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. In this exploratory Change Makers project, the Concord Consortium will develop, test, and evaluate a citizen science program that leverages innovative technology, such that youth engage directly with energy issues through scientific inquiry. The project will create the Infrared Street View, a citizen science program that aims to produce a thermal version of Google's Street View using an affordable infrared camera attached to a smartphone. The infrared camera serves as a high-throughput data acquisition instrument that collects thousands of temperature data points each time a picture is taken. Youth will collect massive geotagged thermal data that have considerable scientific and educational value for visualizing energy usage and improving energy efficiency at all levels. The Infrared Street View program will provide a Web-based platform for youth and anyone interested in energy efficiency to view and analyze the aggregated data to identify possible energy losses. By sharing their scientific findings with stakeholders, youth will make changes to the way energy is being used. The project will start with school, public, and commercial buildings in selected areas where performing thermal scan of the buildings and publishing their thermal images for educational and research purposes are permitted by school leaders, town officials, and property owners. In collaboration with high schools and out-of-school programs in Massachusetts, this project will conduct pilot-tests with approximately 200 students.
To contribute to advancing learning, the study will probe three research questions: 1) Under what circumstances can technology bridge out-of-school and classroom science learning and improve learning on both sides? 2) To what extent can unobtrusive assessment based on data mining support research and evaluation of student learning in out-of-school settings? and 3) To what extent can instructional intelligence built into the app used in the program help students learn in out-of-school programs and improve the quality of data they contribute to the citizen science project? Data sources for investigating these questions include students' interaction data with the app logged behind the scenes and the images they have taken, as well as results based on traditional assessments from a small number of participants. Throughout the project, staff will widely disseminate project products and findings through the Internet, science fairs, conferences, publications, and partner networks. An eight-member Advisory Board consisting of cleantech experts, science educators, and educational researchers will oversee and evaluate this project.
This article explores the roots of the citizen science movement. It uses several ongoing projects as examples, including the Audubon's Christmas Bird Count, research into bee colony collapse, and nanotechnology programs. The article concludes by providing guidance for the development of future citizen science projects, focusing on an increased dialogue between traditional and informal science education.
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TEAM MEMBERS:
Michael MuellerDeborah TippinsLynn Bryan
This poster was presented at the April 2011 workshop, Engaging and Learning for Conservation. It describes the eBirding citizen science program, including its methods, findings and conclusions.
This poster was presented at the April 2011 workshop, Engaging and Learning for Conservation. It describes the eBirding citizen science program, including its methods, findings and conclusions.
The University of Pittsburgh's Center for Learning in Out-of-School Environments (UPCLOSE), the Carnegie Museum of Natural History, and the Robotics Institute at Carnegie Mellon University are building an open access cyberlearning infrastructure that employs super high-resolution gigapixel images as a tool to support public understanding, participation, and engagement with science. Networked, gigapixel image technology is an information and communication technology that creates zoomable images that viewers can explore, share, and discuss. The technology presents visual information of scientifically important content in such detail that it can be used to promote both scientific discovery and education. The purpose of the project is to make gigapixel technology accessible and usable for informal science educators and scientists by developing a robotic imaging device and online services for the creation, storage, and sharing of billion-pixel images of scientifically important content that can be analyzed visually. Project personnel are conducting design activities, user studies, and formative evaluation studies to support the development of a gigapan technology platform for demonstration and further prototyping. The project builds on and leverages existing technologies to provide informal science education organizations use of gigapixel technology for the purpose of facilitating three types of activities that promote participatory learning by the public--Public Understanding of Science activities; Public Participation in Scientific Research activities; and Public Engagement in Science activities. The long-terms goals of the work are to (1) create an accessible database of gigapixel images that informal science educators can use to facilitate public-scientist interactions and promote participatory science learning, (2) characterize and demonstrate the affordances of networked gigapixel technologies to support socially-mediated, science-focused cyberlearning experiences, (3) generate knowledge about how gigapixel technology can enable three types of learning interactions between scientists and the public around visual data, and (4) disseminate findings that describe the design, implementation, and evaluation of the gigapixel platform to support participatory science learning. The project\'s long-term strategic impacts include guiding the design of high-resolution images for promoting STEM learning in both informal and formal settings, developing an open educational resource and science communication platform, and informing informal science education professionals about the use and effectiveness of gigapixel images in promoting participatory science learning by the public.
This report summarizes evaluative findings from a project titled “What Curiosity Sounds Like: Discovering, Challenging, and Sharing Scientific Ideas” (a.k.a.: “Discovery Dialogues”). The project, a Full-Scale development project funded by the National Science Foundation as part of its Advancing Informal Science Learning (AISL) program, explored new ways to actively engage both lay and professional audiences, and foster meaningful communication between scientists and the general public. Appendix includes survey and interview questions.