U!Scientist is an in-gallery touch table adaptation of the popular online citizen science project Galaxy Zoo. Taking advantage of the social opportunities in a museum setting, the project aims not only to enhance visitors’ science self-efficacy but also to encourage visitors to discuss their choices with friends and family.
This poster was presented at the 2019 NSF AISL Principal Investigators Meeting.
Supported by the National Science Foundation, the Global Soundscapes! Big Data, Big Screens, Open Ears project employs a variety of informal learning experiences to present the physics of sound and the new science of soundscape ecology. The interdisciplinary science of soundscape ecology analyzes sounds over time in different ecosystems around the world. The major components of the Global Soundscapes project are an educator-led interactive giant-screen theater show, group activities, and websites. All components are designed with both sighted and visually impaired students in mind. Multimedia
The Space and Earth Informal STEM Education (SEISE) project, led by the Arizona State University with partners Science Museum of Minnesota, Museum of Science, Boston, and the University of California Berkeley’s Lawrence Hall of Science and Space Sciences Laboratory, is raising the capacity of museums and informal science educators to engage the public in Heliophysics, Earth Science, Planetary Science, and Astrophysics, and their social dimensions through the National Informal STEM Education Network (NISE Net). SEISE will also partner on a network-to-network basis with other existing coalitions and professional associations dedicated to informal and lifelong STEM learning, including the Afterschool Alliance, National Girls Collaborative Project, NASA Museum Alliance, STAR_Net, and members of the Association of Children’s Museums and Association of Science-Technology Centers. The goals for this project include engaging multiple and diverse public audiences in STEM, improving the knowledge and skills of informal educators, and encouraging local partnerships.
In collaboration with the NASA Science Mission Directorate (SMD), SEISE is leveraging NASA subject matter experts (SMEs), SMD assets and data, and existing educational products and online portals to create compelling learning experiences that will be widely use to share the story, science, and adventure of NASA’s scientific explorations of planet Earth, our solar system, and the universe beyond. Collaborative goals include enabling STEM education, improving U.S. scientific literacy, advancing national educational goals, and leveraging science activities through partnerships. Efforts will focus on providing opportunities for learners explore and build skills in the core science and engineering content, skills, and processes related to Earth and space sciences. SEISE is creating hands-on activity toolkits (250-350 toolkits per year over four years), small footprint exhibitions (50 identical copies), and professional development opportunities (including online workshops).
Evaluation for the project will include front-end and formative data to inform the development of products and help with project decision gates, as well as summative data that will allow stakeholders to understand the project’s reach and outcomes.
As the world is increasingly dependent upon computing and computational processes associated with data analysis, it is essential to gain a better understanding of the visualization technologies that are used to make meaning of massive scientific data. It is also essential that the infrastructure, the very means by which technologies are developed for improving the public's engagement in science itself, be better understood. Thus, this AISL Innovations in Development project will address the critical need for the public to learn how to interpret and understand highly complex and visualized scientific data. The project will design, develop and study a new technology platform, xMacroscope, as a learning tool that will allow visitors at the Science Museum of Minnesota and the Center of Science and Industry, to create, view, understand, and interact with different data sets using diverse visualization types. The xMacroscope will support rapid research prototyping of public experiences at selected exhibits, such as collecting data on a runner's speed and height and the visualized representation of such data. The xMacroscope will provide research opportunities for exhibit designers, education researchers, and learning scientists to study diverse audiences at science centers in order to understand how learning about data through the xMacroscope tool may inform definitions of data literacy. The research will advance the state of the art in visualization technology, which will have broad implications for teaching and learning of scientific data in both informal and formal learning environments. The project will lead to better understanding by science centers on how to present data to the public more effectively through visualizations that are based upon massive amounts of data. Technology results and research findings will be disseminated broadly through professional publications and presentations at science, education, and technology conferences. The project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants. The project is driven by the assumption that in the digital information age, being able to create and interpret data visualizations is an important literacy for the public. The research will seek to define, measure, and advance data visualization literacy. The project will engage the public in using the xMacrocope at the Science Museum of Minnesota and at the Center of Science and Industry's (COSI) science museum and research center in Columbus, Ohio. In both museum settings the public will interact with different datasets and diverse types of visualizations. Using the xMacroscope platform, personal attributes and capabilities will be measured and personalized data visualizations will be constructed. Existing theories of learning (constructivist and constructionist) will be extended to capture the learning and use of data visualization literacy. In addition, the project team will conduct a meta-review related to different types of literacy and will produce a definition with performance measures to assess data visualization literacy - currently broadly defined in the project as the ability to read, understand, and create data visualizations. The research has potential for significant impact in the field of science and technology education and education research on visual learning. It will further our understanding of the nature of data visualization literacy learning and define opportunities for visualizing data in ways that are both personally and culturally meaningful. The project expects to advance the understanding of the role of personalization in the learning process using iterative design-based research methodologies to advance both theory and practice in informal learning settings. An iterative design process will be applied for addressing the research questions by correlating visualizations to individual actions and contributions, exploring meaning-making studies of visualization construction, and testing the xMacroscope under various conditions of crowdedness and busyness in a museum context. The evaluation plan is based upon a logic model and the evaluation will iteratively inform the direction, process, and productivity of the project.
