Module 4

When first incorporating Youth Citizen and Community Science into classroom culture and curriculum, there can be hesitation in allowing students the space to make observations and ask questions. How much is too much direction? How will I ensure students are able to produce and take ownership of quality data? Am I able to produce high quality data myself?

When beginning any YCCS project, it is important to recognize that all data collected does not need to be perfect. Not all data collected will need to be submitted. The data can be a way for classrooms to tell the story of their understanding of the environment, but that does not mean that students need to be proficient at conducting research from day one. Phew- let it go. That acknowledgement is a reminder that, when starting a YCCS project, student data may not begin as research quality, but a goal students should know they are striving towards. And just imagine how impressed with themselves they will be. After practicing, building skill, and comparing data, students will be able to determine at what point their data is of high enough quality to submit for scientific research and collection.

Once methods of collection have been determined, for your own purposes as well as those of researchers, classrooms can begin making our observations using their new tools and skill sets. With binoculars in hand, they might set off into the great wide world that is their school’s playground. By this point, students will have become increasingly aware of the biodiversity that surrounds them, but may still struggle with the accuracy of their observations. They can become aware of many species yet to be identified. It is at this point when students are able to look critically at their own data and ask themselves, are their observations accurate enough, based on evidence, supported by detail.

Students may then come to the conclusion that they needed to learn more about which (pollinator, birds, etc.) are most common in the area to help them better identify the species they were seeing. They might begin research projects, collect additional data, compare to historical data sets or even engage with the data coming from other citizen scientists.