Tinkering activities designed for parents and children can foster spatial thinking, which benefits spatial skill development (Ramey et al., 2020). During tinkering activities, families may be challenged to use tools and materials to solve open-ended problems (Bevan, 2017). The problems specified by different tinkering challenges can highlight intrinsic or extrinsic spatial information (Chatterjee, 2008; Mix et al., 2018). In this project we asked, how does the spatial information highlighted by a tinkering challenge affect the quality of families’ spatial thinking?
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TEAM MEMBERS:
Naomi PolinskyElena FiegenKaitlyn HurkaCatherine HadenDavid Uttal
The tinkering process of making, testing, and iteratively redesigning projects can teach children about engineering concepts (Marcus et al., 2021; NGSS, 2013), but there is variability in how tinkering programs are designed. Storytelling may make children’s learning experiences personally meaningful and narratively organized, thereby supporting memory (Bruner, 1996). We designed multiple story-based tinkering programs and examined how the types of story characters and goals introduced in the tinkering programs would relate to the content of families’ talk in post-tinkering reflections.
In this project, we asked whether storytelling during tinkering might support children’s engagement in STEM and how that may differ across boys and girls. According to Bruner (1996), stories can help children to organize experiences by adding coherence, increasing understanding, and facilitating learning. We observed associations between story and STEM in two contexts: home and museum exhibit.
Given the important role of autonomy support in children’s motivation and learning, this study asked whether parents’ use of autonomy supportive language (vs. controlling language) was associated with children’s engagement in science, technology, engineering, and mathematics in a bi-directional manner during an at-home tinkering activity.
This poster from the 2023 ASTC conference provides and overview of research from the NSF funded Designing Our Tomorrow project. This research study examined storytelling approaches used by caregivers and educators to communicate to other caregiver and educators that the engineering practices exercised at DOT exhibits are usefully relevant to problem-solving in their day-to-day lives and within their communities.
"Conectando Saberes" united experts and learners from diverse backgrounds to explore the current landscape, amplify voices, and identify priorities for equity and transformation in STEM learning among Latiné youth and families.
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TEAM MEMBERS:
resourceresearchMuseum and Science Center Exhibits
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