The project will advance efforts by the American Association for the Advancement of Science and the Institute for Learning Innovation to bring together young adults from communities historically underrepresented in science, technology, engineering, and mathematics (STEM) to collaboratively conduct scientifically driven challenges embedded in a mobile learning tool based upon the AAAS Active Explorer platform. The project will be conducted at the Washington National Mall, San Francisco National Golden Gate Park, and the Boston Harbor Islands National Recreation Area, and will study how a mobile technology used in these settings can facilitate learner engagement in science content; how it can affect young adults' engagement in science-learning processes; and whether interest in learning science and technology has been furthered. The project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments, including pathways for broadening access to STEM learning experiences and advancing research STEM learning. Research questions will investigate science learning inequalities by addressing how place-based augmented reality games can connect young adults to scientific practices, including observing science phenomena, analyzing data, and communicating findings; how young adults develop science skills related to their science self-efficacy through participation in augmented reality science exploration; and how mobile technologies and gaming can serve as mediators that enable young adults to improve their science identity. In addition to engaging young adults in science activities at the National Parks and increasing their science skills, the project will provide valuable information to National Park staff and scientists to assist them in designing effective tools, resources and experiences to better engage young adults. Research teams will collect data in the form of digital ethnography, focus groups, activity reports, artifacts, and surveys. The project will document learning and engagement through mobile technology in three urban national parks that will involve 60 young adults at each location, and will create innovative measurement tools to monitor how informal settings can leverage the intersections of the arts and sciences to support student engagement and learning.
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 widespread accessibility of live streaming video now makes it possible for viewers around the world to watch live events together, including unprecedented, 24/7 views of wildlife. In addition, online technologies such as live chatting and forums have opened new possibilities for people to collaborate from locations around the world. The innovation that the projects provide is bringing these opportunities together, enabling real-time research and discussion as participants observe and annotate live streaming footage; sharing questions and insights through live Q&A sessions; and explore data with interactive visualization tools. Scientists will support the community's research interests, in contrast with traditional models of citizen science in which communities support the work of scientists. This project will enable people from diverse backgrounds and perspectives to co-create scientific investigations, including participants who might not otherwise have access to nature. The evaluation research for this project will advance the understanding of practices that enable interconnected communities of people to participate in more phases of scientific discovery, and how participation affects their learning outcomes. It is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of science, technology, engineering, and mathematics (STEM) learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants. As such, this project will advance a new genre of Public Participation in STEM Research (PPSR). It will also advance scientific exploration using live wildlife cams and establish a database for long-term research to understand how bird behavior and reproductive success are affected by environmental change. This project aims to deepen public involvement in science, building on knowledge and relevance for STEM learning by creating an online learning environment that expands on traditional crowdsourcing models of PPSR in which participants collect data to answer questions driven by scientists. In this project, participants are involved in co-created research investigations, including asking questions, deciding what data are needed, generating data, looking for patterns, making interpretations, reviewing results, and sharing findings. The goals are to 1) create a system that involves the public more deeply in scientific research; 2) develop participants' science skills and interests; 3) increase participants' understanding of birds and the environment; 4) generate new scientific knowledge about wildlife; and 5) advance the understanding of effective project design for co-created PPSR projects at a national scale. Through iterative design and evaluation, the project will advance the understanding of the conditions that foster online collaboration and establish design principles for supporting science and discovery in online learning environments. Through scaling and quasi-experimental studies, the evaluation research will advance the understanding of how learning outcomes may be similar or different for participants engaging in different ways, whether they observe the cams and read about the investigation, process data as contributors, provide some input as collaborators, or join in most or all of the scientific process as co-creators. Despite the popularity of live wildlife cams, with millions of people watching hundreds of cams around the world, little research has been conducted on the use of live cams for collaborative work in formal or informal science education. The infrastructure and open-source framework created for this project will expand the capacity for online communities of people from diverse career backgrounds and perspectives to collaborative on solving personally meaningful questions and contribute to new knowledge. Using this project as a prototype, cam operators from around the world could build networks of cams, enabling future studies with broader scope for comparative biological studies and discoveries. Additionally, it will serve as a model for use in classrooms or for online communities exploring other scientific fields using live-streaming content in collaborative research. By involving scientists and participants from across society as collaborators and co-creators, this project can help increase public engagement with science, technology, and environmental stewardship while advancing the understanding of the natural world and informing public decision-making.
