As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches and resources for use in a variety of settings. The project will collaboratively design, test and study effective and efficient ways to develop embedded assessments (EAs) of citizen science (CS) volunteer scientific inquiry skills in order to better understand the impact of these CS experiences on volunteer scientific inquiry abilities. EAs are assessment activities that are integrated into the learning experience and allow learners to demonstrate their competencies in an unobtrusive way. The acquisition of scientific inquiry skills is an essential, even defining, characteristic of citizen science experiences that has a direct influence on data quality. Methods for assessing the direct impact of CS on volunteers' scientific inquiry skills are limited. The project will result in EA measures designed for use by diverse CS projects, strategies that CS projects can use to develop EA assessment tools, and research findings that document opportunities, supports and barriers of this innovative method across a range of CS contexts. Findings and initial resources will be shared with the broad array of stakeholders in CS through conferences, workshops, peer-reviewed publication, community websites and other relevant venues. The results of this work also have the potential to generalize to other informal science learning experiences that engage the public in science The project will address two research questions: (1) What processes are useful for developing broadly applicable EA methods or measures? and (2) What can we learn about gains in volunteers' scientific inquiry skills when citizen science organizations use EA? These will be addressed through design-based research focused on two streamlining strategies. For the reframing data validation strategy, six leaders from five established citizen science projects will conduct secondary analyses of their existing databases to uncover the skill gains of CS volunteers that are currently unexplored in their data. For the common measure strategy, ten CS projects will collaborate to create and test common EA measures of select identification-based skills. Data will be gathered through meeting notes, participant interviews and action plans, and volunteer skill gains to capture process and products of each strategy. Data will be analyzed using grounded theory, multiple process techniques, multilevel models, and repeated-measures analysis of variance. The design-based-research framework will significantly expand project impacts by jump-starting evaluation of the participating CS projects and by producing initial resources for two distinct EA strategies that have the potential to dramatically alter practice and impact citizen science efforts to ultimately enable more people to learn by contributing to the science endeavor. The project will directly equip the 15 participating citizen-science projects with authentic performance tools to assess the quality of their programing, which will expand their understanding of CS volunteer skills and help them better recruit and support their varied audiences (including rural, low-income and tribal communities).
While interest in citizen science as an avenue for increasing scientific engagement and literacy has been increasing, understanding how to effectively engage underrepresented minorities (URMs) in these projects remains a challenge. Based on the research literature on strategies for engaging URMs in STEM activities and the project team’s extensive experience working with URMs, the project team developed a citizen science model tailored to URMs that included the following elements: 1) science that is relevant to participants’ daily lives, 2) removal of barriers to participation, such as
"Have You Spotted Me? Learning Lessons by Looking for Ladybugs" is an innovative citizen science project that targets children from Native American, rural, farming, and disadvantaged communities. While most citizen science efforts target teens and adults, this project enables youth ages 5-11 to contribute to the development of a major ladybug database. Adult mentors in youth programs introduce children to topics such as ladybugs, invasive species, biodiversity, and conservation. Youth not affiliated with a program may participate independently. Project deliverables include a self-contained education program, an Internet portal and project website, a dedicated corps of volunteers, and the largest, accessible biological database ever developed. The database is made more reliable by utilizing records accompanied by an identifiable data image as a certified data point. Partners include the NY State 4-H, South Dakota State 4-H, Migrant Worker Children's Education Program, Cayuga Nature Center, Seneca Nation Department of Education Summer Programs, Seneca Nation Early Childhood Learner Centers After School Program, and the Onondaga Nation After School Program. Strategic impact will be realized through the creation of a citizen science project that provides hands-on interactions, field experiences, and accessible data that creates unique learning opportunities for youth. It is estimated that nearly 10,000 youth will be impacted by this work.
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TEAM MEMBERS:
John LoseyLeslie AlleeLouis HeslerMichael CatanguiJohn Pickering
You can use CyberTracker on a Smartphone or handheld computer to record any type of observation. CyberTracker, which requires no programming skills, allows you to customize a series of screens for your own data collection needs. Our vision is to enable you to be part of a worldwide environmental monitoring network. Our mission is to help you improve environmental monitoring by increasing the efficiency of data gathering and to improve observer reliability.