Implementing Pretraining to Optimise Learning in Immersive Virtual Reality

ABSTRACT Background In recent years, immersive virtual reality in education has garnered attention, however, there have been mixed findings on the efficacy of IVR in education. Thus, exploring which strategies are effective in transferring learning from IVR to real‐world applications is imperative. Objective This study aims to investigate the efficacy of the pretraining principle for acquiring procedural knowledge and skills in an IVR setting that will transfer to real‐world environments. Methods Ninety‐three participants were randomly assigned to either a pretraining or no‐pretraining group. The pretraining group watched a video before the IVR lesson, providing the names and characteristics of the physical objects and actions of a micropipette, while the no‐pretraining group did not receive this video. During the IVR lesson, participants completed a training phase, followed by a four‐step serial dilution test. Afterwards, all participants completed a modified serial dilution test in a real‐life setting, along with a knowledge test and assessment on cognitive load, presence, self‐efficacy and demographic information. Results and Conclusions Analyses demonstrated the pretraining group scored significantly higher on the knowledge test and committed fewer errors in the real‐life serial dilution task compared to the no‐pretraining group. The pretraining group also reported lower cognitive load, with no observable differences in presence, self‐efficacy ratings or errors during the virtual serial dilution task between groups. Theoretical and practical implications are discussed.

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Publication Details

Journal
Journal of Computer Assisted Learning
Published
2024-12-23
DOI
https://doi.org/10.1111/jcal.13099
Citations
10
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
3.72

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article

Implementing Pretraining to Optimise Learning in Immersive Virtual Reality

Richard E. Mayer, Cynthia Y. Delgado
10 citations
Journal of Computer Assisted Learning
Virtual Reality Applications and Impacts
3.72
article

Implementing Pretraining to Optimise Learning in Immersive Virtual Reality

Richard E. Mayer, Cynthia Y. Delgado
article en
10 citations

Abstract

ABSTRACT Background In recent years, immersive virtual reality in education has garnered attention, however, there have been mixed findings on the efficacy of IVR in education. Thus, exploring which strategies are effective in transferring learning from IVR to real‐world applications is imperative. Objective This study aims to investigate the efficacy of the pretraining principle for acquiring procedural knowledge and skills in an IVR setting that will transfer to real‐world environments. Methods Ninety‐three participants were randomly assigned to either a pretraining or no‐pretraining group. The pretraining group watched a video before the IVR lesson, providing the names and characteristics of the physical objects and actions of a micropipette, while the no‐pretraining group did not receive this video. During the IVR lesson, participants completed a training phase, followed by a four‐step serial dilution test. Afterwards, all participants completed a modified serial dilution test in a real‐life setting, along with a knowledge test and assessment on cognitive load, presence, self‐efficacy and demographic information. Results and Conclusions Analyses demonstrated the pretraining group scored significantly higher on the knowledge test and committed fewer errors in the real‐life serial dilution task compared to the no‐pretraining group. The pretraining group also reported lower cognitive load, with no observable differences in presence, self‐efficacy ratings or errors during the virtual serial dilution task between groups. Theoretical and practical implications are discussed.

Journal of Computer Assisted LearningVol. 41(1)
University of California, Santa Barbara (US)
Office of Naval Research
Quality Education
Openalex Percentile: Top 6%
Virtual Reality Applications and Impacts
3.72
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