This project's goals are to:
Enable participants to contribute to any or all stages of the scientific process and enhance their learning using an online citizen science platform and live bird cams.
Generate new scientific knowledge about wildlife.
Advance the understanding of effective project design for co-created online citizen-science projects at a national scale.
This poster was presented at the 2021 NSF AISL Awardee Meeting.
PocketMacro is a mobile app designed by The Human-Computer Interaction Institute at Carnegie Mellon University to help users better identify benthic macroinvertebrates commonly found in streams and other waterways. In Summer 2021, the app and other supplemental materials were highlighted during trainings for educators held at the Stroud Water Research Center.
The evaluation team from Rockman et al Cooperative (REA) surveyed and interviewed educators who participated in the summer trainings to determine what they took away from the experience and to gather feedback about the PocketMacro app
Learning to See, Seeing to Learn is a National Science Foundation-funded project to develop www.macroinvertebrates.org, a digital observation tool and set of informational resources that can supplement volunteer biomonitoring trainings and improve aquatic macroinvertebrates identification. Project researchers are interested in how trainers and volunteers use the tool, as well as how training that incorporates the tool impacts volunteers’ confidence in and accuracy around aquatic macroinvertebrates identification. In November 2018, project partner, Stroud Water Research Center, conducted a
Identifying private gardens in the U.K. as key sites of environmental engagement, we look at how a longer-term online citizen science programme facilitated the development of new and personal attachments of nature. These were visible through new or renewed interest in wildlife-friendly gardening practices and attitudinal shifts in a large proportion of its participants. Qualitative and quantitative data, collected via interviews, focus groups, surveys and logging of user behaviours, revealed that cultivating a fascination with species identification was key to both ‘helping nature’ and wider
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TEAM MEMBERS:
Nirwan SharmaSam GreavesAdvaith SiddharthanHelen AndersonAnnie RobinsonLaura Colucci-GrayAgung Toto WibowoHelen BostockAndrew SalisburyStuart RobertsDavid SlawsonRené van der Wal
In citizen science, user-centred development is often emphasised for its potential to involve participants in the development of technology. We describe the development process of the mobile app “Naturblick” as an example of a user-centred design in citizen science and discuss digital user feedback with regard to the users' involvement. We have identified three types of digital user feedback using qualitative content analysis: general user feedback, contributory user feedback and co-creational user feedback. The results indicate that digital user feedback can link UCD techniques with more
A team of experts from five institutions (University of Minnesota, Adler Planetarium, University of Wyoming, Colorado State University, and UC San Diego) links field-based and online analysis capabilities to support citizen science, focusing on three research areas (cell biology, ecology, and astronomy). The project builds on Zooniverse and CitSci.org, leverages the NSF Science Gateways Community Institute, and enhances the quality of citizen science and the experience of its participants.
This project creates an integrated Citizen Science Cyberinfrastructure (CSCI) framework that expands the capacity of research communities across several disciplines to use citizen science as a suitable and sustainable research methodology. CSCI produces three improvements to the infrastructure for citizen science already provided by Zooniverse and CitSci.org:
Combining Modes - connecting the process of data collection and analysis;
Smart Assignment - improving the assignment of tasks during analysis; and
New Data Models - exploring the Data-as-Subject model. By treating time series data as data, this model removes the need to create images for classification and facilitates more complex workflows. These improvements are motivated and investigated through three distinct scientific cases:
Biomedicine (3D Morphology of Cell Nucleus). Currently, Zooniverse 'Etch-a-Cell' volunteers provide annotations of cellular components in images from high-resolution microscopy, where a single cell provides a stack containing thousands of sliced images. The Smart Task Assignment capability incorporates this information, so volunteers are not shown each image in a stack where machines or other volunteers have already evaluated some subset of data.
Ecology (Identifying Individual Animals). When monitoring wide-ranging wildlife populations, identification of individual animals is needed for robust estimates of population sizes and trends. This use case combines field collection and data analysis with deep learning to improve results.
Astronomy (Characterizing Lightcurves). Astronomical time series data reveal a variety of behaviors, such as stellar flares or planetary transits. The existing Zooniverse data model requires classification of individual images before aggregation of results and transformation back to refer to the original data. By using the Data-as-Subject model and the Smart Task Assignment capability, volunteers will be able to scan through the entire time series in a machine-aided manner to determine specific light curve characteristics.
