In fall 2019, the Bell Museum received funding via a NASA TEAM II grant to create Mars: The Ultimate Voyage, a full-dome planetarium show and accompanying hands-on activities that focus on the interdisciplinary roles that will be needed to send humans to Mars. This report from Catalyst Consulting Group presents the findings from the summative evaluation completed in March–May 2023.
This project includes the development of a toolkit of new hands-on facilitated museum activities, and a mobile app with both app-based activities and do-it-yourself (DIY) activities. This evaluation report focuses on the formative evaluation of three app activities that are being added to the DIY app series.
In this paper, we investigate bias detection and mitigation techniques to address issues of
algorithmic fairness in multimodal models of museum visitor visual attention.
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TEAM MEMBERS:
Halim AcostaNathan HendersonJonathan RoweWookhee MinJames MinogueJames Lester
resourceevaluationMuseum and Science Center Exhibits
The linked repository contains select resources from the SICIIT NSF project (Supporting Science and Engineering Identity Change in Immersive Interactive Technologies). The project did not reach its main objective, mainly due to disruptions caused by COVID, but we hope that the materials will be a useful resource for follow-up research.
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TEAM MEMBERS:
Stefan RankAyana AllenGlen MuschioAroutis FosterKapil Dandekar
In recent years, transmedia has come into the spotlight among those creating and using media and technology for children. We believe that transmedia has the potential to be a valuable tool for expanded learning that addresses some of the challenges facing children growing up in the digital age. Produced by the USC Annenberg Innovation Lab and the Joan Ganz Cooney Center, this paper provides a much-needed guidebook to transmedia in the lives of children age 5-11 and its applications to storytelling, play, and learning. Building off of a review of the existing popular and scholarly literature
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TEAM MEMBERS:
Becky Herr-StephensonMeryl AlperErin Reilly
Data is increasingly important in all aspects of people’s lives, from the day-to-day, to careers and to civic engagement. Preparing youth to use data to answer questions and solve problems empowers them to participate in society as informed citizens and opens doors to 21st century career opportunities. Ensuring equitable representation in data literacy and data science careers is critical. For many girls underrepresented in STEM, developing a "data science identity" requires personally meaningful experiences working with data. This project aims to promote middle school-aged girls’ interest and aspirations in data science through an identity-aligned, social game-based learning approach. The goals are to create a more diverse and inclusive generation of data scientists who see data as a resource and who are equipped with the skills and dispositions necessary to work with data in order to solve practical problems. The research team will run 10 social clubs and 10 data science clubs mentored by women in data science recruited through the University of Miami’s Institute for Data Science and Computing. Participants will be 250 middle school-aged girls recruited in Miami, FL, and Yolo County, CA, through local and national girls’ organizations. Youth will participate in a data science club and will learn key data science concepts and skills, including data structures, storage, exploration, analysis, and visualization. These concepts will be learned from working with their own data collected in personally meaningful ways in addition to working with data collected by others in the same social game eco-system. The project will also develop facilitator materials to allow adult volunteers to create game-based informal data science learning experiences for youth in their areas. 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 and is co-funded by the Innovative Technology Experiences for Students and Teachers (ITEST), which seeks to engage underrepresented students in technology-rich learning environments, including skills in data literacy, and increase students’ knowledge and interest in information and communication technology (ICT) careers.
Researchers will focus on two primary research questions: 1) Across gameplay and club experiences, in what ways do participants engage with data to pursue personal or social goals? 2) How do gameplay and club experiences shape girls’ perceptions of data, data science, and their fit with data and data science? The project will use design-based research methods to iteratively design the game and social club experiences. To ensure that uses of data feel personally and socially meaningful to young girls, the virtual world’s goals, narratives, and activities will be co-designed with girls from groups underrepresented in data science. The project will research engagement with game data in two informal, game-based learning scenarios: organic, self-directed, social play club, and structured, adult-facilitated data science clubs. The research will use a combination of quantitative and qualitative methods including surveys, focus groups, interviews, and gameplay and club observations. Project evaluation will determine how gameplay and club experiences impact participants' attitudes toward and interest in data-rich futures. The project holds the potential for broadening participation and promoting interest in data science by blending game-based learning with the rich social and adult mentoring through club participation. The results will be disseminated through conference presentations, scholarly publications, and social media. The game and facilitator materials will be designed for dissemination and made freely available to the public.
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TEAM MEMBERS:
Lisa HardyGary GoldbergerJennifer Kahn
This assessment serves as the summative assessment of the IMLS-funded project at KU Biodiversity Institute and Natural History Museum: Natural History Mystery: Immersing families in a problem-solving game using museum collections. The assessment employs a mixed methods approach, in which both quantitative and qualitative data are collected. More specifically, quantitative data are generated from surveys that are administered to participants at the beginning and end of the game and analyzed by using descriptive statistics (i.e., mean, standard deviation, and histogram) and paired sample t-test
The University of Kansas Natural History Museum, in collaboration with the University of California Museum of Paleontology, will develop, test, and deploy an immersive educational game on the topic of evolution and common ancestry. The museum will frame the game with a narrative that involves tracing the origin of a zoonotic disease (infectious disease that is transmitted between species from animals to humans or from humans to animals). Played on the museum floor, the escape room-inspired game will explore innovative formats for museum learning and engagement. It is being designed for families with children ages 7 to 12, and by visiting groups of schoolchildren in grades 3 to 5.
This poster was presented at the 2021 NSF AISL Awardee Meeting.
Collaborative robots – cobots – are designed to work with humans, not replace them. What learning affordances are created in educational games when learners program robots to assist them in a game instead of being the game? What game designs work best?