PS 21-31 - Investigating early observation patterns by community scientists to inform engagement and retention

Tuesday, August 8, 2023

5:00 PM – 6:30 PM PDT

Location: ESA Exhibit Hall

Presenting Author(s)

Erin F. Snyder

MS Student and Research Assistant
Chicago Botanic Garden, Northwestern University
Glencoe, United States

Coauthor(s)

ST

Sophie Taddeo

Chicago Botanic Garden, Northwestern University, United States
EA

Elsa C. Anderson

Assistant Professor
Northwestern University, Chicago Botanic Garden, Illinois, United States
EO

Emma Oschrin

Chicago Botanic Garden, Northwestern University
Glencoe, Illinois, United States
KH

Kayri Havens

Chicago Botanic Garden, Northwestern University
Glencoe, Illinois, United States

Abstract: Community science democratizes the process of scientific knowledge production. Data from community science projects are increasingly used in ecological research to broaden the spatial, temporal, and taxonomic scope of traditional datasets. When employed equitably, community science can be a tool used to support environmental justice by reducing barriers to participation in the scientific process, improving transparency of research methods, and promoting ecological literacy. Although community science platforms engage non-professional scientists, recent research indicates that biases in crowdsourced datasets can mirror the spatial and taxonomic biases found in professional surveys. To combat these biases, it is important to understand what motivates users to join and participate in community science initiatives. Due to barriers such as lack of access to demographic data or resources to conduct participant interviews, participants themselves, their participation patterns, and motivations for joining community science projects are vastly understudied. Our research assesses how the behavior of community scientists changes over time in an effort to inform recruitment and retention strategies. Our study utilizes observations of plant taxa observations conducted in the Great Lakes region recorded through Budburst, a phenology and plant-pollinator focused web platform and mobile app. First, we develop a typology of users by characterizing their first year of engagement on Budburst. Specifically, we assess user activity as well as the diversity and spatial scope of their observations. Second, we assess how user behaviors change over time by studying changes in the frequency, diversity, and spatial scope of observations. We identify which plant species and observation patterns correspond to highly engaged community science users in order to inform strategies for attracting new users. Preliminary results indicate that two Acer species are frequently the first observation recorded by new users. Additionally, diversity and spatial scope of observations made by individual users increases over time. Our findings will promote a deeper understanding of how users engage with Budburst and how these patterns change over time. Results of our study could inform recruitment strategies and programming decisions for Budburst and other community science programs, which could in turn mitigate dataset biases by broadening participation from underrepresented users and in under-observed areas. Additionally, our methods of utilizing the characteristics of observations to make inferences about user behavior could be applied to other community science platforms.