The team explores the use of recurrent neural networks (RNNs) to determine automated learning architectures best suited to the projects. Of particular interest is how the degree to which neighboring subjects are coupled affects performance. The integration of existing tools, which is based on application programming interfaces (APIs), also facilitates further tool integration. The effort creates a citizen science framework that directly advances knowledge for three science use cases in biomedicine, ecology, and astronomy, and combines field-collected data with data analysis. This has the ability to solve key problems in the individual applications, as well as benefiting the research of the dozens of projects on the Zooniverse platform. It provides benefits to researchers using citizen scientists, and to the nearly 1.6 million citizen scientists themselves.
This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Research on Learning in Formal and Informal Settings, within the NSF Directorate for Education and Human Resources.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
This project team will develop and test a prototype of Planet 3, a multi-media online platform to apply real world problems (e.g., pollution, overpopulation) to middle school earth and life science learning. The prototype will include videos, simulations, and games to allow opportunities for students to explore problem sets, collect and analyze data, and draw conclusions. At the end of Phase I in a pilot study with two classrooms, the researchers will examine whether the prototype functions as planned, where teachers can implement the prototype within classroom practice, and if students are engaged while examining real-world problems.
Public Participation in Scientific Research (PPSR), often referred to as crowdsourcing or citizen science, engages participants in authentic research, which both advances science discovery as well as increases the potential for participants' understanding and use of science in their lives and careers. This four year research project examines youth participation in PPSR projects that are facilitated by Natural History Museums (NHMs). NHMs, like PPSR, have a dual focus on scientific research and science, technology, engineering, and mathematics (STEM) education. The NHMs in this project have established in-person and online PPSR programs and have close ties with local urban community-based organizations. Together, these traits make NHMs appropriate informal learning settings to study how young people participate in PPSR and what they learn. This study focuses on three types of PPSR experiences: short-term outdoor events like bioblitzes, long-term outdoor environmental monitoring projects, and online PPSR projects such as crowdsourcing the ID of field observations. The findings of this study will be shared through PPSR networks as well as throughout the field in informal STEM learning in order to strength youth programming in STEM, such that youth are empowered to engage in STEM research and activities in their communities. This project is funded through Science Learning+, which is an international partnership between the National Science Foundation (NSF) and the Wellcome Trust with the UK Economic and Social Research Council. The goal of this joint funding effort is to make transformational steps toward improving the knowledge base and practices of informal STEM experiences. Within NSF, Science Learning+ is part of the Advancing Informal STEM Learning (AISL) program that seeks to enhance learning in informal environments and to broaden access to and engagement in STEM learning experiences.
The study employs observations, surveys, interviews, and learning analytics to explore three overarching questions about youth learning: 1) What is the nature of the learning environments and what activities do youth engage in when participating in NHM-led PPSR? 2) To what extent do youth develop three science learning outcomes, through participation in NHM-led citizen science programs? The three are: a) An understanding of the science content, b) identification of roles for themselves in the practice of science, and c) a sense of agency for taking actions using science? 3) What program features and settings in NHM-led PPSR foster these three science learning outcomes among youth? Based on studies occurring at multiple NHMs in the US and the UK, the broader impact of this study includes providing research-based recommendations for NHM practitioners that will help make PPSR projects and learning science more accessible and productive for youth. This project is collaboration between education researchers at University of California, Davis and Open University (UK), and Oxford University (UK) and citizen science practitioners, educators, and environmental scientists at three NHMs in the US and UK: NHM London, California Academy of Sciences, and NHM Los Angeles.
One common barrier to STEM engagement by underserved and underrepresented communities is a feeling of disconnection from mainstream science. This project will involve citizen scientists in the collection, mapping, and interpretation of data from their local area with an eye to increasing STEM engagement in underrepresented communities. The idea behind this is that science needs to start at home, and be both accessible and inclusive. To facilitate this increased participation, the project will develop a network of stakeholders with interests in the science of coastal environments. Stakeholders will include members of coastal communities, academic and agency scientists, and citizen science groups, who will collectively and collaboratively create a web-based system to collect and view the collected and analyzed environmental information. Broader impacts include addressing the STEM barriers to those who reside in the coastal environment but who are underrepresented in STEM education, vocations and policy-making. These include tribal communities (racial and ethnic inclusion), fishery communities (inclusion of communities of practice), and rural communities without direct access to colleges or universities. This project will create a physical, a social, and a virtual, environment where all participants have an equal footing in the processes of "doing science" - the Coastal Almanac. The Almanac is simultaneously a network of individuals and organizations, and a web-based repository of coastal data collected through the auspices of the network. During the testing phase, the researchers will implement the "rules of engagement" through multiple interaction pathways in the growing Coastal Almanac network: increases in rigorous citizen science, development of specific community-scientist partnerships to collect and/or use Almanac data, development of K-12 programs to collect and/or use Almanac data. The proposed work will significantly scale up citizen science and community-based science programs on the West Coast, broadening participation by targeting members of coastal communities with limited access to mainstream science, including participants from non-STEM vocations, and Native Americans. The innovation of the Coastal Almanac is in allowing the process of deepening involvement in science, and through that process increasing agency of community members to be bona fide members of the science team, to evolve organically, in the manner dictated by community members and the situation, rather than a priori by the project team and mainstream science. The project has the potential in the long-term to increase participation in marine science education, workforce, and policy-making by underrepresented groups resident in the coastal environment. Contributions by project citizen scientists will also provide valuable data to mainstream science and to resource management efforts.
