Sensing for Data Science: A Web-based Interactive Learning Platform for Next Generation Secondary Education

About This Grant

New advances in data science have paved the way for the development of transformational technologies that touch upon many aspects of daily lives, including health, transportation, and security, among others. Consequently, there is a critical need for today's students to gain an increased understanding of data science, building the workforce needed to continue data science innovations in service of society. The Sensing for Data Science (SensDS) project responds to this need through the design and development of an educational platform and instructional materials focused on the use of Cyber-Physical Human Systems for hands-on data science education. This interdisciplinary project takes place in urban and rural high schools in Alabama and uses gesture-driven radio frequency sensors to introduce 260 students and their teachers to data science concepts and processes. Specifically, the project will develop a web-based, interactive, machine learning platform, tailored to hybrid learning for grades 9-12, which will engage students with sensing + machine learning + control technology as they interact with virtual games and robots. The project involves activities that make visible how data moves across platforms in a system and then uses tools to make those patterns meaningful for students. SensDS follows a design-learn-play methodology for translating abstract data science concepts into a more easily understandable, tangible domain, enabling students to intuitively relate their movements with patterns observed in radio frequency sensor data. Using this platform and associated curricular materials, students will flexibly experience the entire data lifecycle and observe the impact of their design choices on the real-world behavior of actual systems. Connections among data, system design, and performance will be established via an easy-to-use visual user interface, allowing students to experiment, play and learn through interactive activities. This approach aims to spark student interest in science, technology, engineering, and mathematics, showing students how data science relates to everyday life and opening doors to future careers in artificial intelligence, data science, and related technologies. The primary goal of this project is to develop a web-based, interactive machine learning platform tailored and integrated into hybrid (on-site and online) curriculum for Grade 9-12 data science education, accessible to all students regardless of academic background, learning abilities, or prior knowledge. The project's specific objectives are to 1) develop integrated sensing, data science, and control functionalities within a visual user interface to make the entire data science pipeline accessible to Grade 9-12 students; 2) develop a data science instructional sequence that exploits student experimentation with Cyber-Physical Human Systems via the SensDS platform and addresses Grades 9-12 learning standards; and 3) implement and evaluate the sensor-based data science learning instructional sequence within in-person and hybrid learning environments. This project employs a learning-in-community methodology that engages high school teachers and students in participatory design research to develop technological and curricular resources to aid teachers in designing and integrating data science education into Grade 9-12 curricula, ensuring the materials are relevant, accessible, and effective. A key outcome of this project will be the development and dissemination of the open-source SensDS platform and relating curricula, which will contribute to the research and understanding of how new Cyber-Physical Human Systems technologies can enhance experiential data science education. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. 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.