Transdisciplinary science integrates knowledge across STEM disciplines to research complex challenges such as climate science, genetic engineering, or ecology. In this project, teachers and students will design smart greenhouses by connecting electronic sensors that can detect light or other environmental data to microcontrollers that can activate devices that water plants and regulate other environmental factors such as temperature or light. This activity brings together engineering, computer science, and horticulture. Working across urban and rural contexts, the project will engage teachers in professional development as they adopt and adapt instructional materials to support their students in learning across disciplines as they build smart greenhouses.
Projects
STEM learning is a function of both student level and classroom level characteristics. Though research efforts often focus on the impacts of classrooms level features, much of the variation in student outcomes is at the student level. Hence it is critical to consider individual students and how their developmental systems (e.g., emotion, cognition, relational, attention, language) interact to influence learning in classroom settings. This is particularly important in developing effective models for personalized learning. To date, efforts to individualize curricula, differentiate instruction, or leverage formative assessment lack an evidence base to support innovation and impact. Tools are needed to describe individual-level learning processes and contexts that support them. The proposed network will incubate and pilot a laboratory classroom to produce real-time metrics on behavioral, neurological, physiological, cognitive, and physical data at individual student and teacher levels, reflecting the diverse dynamics of classroom experiences that co-regulate learning for all students.
As STEM education researchers work to improve STEM teaching and learning in schools and districts across the nation, rural communities are often overlooked. There is a definite critical need for STEM education research focused on rural communities. Rural schools typically have less funding for STEM programs, have trouble recruiting and retaining quality STEM teachers, and have less access to STEM learning opportunities. Yet, rural communities possess an abundance of ingenuity, resourcefulness, and collective problem-solving skills. This project works to address this need by bringing together researchers, rural educators, and workforce leaders in rural communities to support the mutual exchange of knowledge and learning around pressing problems in rural K-12 STEM education, understanding rural ingenuity within teaching STEM, and STEM education's connection with the local workforce.
This project will investigate how recent advances in artificial intelligence can support computational thinking development within an innovative biology curriculum in which students design and program a robotic arm controlled by their own muscle activity. Specifically, the project will focus on how AI tools can assist students in designing algorithms and translating them into computer programs.