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 report is the summative evaluation of Moon Adventure Game. The Moon Adventure Game is a challenge-based immersive game, inspired by “escape room” experiences, which asks visitors to take on activities to help them think about what people might need to live and work on the Moon.
Successful peer-to-peer practices in informal science learning (ISL) are often not well defined, but further investigation has the potential to help uncover how to motivate and scaffold children's joint learning in science and engineering. Team Hamster!, a PBS KIDS interactive digital series that helps youth think creatively and use engineering skills to solve problems with everyday tools, will be used to achieve the goals of this project.
Recent advances in multimodal learning analytics show significant promise for addressing these challenges by combining multi-channel data streams from fully-instrumented exhibit spaces with multimodal machine learning techniques to model patterns in visitor experience data. We describe initial work on the creation of a multimodal learning analytics framework for investigating visitor engagement with a game-based interactive surface exhibit for science museums called Future Worlds.
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TEAM MEMBERS:
Jonathan RoweWookhee MinSeung LeeBradford MottJames Lester
resourceresearchMuseum and Science Center Exhibits
Multimodal models often utilize video data to capture learner behavior, but video cameras are not always feasible, or even desirable, to use in museums. To address this issue while still harnessing the predictive capacities of multimodal models, we investigate adversarial discriminative domain adaptation for generating modality-invariant representations of both unimodal and multimodal data captured from museum visitors as they engage with interactive science museum exhibits.
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TEAM MEMBERS:
Nathan HendersonWookhee MinAndrew EmersonJonathan RoweSeung LeeJames MinogueJames Lester
resourceresearchMuseum and Science Center Exhibits
Recent years have seen a growing interest in investigating visitor engagement in science museums with multimodal learning analytics. Visitor engagement is a multidimensional process that unfolds temporally over the course of a museum visit. In this paper, we introduce a multimodal trajectory analysis framework for modeling visitor engagement with an interactive science exhibit for environmental sustainability.
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TEAM MEMBERS:
Andrew EmersonNathan HendersonWookhee MinJonathan RoweJames MinogueJames Lester
resourceresearchMuseum and Science Center Exhibits
In this paper, we introduce a Bayesian hierarchical modeling framework for predicting learner engagement with Future Worlds, a tabletop science exhibit for environmental sustainability.
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TEAM MEMBERS:
Andrew EmersonNathan HendersonJonathan RoweWookhee MinSeung LeeJames MinogueJames Lester