Designing Experiential Learning with Beehive Sensor Data into a Non-Relational Database Course
This project intends to study how experiential learning and collaboration with an on-campus club impact the ability of students in a non-relational database course to better understand characteristics of sensor data, and, consequently, to better be able to architect and deploy systems for storing and analyzing that data. It will combine course curriculum with the club’s activities to benefit both the students in the course and the club members, providing experiential learning for all involved.
Partnering with the beekeeping club on campus, plans are underway to install several hive sensors, enabling us to compare the health of the hives and to compare the impact of various interventions, such as insulating hives.
The data obtained from the sensors will be incorporated in real-time into a non-relational database course for the first time during the spring 2025 semester. The course explores how the Internet of Things, and more specifically sensors, have dramatically increased the volume, velocity, and variety of data that’s collected. Having extensive, live data will give the students a real-world perspective on the nature of these datasets, allowing them to better architect systems to accommodate that data.
This project, developed through the lens of the Scholarship of Teaching and Learning, benefits the students in my database course, but it also provides an excellent learning experience for the members of the beekeeping club, as they’re able to implement sensors they’ve otherwise only read about and, from the sensor readings, better determine the health of the bees and any necessary interventions.
