This project builds on an NSF-funded program which engaged youth in the creation of art-science experiences that use the biology and the experiences of migratory birds as a means for communicating the impact of a changing climate.
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TEAM MEMBERS:
Rebecca SafranShawhin RoudbariMary Osnes
The Arctic is warming four times faster as a result of climate change than any other region, but the impacts of this warming are not well known beyond the local communities in the region. The Alaska Pacific University (APU) will organize a one-year planning project to further develop relationships with four Indigenous communities along the Alaskan Yukon River who are experiencing environmental and social impacts from the climate crisis.
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TEAM MEMBERS:
James TemteJulie Brigham-GretteBlane De St CroixErin Marbarger
resourceresearchMuseum and Science Center Exhibits
This white paper describes outcomes from a conference about using non-science art in science education. Art and science are often combined for entertainment, education (STEAM) and inspirational value. However, in almost all cases the art is science-themed (scientific visualizations, science-inspired art, art about scientific topics, etc.). This conference asks the question “what about art for arts-sake?”. That is, what is the impact of non-scientific art in science education? Can non-science themed art be used to broaden perspectives about science? Can it cue people to think about science more
The McWane Science Center (MWSC) will create a new exhibition experience entitled “Dropping Science: Hip-Hop Interactive” that will capture the elements of the popular music genre using interpretive experiences. Project activities include exhibit content development; development of a formal evaluation plan; exhibit prototyping; remedial evaluation, and a final exhibit design plan. An important project goal is to develop the process for creating lasting, reciprocal relationships with the local African American community and throughout the region, thus creating an exhibit space that connects underrepresented audiences to STEM and establishes MWSC as a true community partner. The outcome of this project will be a new interactive experience that was co-developed with and representative of MWSC’s local community that helps MWSC connect with and engage local visitors in science through a more culturally and personally relevant lens.
Artificial intelligence (AI) is in many of our everyday activities—from unlocking phones to running Internet searches to parking cars. Yet, most instruction on how AI works is only in computer science courses. The unique role that AI plays in making decisions that affect human lives heightens the need for education approaches that promote public AI literacy. Little research has been done to understand how we can best teach AI in informal learning spaces. This project will engage middle school age youth in learning abouts AI through interaction with museum exhibits in science and technology centers. The exhibits employ embodied interactions and creative making activities that involve textiles, music making, and interactive media. The research will build on three exhibit prototypes that teach about concepts including bias in data in machine learning, AI decision-making processes, and how AI represents knowledge. Female-identifying and Title 1 youth will be recruited as participants during the exhibit design iterations and testing. 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
Researchers will explore two key research questions: 1) How can the design of interactive museum exhibits encourage interest development in and learning about AI among learners without a Computer Science background by using embodiment and creative making? and 2) How do embodied interaction and creative making mediate learning about AI in informal learning environments? The project will take a design-based research approach, iteratively building on existing exhibit prototypes and testing them in-situ with learners. Data sources and modes of analysis will include retrospective surveys to assess interest, content knowledge gain, creativity, learning talk analysis of audio recordings, and coding of embodied movements in video recordings. Learning talk analysis will identify instances of joint sensemaking during naturalistic interactions with our exhibit to reveal connections between sensemaking talk; learners' behaviors and embodied actions during real-time collaborative knowledge building; and outcomes in knowledge, interest, and creativity measures as elicited in retrospective surveys. The final set of exhibits will be rigorously evaluated with over 500 museum visitors. The key contributions of this work will include a set of rigorously tested exhibits, publicly available exhibit designs, a set of design guidelines for developing AI literacy museum exhibits, and an improved understanding of the relationship between AI-related learning and interest development, embodiment, and creativity.
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TEAM MEMBERS:
Brian MagerkoDuri LongJessica Roberts