Adaptive Immersive VR Training Based on Performance and Self-Efficacy

TY - GEN

T1 - Adaptive Immersive VR Training Based on Performance and Self-Efficacy

AU - Lui, Lasse F.

AU - Radhakrishnan, Unnikrishnan

AU - Chinello, Francesco

AU - Koumaditis, Konstantinos

PY - 2023

Y1 - 2023

N2 - Effective training requires that the training experience fits the ability and confidence (i.e., self-efficacy) of the trainee. Specifically, the individual's self-efficacy should ideally be slightly higher than the difficulty of a given task. A significant benefit of immersive virtual reality (IVR) is the potential to utilize measures of trainee behavior to continuously adapt the training content to the individual. However, a major challenge involves the identification of relevant measures that can be used to adapt training content in a way that increases training output. The current paper aims to inspire further research on adaptive IVR training by describing the design and development of a study on adaptive IVR training where the use of self-efficacy measures for adaptation marks a point of departure from prior literature. The design of the proposed study is informed by analyses of results from previous IVR studies.

AB - Effective training requires that the training experience fits the ability and confidence (i.e., self-efficacy) of the trainee. Specifically, the individual's self-efficacy should ideally be slightly higher than the difficulty of a given task. A significant benefit of immersive virtual reality (IVR) is the potential to utilize measures of trainee behavior to continuously adapt the training content to the individual. However, a major challenge involves the identification of relevant measures that can be used to adapt training content in a way that increases training output. The current paper aims to inspire further research on adaptive IVR training by describing the design and development of a study on adaptive IVR training where the use of self-efficacy measures for adaptation marks a point of departure from prior literature. The design of the proposed study is informed by analyses of results from previous IVR studies.

KW - I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism

KW - Virtual Reality

UR - http://www.scopus.com/inward/record.url?scp=85159726840&partnerID=8YFLogxK

U2 - 10.1109/VRW58643.2023.00012

DO - 10.1109/VRW58643.2023.00012

M3 - Article in proceedings

AN - SCOPUS:85159726840

SP - 25

EP - 29

BT - Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023

PB - IEEE

T2 - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023

Y2 - 25 March 2023 through 29 March 2023

ER -