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dc.contributor.authorLee-Cultura, Serena
dc.date.accessioned2021-04-08T08:45:23Z
dc.date.available2021-04-08T08:45:23Z
dc.date.created2021-01-04T16:18:20Z
dc.date.issued2019
dc.identifier.isbn978-1-4503-6196-5
dc.identifier.urihttps://hdl.handle.net/11250/2736776
dc.description.abstractEmbodied Interaction (EI) offers unique opportunities to uncover novel ways to achieve experiential learning whilst keeping students stimulated and engaged. Spatial abilities have been repeatedly demonstrated as a success predictor for educations and professions in Science, Technology, Engineering and Mathematics. However, many researchers argue that training and assessment of this pertinent reasoning skill is vastly underrepresented in the school curriculum. This paper presents TetRotation, a PhD centred on how affordances coming from Multimodal Analytics can be coupled with EI to nurture Mental Rotation (MR) skills. The overarching objectives of the project are two fold. First, the TetRotation Interaction Design study will highlight best practices identified through the assessment of efficiency, level of engagement and learning gains achieved when using gesture based EI to solve MR tasks. Next, in the TetRotation Game study, these design practices will guide the implementation of an interactive serious game purposed to support the development of MR skills. This research relies on mixed method techniques, including data collections from users’ actions, like motion sensing, EEG, gaze tracking, video-recordings, click streams, interviews and surveysen_US
dc.language.isoengen_US
dc.publisherACMen_US
dc.relation.ispartofProceedings of the Thirteenth International Conference on Tangible, Embedded, and Embodied Interaction
dc.titleTetRotation: Utilising Multimodal Analytics and Gestural Interaction to Nurture Mental Rotation Skillsen_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber715-718en_US
dc.identifier.doihttps://doi.org/10.1145/3294109.3302932
dc.identifier.cristin1865099
dc.description.localcode© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published here, https://doi.org/10.1145/3294109.3302932en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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