Data literacy is a major component of the National Research Council’s Next Generation Science Standards (NGSS), and successful methods for increasing student data literacy are currently being evaluated. One such method employs a placed-based approach, wherein students analyze data from their local ecosystem. We present a case study of how local data can be incorporated into NGSS-aligned curricula by exploring data on polychlorinated biphenyls (PCBs) in Hudson River fish. The Hudson River is one of the largest US Superfund sites in the nation because of PCB pollution, and the Hudson River fish dataset is among the largest datasets on fish contamination in the world. We developed a data-focused curriculum made up of three lessons on PCBs in fish, and recruited nine teachers to pilot the curriculum in their classrooms in the Hudson Valley. In these inquiry-based lessons, students evaluate how PCB contamination differs across time, space, and between species in the Hudson River. We collected pre- and post-surveys from students, asking students about PCBs in particular and movement of contaminants in ecosystems in general, as well as student comprehension of data analysis concepts such as variability and overall comfort working with data. We also collected feedback forms from participating teachers.
Results/Conclusions
Both students and teachers responded positively to the curriculum. Teachers reported that they found the curriculum useful for connecting students to their local environment, teaching about contaminants, and strengthening student data skills. Many teachers continue to use the curriculum beyond the pilot program by incorporating it into their yearly teaching plans. Students reported in post-surveys that participating in the curriculum positively influenced their understanding of the risks associated with PCBs, and what factors influence PCB levels in fish. Additionally, students provided more accurate descriptions of where you would find PCBs in the Hudson River ecosystem after the lessons, indicating a deeper understanding of ecological concepts such as bioaccumulation. Students also reported that the curriculum had a positive influence on their level of comfort working with data sets in general, and increased their understanding of the concept of variability. Here we demonstrate that using an inquiry-based approach focusing on local data was effective in increasing student understanding of contaminants in general and PCBs in particular, as well as increasing student comfort in working with data. This placed-based, data-driven methodology can be applied to many science topics to increase student data literacy, in accordance with the Next Generation Science Standards.