Exploring Physiological Computing Education in the Alabama Black Belt

University Of Alabama Tuscaloosa, Tuscaloosa AL

Investigators

Abstract

Physiological computing systems have the potential to benefit society through wearable technologies such as smart watches, electronic textile clothing, and brain-computer interfaces in general. Currently, most work at the intersection of computer science education and physiological computing focuses on using physiological technology to augment learning experiences or predict performance. There is a lack of research investigating ways to enable K-12 students in acquiring the knowledge and skills needed to design and build future technologies and applications that leverage physiological sensors. This project will design, develop, and implement an educational physiological computing learning tool, and evaluate the tool's impact on upper secondary student's acquisition of computational thinking skills. The proposed work will provide the computer science education community field with foundational research on how best to leverage novel physiological sensing technologies within K-12 education. In addition to contributing findings to the broader research community, the PI team will build a summer outreach program that exposes high school students from the Alabama Black-Belt (ABB) to novel brain-computer interface sensing technologies. As a result of the powerful innovation and application of computing in STEM disciplines, the STEM+C program supports research and development of interdisciplinary and transdisciplinary approaches to the integration of computing within STEM teaching and learning for preK-12 students in both formal and informal settings. This pilot project will advance the integration of physiological sensing and data processing with computational thinking. Researchers will use a user-centered approach to identify effective designs for educational physiological computing tools. This includes studies that address knowledge gaps related to students' and educators' attitudes and understandings of novel physiological computing technology. Researchers will conduct semi-structured user interviews with Alabama Black Belt Exploring Computer Science (ECS) students and educators to advance knowledge regarding their perceptions and mental models of physiological sensing technologies. Insights gained from these interviews will inform the iterative design of pilot low-fidelity prototypes. Qualitative and quantitative data on students' experiences with each prototype will be collected during user experiments. Feedback gained during the low-fidelity prototype studies will guide the development of design solutions. The project will employ hybrid computer programming approaches such as data-flow and block-based programming for the learning tool development. User studies with students will be used to evaluate the tool influence on students' patterns of computational practice including incremental and iterative programming, testing and debugging, abstracting and modularization, computational perspectives of expressing and questioning, and knowledge of physiological computing systems. This project will contribute a web-based educational physiological computing tool designed for K-12 education. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.