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TEAM MEMBERS:
Julia ParrishMarco HatchSelina Heppell
Through the NSF Innovation Corps for Learning Program, (I-Corps L), this project will develop ways to enable the SciStarter program to extend the promise of citizen science by connecting millions of citizen scientists with scientists in need of their help through formal and informal research projects. Citizen science is a fast growing field that engages the public in scientific inquiry through data collection projects and environmental monitoring using sensors, mini spectrometers, water testing kits and other tools. A challenge for the citizen science community has been access to the tools required to collect the types of data needed in citizen science projects. SciStarter facilitates broader participation in citizen science by reducing the barrier for volunteers to identify, acquire, and use the right scientific tools and instruments for each project. This I-Corps for Learning project will develop approaches to enable SciStarter to provide a larger number of citizen scientists with easier access to required and recommended instruments needed for meaningful participation in citizen science projects.
SciStarter aims to provide a holistic solution to the needs of citizen scientists that includes projects, support, and products such as training materials and consulting. SciStarter can be a catalyst in citizen science by connecting people to opportunities to engage and in lowering barriers to public participation in scientific research while creating a hybrid academic-consumer sustainability model. A central focus of this current effort will be establishing a sustainable and scalable means of enabling citizen scientists to obtain equipment and instruments in an efficient and cost-effective manner. The project will make use of elements already in place to expand the engagement of citizen scientists in new or multiple projects, to empower citizens in the process of citizen science, and to provide a useful, scalable and sustainable solution for scientists leading citizen science research projects. The extension of SciStarter will set the stage for greater inclusion of previously marginalized groups in citizen science activities and will extend to all forms of public engagement in science.
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Scientists and researchers from fields as diverse as oceanography and ecology, astronomy and classical studies face a common challenge. As computer power and technology improve, the sizes of data sets available to us increase rapidly. The goal of this project is to develop a new methodology for using citizen science to unlock the knowledge discovery potential of modern, large data sets. For example, in a previous project Galaxy Zoo, citizen scientists have already made major contributions, lending their eyes, their pattern recognition skills and their brains to address research questions that need human input, and in so doing, have become part of the computing process. The current Galaxy Zoo project has recruited more than 200,000 participants who have provided more than 100 million classifications of galaxies from the Sloan Digital Sky Survey. This project builds upon early successes to develop a mode of citizen science participation which involves not only simple "clickwork" tasks, but also involves participants in more advanced modes of scientific thought. As part of the project, a symbiotic relationship with machine learning tools and algorithms will be developed, so that results from citizen scientists provide a rich training set for improving algorithms that in turn inform citizen science modes of participation. The first phase of the project will be to develop a portfolio of pilot projects from astrophysics, planetary science, zoology, and classical studies. The second phase of the project will be to develop a framework - called the Zooniverse - to facilitate citizen scientists. In particular, research and machine-learning communities will be engaged to identify suitable projects and data sets to integrate into Zooniverse.
The ultimate goal with the Zooniverse is to create a sustainable future for large-scale, internet-based citizen science as part of every researcher?s toolkit, exemplifying a new paradigm in computational thinking, tapping the mental resources of a community of lay people in an innovative and complex manner that promises a profound impact on our ability to generate new knowledge. The project will engage thousands of citizens in authentic science tasks leading to a better public understanding of science and also, by the engagement of students, leading to interest in scientific careers.
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TEAM MEMBERS:
Geza GyukPamela GayChristopher LintottMichael RaddickLucy FortsonJohn Wallin