Lowering the Barriers to Data Science: Using Sensor-based Investigations in the Science Classroom

Incorporating data science into K-12 science classrooms presents a significant challenge for teachers. This article advocates for an accessible approach, detailing how sensor-based, physical computing investigations provide a manageable entry point for both educators and students. We focus on a 9th-grade biology teacher’s implementation of a unit where students used microcontrollers to build environmental sensors and engage with data. This hands-on method moves beyond preexisting datasets, allowing students to experience authentic data collection, analysis, and the critical process of debugging. From this case study, we identify five key themes for integration: Creating a Low Floor for Teacher Entry, Data Science Experiences, Incorporating Debugging, Data Science Conversations, and Data Science Connections. This framework illustrates how sensor-based inquiry fosters critical discussions on data literacy and connects scientific concepts to students’ local communities, ultimately lowering the barrier for meaningful data science engagement.