This project explored the impact of an active aquaponics project-based learning program. The purpose of this case study was to assess students’ perceptions, attitudes, and behaviors towards science, technology, engineering, and mathematics (STEM) careers. Two students of different ages, educational backgrounds, and out-of-school experiences were observed while constructing small aquaponics systems. Students were engaged in the construction of a backyard aquaponics system (i.e., constructivist learning environment). Under supervision of Kentucky State University aquaculture scientists, student participants designed and constructed a self-regulating flow valve (automatic bell siphon), worked to troubleshoot their system, and made sure it was working properly.    

The study employed a qualitative methods approach to explore students’ perceptions, attitudes, and behaviors. Qualitative data were collected from field observation and one-on-one interviews. Five emergent positive outcomes were found throughout the design, construction, and operation of the students’ systems: 1) students were able to contribute their own experience and perspectives to the project; 2) students developed critical thinking skills; 3) students gained a sense of pride and self-satisfaction; 4) students showed focus and determination to engage in the project; and 5) students were motivated to engage in the project from start to finish.   

Results demonstrated that the program engaged learners in real-world problem solving and decision-making situations while working collaboratively. Overall, this project shows how hands-on, project-based STEM learning activities in aquaculture/aquaponics can build students’ confidence in STEM and produce positive learning outcomes. These opportunities can be implemented with traditional teaching strategies in efforts to deepen students’ knowledge and create enduring experiences that may last a lifetime. The next steps will be to introduce these methods to a larger number of students, in a classroom setting for example, to make the results more generalizable.