The overarching goal of this Research in Service to Practice project is to leverage multimodal learning analytics to develop an enriched understanding of visitor engagement in science museums. The project centers on data-rich investigations of visitor engagement with interactive tabletop exhibits about environmental science and sustainability. During free-choice learning in museums and science centers, visitor engagement shapes how learners interact with exhibits, move around the exhibit space, and form attitudes, interests, and understanding of science. Multimodal visitor analytics integrates the rich multichannel data streams produced by fully-instrumented exhibit spaces with the data-driven modeling functionalities afforded by recent advances in machine learning and educational data mining.
This poster was presented at the 2021 NSF AISL Awardee Meeting.
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