Sense-making with data through the process of visualization—recognizing and constructing meaning with these data—has been of interest to learning researchers for many years. Results of a variety of data visualization projects in museums and science centers suggest that visitors have a rudimentary understanding of and ability to interpret the data that appear in even simple data visualizations. This project supports the need for data visualization experiences to be appealing, accommodate short and long-term exploration, and address a range of visitors’ prior knowledge. Front-end evaluation
This commentary introduces a preliminary conceptual framework for approaching putative effects of scholarly online systems on collaboration inside and outside of academia. The first part outlines a typology of scholarly online systems (SOS), i.e., the triad of specialised portals, specialised information services and scholarly online networks which is developed on the basis of nine German examples. In its second part, the commentary argues that we know little about collaborative scholarly community building by means of SOS. The commentary closes with some remarks on further research questions
This paper contributes a theoretical framework informed by historical, philosophical and ethnographic studies of science practice to argue that data should be considered to be actively produced, rather than passively collected. We further argue that traditional school science laboratory investigations misconstrue the nature of data and overly constrain student agency in their production. We use our “Data Production” framework to analyze activity of and interviews with high school students who created data using sensors and software in a ninth-grade integrated science class. To understand the
African American and Latinx youth are often socialized towards athletic activity and sports participation, sometimes at the expense of their exploration of the range of potential career paths including those in the science, technology, engineering, and mathematics (STEM) fields. This project will immerse middle school youth in the rapidly growing world of sports data analytics and build their knowledge of statistics concepts and the data science process. The project will focus on the STEM interests and knowledge development of African American and Latinx youth, an underrepresented and underserved group in STEM. Researchers will explore the ways youths' social identities can and should serve as bridges towards future productive academic and professional identities including those associated with STEM learning and the STEM professions. The outcomes of the project will advance knowledge in promoting elements of informal learning experiences that build adolescents' motivation and persistence for productive participation in STEM courses and careers. This project is funded by the Advancing Informal STEM Learning program (AISL), which seeks to advance new approaches to and evidence-based understanding of the design and development of STEM learning opportunities for the public in informal environments, and the Innovative Technology Experiences for Students and Teachers program (ITEST), which funds projects that leverage innovative uses of technologies to prepare diverse youth for the STEM workforce, with a focus on broadening participation among underrepresented and underserved groups in STEM fields.
Over a three-year period, 250 middle school learners in the West Baltimore, Maryland and Hyattsville, Maryland areas will engage in three main learning activities: Summer Camp (three weeks), Sports Day Saturdays, and a Spring Summit. Through a partnership between the University of Maryland and Coppin State University, the project will utilize resources in multiple departments and units across both universities, and engage with youth sports leagues such as the American Athletic Union (AAU) to support participants' engagement in the data science process including collection of raw data, exploration of data, development of models, visualization, communication, and reporting of data, and data-driven decision making. Furthermore, youth participants will attend local AAU, college, and professional sporting events, and interact with members of coaching staffs to better understand the ways performance data technologies are utilized to inform recruitment and team performance. The mixed-methods research agenda for this project is guided by three main questions: (1) What elements of the project's model are most successful at supporting congruence of adolescents' academic identity, including STEM identity and social identity including athletic identity? (2) What elements support adolescents' motivation, and persistence for productive participation in current and future STEM courses? (3) To what extent did the project appear to influence participants' perceptions of their future professions? At multiple points throughout the experience, participants will complete surveys designed to document and assess statistics and data science knowledge; interest in STEM careers; academic, social and athletic identity development; and STEM course taking patterns. Researchers will also observe project activities, interview a focal group of participants, and survey participants' parents to identify elements of learning experiences that encourage and support adolescents' interest in STEM disciplines and STEM professions. The project team will develop conceptual and pedagogical frameworks that support middle school youth' engagement and interest in science, engineering, technology, and mathematics through repurposing spaces where these youths frequent. A major outcome of the project will be workforce preparation and offers a promising approach for encouraging youth to persist along STEM pathways, which may ultimately result in broadened participation in STEM workforces.
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.
The Sustainability Teams Empower and Amplify Membership in STEM (S-TEAMS), an NSF INCLUDES Design and Development Launch Pilot project, will tackle the problem of persistent underrepresentation by low-income, minority, and women students in STEM disciplines and careers through transdisciplinary teamwork. As science is increasingly done in teams, collaborations bring diversity to research. Diverse interactions can support critical thinking, problem-solving, and is a priority among STEM disciplines. By exploring a set of individual contributors that can be effect change through collective impact, this project will explore alternative approaches to broadly enhance diversity in STEM, such as sense of community and perceived program benefit. The S-TEAMS project relies on the use of sustainability as the organizing frame for the deployment of learning communities (teams) that engage deeply with active learning. Studies on the issue of underrepresentation often cite a feeling of isolation and lack of academically supportive networks with other students like themselves as major reasons for a disinclination to pursue education and careers in STEM, even as the numbers of underrepresented groups are increasing in colleges and universities across the country. The growth of sustainability science provides an excellent opportunity to include students from underrepresented groups in supportive teams working together on problems that require expertise in multiple disciplines. Participating students will develop professional skills and strengthen STEM- and sustainability-specific skills through real-world experience in problem solving and team science. Ultimately this project is expected to help increase the number of qualified professionals in the field of sustainability and the number of minorities in the STEM professions.