The project team is developing a prototype of a web-based game utilizing the illustrations of chemical elements and science terms created by Simon Basher in his three books, The Periodic Table: Elements with Style!, Chemistry: Getting a Big Reaction!, and Physics: Why Matter Matters! The game will incorporate augmented reality (person-to-person gameplay with the support of the software) to teach grade 4 to 6 students science concepts, including an introduction to chemistry. The game will include curriculum support materials. Pilot research in Phase I will seek to demonstrate that the software prototype functions as planned, teachers are able to integrate it within the classroom environment, and students are engaged with the prototype.
Purpose: This project will develop and test Happy Atoms, a physical modeling set and an interactive iPad app for use in high school chemistry classrooms. Happy Atoms is designed to facilitate student learning of atomic modeling, a difficult topic for chemistry high school students to master. Standard instructional practice in this area typically includes teachers using slides, static ball and stick models, or computer-simulation software to present diagrams on a whiteboard. However, these methods do not adequately depict atomic interactions effectively, thus obscuring complex knowledge and understanding of their formulas and characteristics.
Project Activities: During Phase I (completed in 2014), the team developed a prototype of a physical modeling set including a computerized ball and stick molecular models representing the first 17 elements on the periodic table and an iPad app that identifies and generates information about atoms. A pilot study at the end of Phase I tested the prototype with 187 high school students in 12 chemistry classes. Researchers found that the prototype functioned as intended. Results showed that 88% of students enjoyed using the prototype, and that 79% indicated that it helped learning. In Phase II, the team will develop additional models and will strengthen functionality for effective integration into instructional practice. After development is complete, a larger pilot study will assess the usability and feasibility, fidelity of implementation, and promise of Happy Atoms to improve learning. The study will include 30 grade 11 chemistry classrooms, with half randomly assigned to use Happy Atoms and half who will continue with business as usual procedures. Analyses will compare pre-and-post scores of student's chemistry learning, including atomic modeling.
Product: Happy Atoms will include a set of physical models paired with an iPad app to cover high school chemistry topics in atomic modeling. The modeling set will include individual plastic balls representing the elements of the periodic table. Students will use an iPad app to take a picture of models they create. Using computer-generated algorithms, the app will then identify the model and generate information about its physical and chemical properties and uses. The app will also inform students if a model that is created does not exist. Happy Atoms will replace or supplement lesson plans to enhance chemistry teaching. The app will include teacher resources suggesting how to incorporate games and activities to reinforce lesson plans and learning.
STEM Pathways is a collaboration between five Minnesota informal STEM (science, technology, engineering, and mathematics) education organizations—The Bakken Museum, Bell Museum of Natural History, Minnesota Zoo, STARBASE Minnesota, and The Works Museum—working with Minneapolis Public Schools (MPS) and advised by the Minnesota Department of Education. STEM Pathways (logo shown in Figure 1) aims to provide a deliberate and connected series of meaningful in-school and out-of-school STEM learning experiences to strengthen outcomes for students, build the foundation for a local ecosystem of STEM
The University of Southern California (USC) will build on prior work to test a robust model for assessing player content engagement and social interactions within an augmented reality game (ARG). In partnership with No Mimes Media, USC will use machine learning algorithms to make automated player inferences to customize game play. The content focus of the game will span a range of STEM disciplines, with a special emphasis on earth science content and scientific investigation & experimentation reasoning. High school youth from underserved communities in Los Angeles will be recruited to participate in the endeavor. This pathways project will use various "rabbit hole" techniques to attract freshmen and sophomore students from partner charter schools to the online game. The rabbit hole strategies may include cryptic posters, inquisitive signs, & SQR codes strategically placed in plain and open view of the target group. The game will be fully accessible to the target group online. During the ARG experience, youth players will encounter STEM concepts and scientific problems. Antagonistic characters will promulgate scientific misconceptions and nonscientific reasoning and challenge players to employ their scientific knowledge and skills to level-up, gain badges, and move through the game. As game play persists, machine learning algorithms will gather data on the players learning competencies and social interactions within the game. These data will be aggregated and analyzed to assess learning and interactions within the ARG environment. Additional analyses will be conducted by the mixed methods approach the external evaluation group, CRESST, will employ for the project formative and summative evaluations. Approximately 300 youth, within the target grade levels, are expected to participate in the gaming experience. However, given that access to the game and assessment tools will expand beyond the target group, the potential reach of the project could be much greater. Further, the stated aim of the project is not only to produce a scalable model for broad implementation but it also endeavors to provide puppetmasters with research and assessment tools to create more individualized experiences and improved learning outcomes for players within ARG environments.
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TEAM MEMBERS:
Yu-Han ChangJihie KimRajiv Maheswaran