Developing Model‐Building as a Scientific Practice in Collaborative Citizen Science

Abstract

Core Ideas Citizen scientists learned how to develop sound methods to rule out plausible explanations through the use of models. Citizen scientists engaged in increased levels of discussion about models following project participation. Developing models may help prepare citizen scientists for independent endeavors. Citizen science programs pose excellent opportunities for science learning through volunteer engagement in authentic science projects, often with scientists. In this article, we share data on whether the development, discussion, and revision of models resulted in an improved description of scientific practices. We engaged individuals in a collaborative citizen science project where individuals use online resources to pose locally based research questions and use modeling practices to design research. These individuals also gathered data to support or refute their models. Project leaders were interviewed before and after project participation to determine the extent to which ideas about scientific practices have changed. We found that these individuals developed a greater capacity to independently ask and answer questions related to successful research design.

Impact of computer modeling on learning and teaching systems thinking

“…Educators have leveraged computer modeling to develop students' representational skills, content knowledge, and engagement in scientific practices to enhance causal thinking (Damelin et al, 2017; Jordan et al, 2018). To explore the affordances of computer modeling, researchers have examined students' written work, think‐aloud protocols when interacting with tools, and interviews (Damelin et al, 2017; Novak & Krajcik, 2019; Rosenberg & Lawson, 2019; Wilensky & Resnick, 1999).…”

“…Computer modeling may help enrich systems thinking by highlighting the central phenomena of a system (Damelin, Krajcik, Mcintyre, & Bielik, 2017; Dickes, Sengupta, Farris, & Basu, 2016; Jordan et al, 2018) and deepening students' argumentation around systems mechanisms (Damelin et al, 2017; Rosenberg & Lawson, 2019). Computer tools, such as data logging systems, graphing tools, simulation, and modeling environments, may also influence learning by affording changes in classroom interactions (Kim, Hannafin, & Bryan, 2007; Maor & Taylor, 1995).…”