how young children’s CT develops and which kinds of instructional approaches and practices truly support the development of CT. Early elementary educators need feasible research-based, developmentally appropriate CT curricula. This project will contribute to this critical STEM educational need by working with a design team of 5 elementary teachers to develop a research-based integrated mathematics and CT curriculum.

This project aims to develop, implement, and evaluate an Internet of Things (IoT) based educational curriculum and technology that provides grades 9-12 students with Computer Science (CS) and Software Engineering (SE) education.

This project builds and tests applications tied to the school curriculum that integrate the sciences with mathematics, computational thinking, reading and writing in elementary schools. The investigative core of the project is to determine how to best integrate computing across the curriculum in such a way as to support STEM learning and lead more urban children to STEM career paths.

This is a continuing research project that supports (1) creation of what are termed "ink inscriptions"--handwritten sketches, graphs, maps, notes, etc. made on a computer using a pen-based interface, and (2) in-class communication of ink inscriptions via a set of connected wireless tablet computers. The primary products are substantiated research findings on the use of tablet computers, inscriptions, and networks in 4th/5th grade classrooms as well as models for teacher education and use.

This project will provide a virtual environment for completing the Food, Energy, and Water (FEW) graduate student experience. The proposed work facilitates a transition from interdisciplinary to transdisciplinary training of existing faculty and current graduate students through a virtual resource center to help develop systematic processes for interdisciplinary thinking about large societal problems, especially those at the nexus of food, energy, and water.

The Graphing Research on Inquiry with Data in Science (GRIDS) project will investigate strategies to improve middle school students' science learning by focusing on student ability to interpret and use graphs. GRIDS will undertake a comprehensive program to address the need for improved graph comprehension. The project will create, study, and disseminate technology-based assessments, technologies that aid graph interpretation, instructional designs, professional development, and learning materials.

The project will create opportunities for teachers to develop programming content knowledge and new understandings of the creative possibilities in computer science education, thereby increasing opportunities for students to develop conceptual and creative fluency with programming.

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students.

The project will develop and research a new Mixed Reality environment (MR), called GEM-STEP, that leverages play and embodiment as resources for integrating computational modeling into the modeling cycle as part of science instruction for elementary students.

This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.

This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.

The project will provide the opportunity for upper elementary students to learn computer science and build strong collaboration practices. Leveraging the promise of virtual learning companions, the project will collect datasets of collaborative learning for computer science in diverse upper elementary school classrooms; design, develop, and iteratively refine its intelligent virtual learning companions; and generate research findings and evidence about how children collaborate in computer science learning and how best to support their collaboration with intelligent virtual learning companions.

The project will provide the opportunity for upper elementary students to learn computer science and build strong collaboration practices. Leveraging the promise of virtual learning companions, the project will collect datasets of collaborative learning for computer science in diverse upper elementary school classrooms; design, develop, and iteratively refine its intelligent virtual learning companions; and generate research findings and evidence about how children collaborate in computer science learning and how best to support their collaboration with intelligent virtual learning companions.

This project will design and study new learning environments integrating mathematical and computational thinking. The project will examine how to design learning modules that place mathematics concepts. By exploring how different kinds of designs support learning and engagement, the project will establish a set of design principles for supporting mathematical and computational thinking.

This project will explore PK-2 teachers' content knowledge by investigating their understanding of the design and implementation of culturally relevant computer science learning activities for young children. The project team will design a replicable model of PK-2 teacher professional development to address the lack of research in early computer science education.

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.