A Learning Ecosystem for Teaching High School Students Machine Learning Concepts and Data Science Skills in Healthcare and Medicine

About This Grant

Healthcare is rapidly changing into a multidisciplinary field. Data science and artificial intelligence (AI) have become integral for healthcare and medical services. Machine Learning (ML), a branch of AI, is broadly applicable for developing predictive models that drive research, development and healthcare practices. Unintentional bias within the datasets and computer programs used for ML creates healthcare outcomes which benefit some people more than others. This project will develop an innovative and inclusive learning and teaching ecosystem for high school students. The ecosystem consists of educational agencies and teachers, cross-disciplinary expertise from data scientists and medical clinicians, community members and college students from diverse background as mentors. Authentic cross-cultural discussions amongst community members and students will be a key component of students’ learning experience. The ecosystem will provide a data science and ML laboratory course and an annual datathon. Computer science teachers will facilitate the course, and will also receive professional development in problem-based data science approaches. Students in the course will explore student-led, inquiry-based strategies on how to navigate and visualize large healthcare sets using the same programming languages and tools that data scientists use. During the datathon, students will team with their local community members and Science, Technology, Engineering, and Mathematics (STEM) teachers to solve authentic data-driven healthcare issues which are important and personal to them. Community members will share their experiences to ensure all voices are heard. Datathon participants will be introduced to culturally-responsive methods. The project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST), which seeks to engage underrepresented students in technology-rich learning environments, including skills in data literacy, and increase students’ knowledge and interest in information and communication technology (ICT) careers. During the project period, researchers will develop and study a semester-long program that engages up to 1000 Rhode Island high school students, with an emphasis on recruiting racial minorities and young women from 12 Title 1 schools. The researchers will investigate how students engage in the program and datathon, the usability and sustainability of this program, and the enactment of the innovative learning ecosystem. The following questions will guide this study: 1) How do the data laboratory and datathon contribute to student learning and efficacy in data science, and their interest in data science and healthcare careers? 2) What are teachers’ perspectives about the usability and effectiveness, including challenges, of the materials, curriculum, and supports? 3) How do teachers take up and enact the activities and tools to support student learning and interests in data science? Researchers will collect and analyze data using mixed methods, including data from a digital learning platform, surveys, interviews, assessments, and observations. The outcome will include a novel pedagogy for teaching high school students about rapidly evolving technologies. Deliverables will consist of annual professional development for the teachers; a public website for all Rhode Island district leaders, teachers, and parents; a vetted data science and ML laboratory course; and designs of the multidisciplinary, cross-cultural datathon. These will be freely shared and promoted online, presented at professional conferences, and published as research articles in peer-reviewed literature. 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.