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
resourceresearchMuseum and Science Center Exhibits
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
resourceresearchMuseum and Science Center Exhibits
The purpose of this paper is to provide an overview of the issues of scientific literacy in a dozen countries, as well as the actions taken to address the distinct problems they face. It also presents some experiments that are conducted there.
This dossier was produced as part of Les Journées internationales de la culture scientifique – Science & You, held in Montreal on May 4th, 5th and 6th, 2017.
Through an iterative design process involving museum educators, learning scientists and technologists, and drawing upon our previous experiences in handheld game design and a growing body of knowledge on learning through gaming, we designed an interactive mystery game called Mystery at the Museum (the High Tech Whodunnit), which was designed for synchronous play of groups of parents and children over a two to three hour period. The primary design goals were to engage visitors more deeply in the museum, engage visitors more broadly across museum exhibits, and encourage collaboration between
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TEAM MEMBERS:
Eric KlopferJudy PerryKurt SquireMing-Fong JanConstance Steinkuehler
The EU-funded MultiMatch project aims to overcome language barriers, and media and distribution problems currently affecting access to on-line cultural heritage material. Partners are developing a vertical search engine able to harvest heterogeneous information from distributed sources and present it in a synthesized manner. To design such a system, user requirements were initially gathered and then translated into specific design features to ensure that the search engine developed was consistent with user needs. This paper presents these user requirements, the initial design of the MultiMatch
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TEAM MEMBERS:
Jennifer MarlowPaul CloughNeil IresonJuan Manuel Cigarran RecueroJavier ArtilesFranca Debole