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Integrating Human Movement in Learning: Advancements in Language Instruction, Multimedia, and Theory.

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Title: Integrating Human Movement in Learning: Advancements in Language Instruction, Multimedia, and Theory.
Authors: de Koning, Bjorn (AUTHOR), Zhang, Shirong (AUTHOR), Sepp, Stoo (AUTHOR)
Source: Educational Psychology Review. Jun2025, Vol. 37 Issue 2, p1-10. 10p.
Abstract: Human movement plays a foundational role in cognition and learning. This topical collection brings together theoretical and empirical work examining how gestures, physical activity, and virtual movement enhance learning in language, multimedia, and activity-based learning. Regarding language learning, interacting with virtual object improves vocabulary learning, especially for learners with low language aptitude. Additionally, emotional narratives support memory more effectively than neutral ones, while instructed gesturing may hinder recall for some learners. In multimedia learning, pointing improves attention and comprehension, whereas tracing can impede learning due to cognitive overload. For activity-based learning, theoretical contributions offer frameworks for integrating movement into learning tasks, emphasizing mechanisms such as generative learning, social cognition, and offloaded processing in areas ranging from digital education to stimming behaviors. Together, these studies offer insights for designing effective, movement-based instruction across diverse learning environments and populations, underscoring the dynamic relationship between bodily action and cognitive development in education. [ABSTRACT FROM AUTHOR]
Copyright of Educational Psychology Review is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Integrating Human Movement in Learning: Advancements in Language Instruction, Multimedia, and Theory.
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  Data: <searchLink fieldCode="AR" term="%22de+Koning%2C+Bjorn%22">de Koning, Bjorn</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Shirong%22">Zhang, Shirong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sepp%2C+Stoo%22">Sepp, Stoo</searchLink> (AUTHOR)
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  Data: Human movement plays a foundational role in cognition and learning. This topical collection brings together theoretical and empirical work examining how gestures, physical activity, and virtual movement enhance learning in language, multimedia, and activity-based learning. Regarding language learning, interacting with virtual object improves vocabulary learning, especially for learners with low language aptitude. Additionally, emotional narratives support memory more effectively than neutral ones, while instructed gesturing may hinder recall for some learners. In multimedia learning, pointing improves attention and comprehension, whereas tracing can impede learning due to cognitive overload. For activity-based learning, theoretical contributions offer frameworks for integrating movement into learning tasks, emphasizing mechanisms such as generative learning, social cognition, and offloaded processing in areas ranging from digital education to stimming behaviors. Together, these studies offer insights for designing effective, movement-based instruction across diverse learning environments and populations, underscoring the dynamic relationship between bodily action and cognitive development in education. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Educational Psychology Review is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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