Embodied learning: introducing a taxonomy based on bodily engagement and task integration

Skulmowski, Alexander; Rey, Günter Daniel

doi:10.1186/s41235-018-0092-9

Cited by 154 publications

(167 citation statements)

References 89 publications

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“…Generally speaking, the results support the claim that the language used in different surveys should match the learning task (as discussed by Skulmowski & Rey, 2017). In the context of activity‐based and interactive learning media, Skulmowski and Rey (2018) suggested a more task‐oriented approach based on Wilson and Golonka (2013) that recommends the use of task analyses. A conceptualization of cognitive load involving a learner, a learning task, the physical environment, and relations between these factors was introduced by Choi, van Merriënboer, and Paas (2014).…”

Section: Implications Of the Measurement Of Extraneous Load In Interamentioning

confidence: 99%

Subjective cognitive load surveys lead to divergent results for interactive learning media

Skulmowski

Rey

2020

Human Behav and Emerg Tech

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Cognitive load theory assumes that cognitive demands that arise from the design of learning materials (known as extraneous load) are major obstacles in the learning process with (digital) media. Interactive digital media allow learners to utilize complex learning materials that respond to user input. However, recent research on cognitive load measurement has led to the question whether different survey instruments produce different measurements for extraneous load generated by interactive learning media. In a laboratory experiment, we investigated this question using digital visualizations. Most importantly, we found that two cognitive load questionnaires revealed divergent results regarding the extraneous load involved in learning with interactive visualizations. This finding indicates that different questionnaires may be needed for different types of tasks in technology-enhanced learning settings. A more fundamental implication is that there needs to be greater consideration of different types of extraneous load.

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Section: Implications Of the Measurement Of Extraneous Load In Interamentioning

confidence: 99%

Subjective cognitive load surveys lead to divergent results for interactive learning media

Skulmowski

Rey

2020

Human Behav and Emerg Tech

Self Cite

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“…Over the past years, many efforts have been undertaken to categorize embodied learning. For example, taxonomies of embodied learning have been developed in the context of technology (Johnson-Glenberg et al 2014;Melcer and Isbister 2016), full-body interactions (Malinverni and Pares 2014), learning with manipulatives (Reed 2018), and, more generally, for the field of learning and instruction (Skulmowski and Rey 2018). The taxonomy of embodied learning described by Johnson- Glenberg et al (2014) consists of four degrees of embodiment in which each degree entails a different level of bodily involvement, or motoric engagement.…”

Section: Operationalizing Embodied Learning Environments For Graphingmentioning

confidence: 99%

Embodied Learning Environments for Graphing Motion: a Systematic Literature Review

et al. 2019

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Embodied learning environments have a substantial share in teaching interventions and research for enhancing learning in science, technology, engineering, and mathematics (STEM) education. In these learning environments, students' bodily experiences are an essential part of the learning activities and hence, of the learning. In this systematic review, we focused on embodied learning environments supporting students' understanding of graphing change in the context of modeling motion. Our goal was to deepen the theoretical understanding of what aspects of these embodied learning environments are important for teaching and learning. We specified four embodied configurations by juxtaposing embodied learning environments on the degree of bodily involvement (own and others/objects' motion) and immediacy (immediate and non-immediate) resulting in four classes of embodied learning environments. Our review included 44 articles (comprising 62 learning environments) and uncovered eight mediating factors, as described by the authors of the reviewed articles: realworld context, multimodality, linking motion to graph, multiple representations, semiotics, student control, attention capturing, and cognitive conflict. Different combinations of mediating factors were identified in each class of embodied learning environments. Additionally, we found that learning environments making use of students' own motion immediately linked to its representation were most effective in terms of learning outcomes. Implications of this review for future research and the design of embodied learning environments are discussed.

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“…Thus, knowledge of their topography is fundamental to understanding potential routes for the spread of infection, tumors, and damage to surrounding structures. However, like the ventricles of the brain (Smith et al, 2007;Adams and Wilson, 2011;Colibaba et al, 2017) current anatomical resources provide limited realistic visualization of the complex structure and spatial relationships of the negative-spaces of sinuses in situ within the skull. Atlases and medical images present students with a series of two-dimensional (2D) slices that they must integrate internally (Garg et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

How Can We Show You, If You Can't See It? Trialing the Use of an Interactive Three‐Dimensional Micro‐CT Model in Medical Education

O'Rourke

Smyth

Webb

et al. 2019

Anatomical Sciences Ed

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Teaching internal structures obscured from direct view is a major challenge of anatomy education. High‐fidelity interactive three‐dimensional (3D) micro‐computed tomography (CT) models with virtual dissection present a possible solution. However, their utility for teaching complex internal structures of the human body is unclear. The purpose of this study was to investigate the use of a realistic 3D micro‐CT interactive visualization computer model to teach paranasal sinus anatomy in a laboratory setting during pre‐clinical medical training. Year 1 (n = 79) and Year 2 (n = 59) medical students undertook self‐directed activities focused on paranasal sinus anatomy in one of two laboratories (traditional laboratory and 3D model). All participants completed pre and posttests before and after the laboratory session. Results of regression analyses predicting post‐laboratory knowledge indicate that, when students were inexperienced with the 3D computer technology, use of the model was detrimental to learning for students with greater prior knowledge of the relevant anatomy (P < 0.05). For participants experienced with the 3D computer technology, however, the use of the model was detrimental for students with less prior knowledge of the relevant anatomy (P < 0.001). These results emphasize that several factors need to be considered in the design and effective implementation of such models in the classroom. Under the right conditions, the 3D model is equal to traditional laboratory resources when used as a learning tool. This paper discusses the importance of preparatory training for students and the technical consideration necessary to successfully integrate such models into medical anatomical curricula.

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Embodied learning: introducing a taxonomy based on bodily engagement and task integration

Cited by 154 publications

References 89 publications

Subjective cognitive load surveys lead to divergent results for interactive learning media

Subjective cognitive load surveys lead to divergent results for interactive learning media

Embodied Learning Environments for Graphing Motion: a Systematic Literature Review

How Can We Show You, If You Can't See It? Trialing the Use of an Interactive Three‐Dimensional Micro‐CT Model in Medical Education

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