Using Cognitive Load Theory to Optimize Simulation Design

2019 ◽  
pp. 129-141
Author(s):  
Laura M. Naismith ◽  
Jeffrey J.H. Cheung ◽  
Matthew Sibbald ◽  
Walter Tavares ◽  
Rodrigo B. Cavalcanti ◽  
...  
Author(s):  
Richard Say ◽  
Denis Visentin ◽  
Vasiliki Betihavas ◽  
Susannah Minutillo

AbstractBackgroundCognitive load theory (CLT) uses an understanding of brain architecture for educational design, with implications for simulation. Since working memory is limited, minimising extraneous cognitive load improves learning of new tasks (intrinsic load) and use of existing knowledge (germane load). This study evaluates the effectiveness of low-fidelity simulation (LFS) utilising CLT principles in the assessment and management of the deteriorating patient (AMDP).MethodCLT design principles informed the choice of LFS and simulation design. The self-rated ability of 13 undergraduate nurses across seven aspects of AMDP was measured in a pre-post design.ResultsSelf-rated ability increased from 2.98 (SD = 0.19) to 4.47 (SD = 0.12) (p < 0.001), with improvements across all AMDP aspects.ConclusionThis study indicates that CLT informed design has benefits for simulation. LFS may be preferred to high fidelity simulation for AMDP teaching and medical simulation for novice learners.


Author(s):  
Roland Brünken ◽  
Susan Steinbacher ◽  
Jan L. Plass ◽  
Detlev Leutner

Abstract. In two pilot experiments, a new approach for the direct assessment of cognitive load during multimedia learning was tested that uses dual-task methodology. Using this approach, we obtained the same pattern of cognitive load as predicted by cognitive load theory when applied to multimedia learning: The audiovisual presentation of text-based and picture-based learning materials induced less cognitive load than the visual-only presentation of the same material. The findings confirm the utility of dual-task methodology as a promising approach for the assessment of cognitive load induced by complex multimedia learning systems.


2013 ◽  
Author(s):  
Lori B. Stone ◽  
Abigail Lundquist ◽  
Stefan Ganchev ◽  
Nora Ladjahasan

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