Year: 2024
Type: article
Study designs: Randomized Controlled Trial, Clinical Trial
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.
DOI: 10.1111/jcal.13099
Authors: Cynthia Y. Delgado, Richard E. Mayer
Institution: University of California, Santa Barbara
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
Estimated APC paid: $3,950
Funder: Office of Naval Research
Award: G1901057771
OpenAlex ID: W4405716454
