Evidence map›Paper›PMID 35514866›Full record

ReviewBMJ simulation & technology enhanced learning2016

Working memory is limited: improving knowledge transfer by optimising simulation through cognitive load theory.

Michael Meguerdichian, Katie Walker, Komal Bajaj

Abstract readReview
In one paragraph

Review in BMJ simulation & technology enhanced learning, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Trial
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  6. When common cognitive biases impact debriefing conversations.Advances in simulation (London, England) · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Michael MeguerdichianDepartment of Emergency Medicine, Institute for Medical Simulation and Advanced Learning, Harlem Hospital Center, Columbia University, New York, New York, USA.
Katie WalkerInstitute for Medical Simulation and Advanced Learning, NYC Health + Hospital, Bronx, New York, USA.
Komal BajajInstitute for Medical Simulation and Advanced Learning, NYC Health + Hospitals, Albert Einstein School of Medicine, Bronx, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This analysis explores how to optimise knowledge transfer in healthcare simulation by applying cognitive load theory to curriculum design and delivery for both novice and expert learners. This is particularly relevant for interprofessional learning which is team-based, as each participant comes to the simulation experience with different levels of expertise. Healthcare simulation can offer opportunities to create complex and dynamic experiences that replicate real clinical situations. Understanding Cognitive Load Theory can foster the acquisition of complex knowledge, skills and abilities required to deliver excellence in patient care without overwhelming a learner's ability to handle new materials due to working memory limitations. The 2 aspects of working memory that will be explored in this paper are intrinsic load and extrinsic load. These will be addressed in terms of the learner's level of expertise and how to consider these elements to enhance the learning environment in simulation scenario development and delivery. By applying the concepts of Cognitive Load Theory, this paper offers educators a method to tailor their curricula to navigate working memory and optimise the opportunity for knowledge transfer.

Indexed as

Cognitive LoadCurriculum DesignKnowledge TransferSimulation EducationWorking Memory

Identifiers

PMID35514866
PMCPMC8936700

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.