The Year in ISE is a slidedoc designed to track and characterize field growth, change and impact, important publications, and current topics in ISE in 2018. Use it to inform new strategies, find potential collaborators for your projects, and support proposal development. Scope This slidedoc highlights a selection of developments and resources in 2018 that were notable and potentially useful for the informal STEM education field. It is not intended to be comprehensive or exhaustive, nor to provide endorsement. To manage the scope and length, we have focused on meta analyses, consensus reports
This CAISE report is designed to track and characterize sector growth, change and impact, important publications, hot topics/trends, new players, funding, and other related areas in Informal STEM Education (ISE) in 2017. The goal is to provide information and links for use by ISE professionals, science communicators, and interested stakeholders who want to discover new strategies and potential collaborators for project and proposal development. Designed as a slide presentation and divided into sectors, it can be used modularly or as a complete report. Each sector reports on research, events
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 proposed project broadens the utility of Public Participation in Scientific Research (PPSR) approaches, which include citizen science, to support new angles in informal learning. It also extends previous work on interactive data visualizations in museums to encompass an element of active contribution to scientific data. To achieve these goals, this project will develop and research U!Scientist (pronounced `You, Scientist!')--a novel approach to using citizen science and learning research-based technology to engage museum visitors in learning about the process of science, shaping attitudes towards science, and science identity development. Through the U!Scientist multi-touch tabletop exhibit, visitors will: (1) interact with scientific data, (2) provide interpretations of data for direct use by scientists, (3) make statements based on evidence, and (4) visualize how their data classifications contribute to globe-spanning research projects. Visitors will also get to experience the process of science, gaining efficacy and confidence through these carefully designed interactions. This project brings together Zooniverse, experts in interactive design and learning based on large data visualizations in museums, and leaders in visitor experience and learning in science museums. Over fifty thousand museum visitors are expected to interact annually with U!Scientist through this effort. This impact will be multiplied by packaging the open-source platform so that others can easily instantiate U!Scientist at their institution.
The U!Scientist exhibit development process will follow rapid iterations of design, implementation, and revision driven by evaluation of experiences with museum visitors. It will involve close collaboration between specialists in computer science, human-computer interaction and educational design, informal science learning experts, and museum practitioners. The summative evaluation will be based on shadowing observations, U!Scientist and Zooniverse.org logfiles (i.e., automated collection of user behavior metrics), and surveys. Three key questions will be addressed through this effort: Q1) Will visitors participate in PPSR activities (via the U!Scientist touch table exhibit) on the museum floor, despite all the distractions and other learning opportunities competing for their attention? If so, who engages, for how long, and in what group configurations? Q2) If visitors do participate, will they re-engage with the content after the museum visit (i.e., continue on to Zooniverse.org)? Q3) Does engaging in PPSR via the touch table exhibit--with or without continued engagement in Zooniverse.org after the museum visit--lead to learning gains, improved understanding of the nature of science, improved attitudes towards science, and/or science identity development?
The mixed methods randomized experimental study assessed a model of engagement and education that examined the contribution of SciGirls multimedia to fifth grade girls’ experience of citizen science. The treatment group (n = 49) experienced 2 hours of SciGirls videos and games at home followed by a 2.5 hour FrogWatch USA citizen science session. The control group (n = 49) experienced the citizen science session without prior exposure to SciGirls. Data from post surveys and interviews revealed that treatment girls, compared to control girls, demonstrated significantly greater interest in their
Learning to See, Seeing to Learn: A Sociotechnical System Supporting Taxonomic Identification Activities in Volunteer-Based Water Quality Biomonitoring is an Innovations in Development proposal to further develop and study a cyber-enhanced informal learning environment to support observational practices and classification skills in a citizen science context. In particular, we focus on the taxonomic ID bottleneck that hampers the acquisition of high-caliber biotic data needed for volunteer-based water quality monitoring efforts.
This poster was presented at the 2014 AISL PI Meeting in Washington, DC. It describes a project that will expand the functions and applications of FieldScope, a web-based science information portal currently supported by the National Geographic Society (NGS). The goal is to create a single, powerful infrastructure for Public Participation in Science Research (PPSR) projects that any organization can use to create their own project and support their own community of participants.
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National Geographic SocietyMary Ford
The Cornell Lab of Ornithology is creating a new type of interactive, question-driven, online bird-identification tool called "Merlin," along with associated games, social networking tools, and other media. Unlike existing bird-identification guides, which are based on traditional taxonomic keys written by scientists, Merlin uses machine learning algorithms and crowd-sourced data (information provided by thousands of people) to identify birds and improve Merlin's performance with each interaction. The tool will help millions of people identify birds and participate in a collective effort to help others. The Crowd ID project will make it easier for people to discover the names of birds, learn observation and identification skills, find more information, and appreciate Earth's biodiversity. The summative evaluation plan is measuring increases in participants' knowledge, engagement, and skills, as well as changes in behavior. Impacts on participants will be compared to a control group of users not using Merlin. Merlin tools will be integrated into the Cornell Lab's citizen science and education projects, which reach more than 200,000 participants, schoolchildren, and educators across the nation. Merlin will be broadly adapted for use on other websites, social networking platforms, exhibits, mobile devices, curricula, and electronic field guides. Once developed, Merlin can be modified to identify plants, rocks, and other animals. Merlin will promote growth of citizen science projects which depend on the ability of participants to identify a wide range of organisms.
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.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative resources for use in a variety of settings. This project will develop and study a cyber-enhanced informal learning environment to improve observational practices and classification skills among citizen scientists. The project will focus on the taxonomic identification skills needed by volunteers to provide high-quality data for water quality monitoring of local streams, lakes, estuaries, wetlands, and ground water resources. To make the task of identifying freshwater insects easier and more engaging, the project will develop an innovative educational resource, the Macroinvertebrate Identification Training Environment, that will use zoomable high-resolution images, interactive media, and annotations of diagnostic features to improve perceptual skills. The goal is to increase the confidence and accuracy of volunteers engaged in identification tasks, while also increasing the reliability and quality of the data they are generating for purposes of scientific research and conservation efforts. This interdisciplinary design research and development project will use networked gigapixel image technology to create a visual environment where users can move seamlessly from full panoramic views of macroinvertebrates to extreme close-ups, with embedded text, images, graphics, audio, and video at various locations and zoom levels. This system will be developed in concert with a cognitive apprenticeship training model designed through a series of design studies. The design studies will be conducted over a two-year period and will include examination of the distinguishing features of various biomonitoring programs, reviews of existing training materials and strategies, expert performance analysis of professional entomologists, and development of user interface features. Project developers will collaborate with five regional volunteer biomonitoring organizations to engage a diverse set of volunteers in the design process, including rural populations, older adults, urban youth, and the trainers who support them. The project work will consist of four integrated strands of activity: design-based learning research, creation of an entomological teaching collection, cyberplatform development, and the external evaluation of the training system. The resulting Macroinvertebrate Identification Training Environment will be evaluated in terms of its impacts on volunteer accuracy, confidence, and engagement in taxonomic classification activities related to macroinvertebrates. The impacts of the learning system on trainers and volunteer biomonitoring organizations will also be examined.