While there is certainly a clear need to improve engagement and retention of underrepresented groups across the entire spectrum of STEM education - from K-12 through graduate education, and on through career choices - the explicit focus here is on the undergraduate piece of this critical issue. This approach to teamwork makes STEM socialization integral to the active learning process. Five-member transdisciplinary teams, from disciplines such as biology, chemistry, computer and information sciences, geography, geology, mathematics, physics, and sustainability science, will work together for ten weeks in summer 2018 on real-world projects with corporations, government organizations, and nongovernment organizations. Sustainability teams with low participation by underrepresented groups will be compared to those with high representation to gather insights regarding individual and collective engagement, productivity, and ongoing interest in STEM. Such insights will be used to scale up the effort through partnership with New Jersey Higher Education Partnership for Sustainability (NJHEPS).
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TEAM MEMBERS:
Amy TuiningaAshwani VasishthPankaj Lai
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.
The American Museum of Natural History, in association with several NOAA entities, will be creating a suite of media products employing visualization of Earth-observation data as well as associated professional development programs to expand educational experiences in informal science institutions nationwide. Interactive versions of the visualizations will also be disseminated via the AMNH website. Visualization assets will be distributed to NOAA for utilization on climate.gov and Science on a Sphere. The creation of training programs and educational materials for informal education professionals will enhance the experience and efficacy of the data visualizations as tools to understand and build stewardship of Earth systems.
Increasingly, the prosperity, innovation and security of individuals and communities depend on a big data literate society. Yet conspicuously absent from the big data revolution is the field of teaching and learning. The revolution in big data must match a complementary revolution in a new kind of literacy, through a significant infusion of STEM education with the kinds of skills that the revolution in 21st century data-driven science demands. This project represents a concerted effort to determine what it means to be a big data literate citizen, information worker, researcher, or policymaker; to identify the quality of learning resources and programs to improve big data literacy; and to chart a path forward that will bridge big data practice with big data learning, education and career readiness.
Through a process of inquiry research and capacity-building, New York Hall of Science will bring together experts from member institutions of the Northeast Big Data Innovation Hub to galvanize big data communities of practice around education, identify and articulate the nature and quality of extant big data education resources and draft a set of big data literacy principles. The results of this planning process will be a planning document for a Big Data Literacy Spoke that will form an initiative to develop frameworks, strategies and scope and sequence to advance lifelong big data literacy for grades P-20 and across learning settings; and devise, implement, and evaluate programs, curricula and interventions to improve big data literacy for all. The planning document will articulate the findings of the inquiry research and evaluation to provide a practical tool to inform and cultivate other initiatives in data literacy both within the Northeast Big Data Innovation Hub and beyond.
The Environmental Scientist-in-Residence Program will leverage NOAA s scientific assets and personnel by combining them with the creativity and educational knowledge of the pioneer hands-on science center. To do this, the program will embed NOAA scientists in a public education laboratory at the Exploratorium. Working closely with youth Explainers, exhibit developers, and Web and interactive media producers at the Exploratorium, NOAA scientists will share instruments, data, and their professional expertise with a variety of public audiences inside the museum and on the Web. At the same time the scientists will gain valuable skills in informal science communication and education. Through cutting-edge iPad displays, screen-based visualizations, data-enriched maps and sensor displays, and innovative interactions with visitors on the museum floor, this learning laboratory will enable NOAA scientists and Exploratorium staff to investigate new hands-on techniques for engaging the public in NOAA s environmental research and monitoring efforts.
C-RISE will create a replicable, customizable model for supporting citizen engagement with scientific data and reasoning to increase community resiliency under conditions of sea level rise and storm surge. Working with NOAA partners, we will design, pilot, and deliver interactive digital learning experiences that use the best available NOAA data and tools to engage participants in the interdependence of humans and the environment, the cycles of observation and experiment that advance science knowledge, and predicted changes for sea level and storm frequency. These scientific concepts and principles will be brought to human scale through real-world planning challenges developed with our city and government partners in Portland and South Portland, Maine. Over the course of the project, thousands of citizens from nearby neighborhoods and middle school students from across Maine’s sixteen counties, will engage with scientific data and forecasts specific to Portland Harbor—Maine’s largest seaport and the second largest oil port on the east coast. Interactive learning experiences for both audiences will be delivered through GMRI’s Cohen Center for Interactive Learning—a state-of-the-art exhibit space—in the context of facilitated conversations designed to emphasize how scientific reasoning is an essential tool for addressing real and pressing community and environmental issues. The learning experiences will also be available through a public web portal, giving all area residents access to the data and forecasts. The C-RISE web portal will be available to other coastal communities with guidance for loading locally relevant NOAA data into the learning experience. An accompanying guide will support community leaders and educators to embed the interactive learning experiences effectively into community conversations around resiliency. This project is aligned with NOAA’s Education Strategic Plan 2015-2035 by forwarding environmental literacy and using emerging technologies.
For decades, particle physicists have been using open access archives of preprints, i.e. research papers shared before the submission to peer reviewed journals. With the shift to digital archives, this model has proved to be attractive to other disciplines: but can it be exported? In particle physics, archives do not only represent the medium of choice for the circulation of scientific knowledge, but they are central places to build a sense of belonging and to define one's role within the community.
Online knowledge production sites do not rely on isolated experts but on collaborative processes, on the wisdom of the group or “crowd”. Some authors have argued that it is possible to combine traditional or credentialled expertise with collective production; others believe that traditional expertise's focus on correctness has been superseded by the affordances of digital networking, such as re-use and verifiability. This paper examines the costs of two kinds of “crowdsourced” encyclopedic projects: Citizendium, based on the work of credentialled and identified experts, faces a recruitment