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Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks
Dynamic decision-making involves a series of interconnected interdependent confluence of decisions to be made. Experiential training is preferred over traditional methods to train individuals in dynamic decision-making. Imparting experiential training in physical settings can be very expensive and u...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9706391/ https://www.ncbi.nlm.nih.gov/pubmed/36457906 http://dx.doi.org/10.3389/fpsyg.2022.872061 |
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author | Rao, Akash K. Chandra, Sushil Dutt, Varun |
author_facet | Rao, Akash K. Chandra, Sushil Dutt, Varun |
author_sort | Rao, Akash K. |
collection | PubMed |
description | Dynamic decision-making involves a series of interconnected interdependent confluence of decisions to be made. Experiential training is preferred over traditional methods to train individuals in dynamic decision-making. Imparting experiential training in physical settings can be very expensive and unreliable. In virtual reality (VR), synthetic environments play a significant role in providing flexible and cost-effective training environments to enhance dynamic decision-making. However, it is still unclear how VR can be used to impart dynamic decision-making training to increase cognitive performance in complex situations. Besides, different repetitive training methods like desirable difficulty framework and heterogeneity of practice have been evaluated on generic cognitive and motor tasks. However, an evaluation of how these repetitive training methods facilitate dynamic decision-making in an individual in a virtual complex environment setting is lacking in the literature. The objective of this study is to evaluate the effect of different repetitive training methods in immersive VR on dynamic decision-making in a complex search-and-shoot environment. In a lab-based experiment, 66 healthy subjects are divided equally and randomly into three between-subject training conditions: heterogenous, difficult, and sham. On Day 1, all the participants, regardless of the condition, executed an environment of a baseline difficulty level. From Days 2 to 7, the participants alternatively executed the novice difficulty and expert difficulty versions of the environment in the heterogenous condition. In difficult conditions, the participants executed the expert difficulty version of the environment from Days 2 to 7. In the sham condition, the participants executed an unrelated VR environment from Days 2 to 7. On Day 8, the participants executed the baseline difficulty version of the environment again in all the conditions. Various performance and workload-based measures were acquired. Results revealed that the participants in the heterogenous and difficult conditions performed significantly better on Day 8 compared with Day 1. The results inferred that a combination of immersive VR environment with repetitive heterogenous training maximized performance and decreased cognitive workload at transfer. We expect to use these conclusions to create effective training environments in VR for imparting training to military personnel in dynamic decision-making scenarios. |
format | Online Article Text |
id | pubmed-9706391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97063912022-11-30 Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks Rao, Akash K. Chandra, Sushil Dutt, Varun Front Psychol Psychology Dynamic decision-making involves a series of interconnected interdependent confluence of decisions to be made. Experiential training is preferred over traditional methods to train individuals in dynamic decision-making. Imparting experiential training in physical settings can be very expensive and unreliable. In virtual reality (VR), synthetic environments play a significant role in providing flexible and cost-effective training environments to enhance dynamic decision-making. However, it is still unclear how VR can be used to impart dynamic decision-making training to increase cognitive performance in complex situations. Besides, different repetitive training methods like desirable difficulty framework and heterogeneity of practice have been evaluated on generic cognitive and motor tasks. However, an evaluation of how these repetitive training methods facilitate dynamic decision-making in an individual in a virtual complex environment setting is lacking in the literature. The objective of this study is to evaluate the effect of different repetitive training methods in immersive VR on dynamic decision-making in a complex search-and-shoot environment. In a lab-based experiment, 66 healthy subjects are divided equally and randomly into three between-subject training conditions: heterogenous, difficult, and sham. On Day 1, all the participants, regardless of the condition, executed an environment of a baseline difficulty level. From Days 2 to 7, the participants alternatively executed the novice difficulty and expert difficulty versions of the environment in the heterogenous condition. In difficult conditions, the participants executed the expert difficulty version of the environment from Days 2 to 7. In the sham condition, the participants executed an unrelated VR environment from Days 2 to 7. On Day 8, the participants executed the baseline difficulty version of the environment again in all the conditions. Various performance and workload-based measures were acquired. Results revealed that the participants in the heterogenous and difficult conditions performed significantly better on Day 8 compared with Day 1. The results inferred that a combination of immersive VR environment with repetitive heterogenous training maximized performance and decreased cognitive workload at transfer. We expect to use these conclusions to create effective training environments in VR for imparting training to military personnel in dynamic decision-making scenarios. Frontiers Media S.A. 2022-11-14 /pmc/articles/PMC9706391/ /pubmed/36457906 http://dx.doi.org/10.3389/fpsyg.2022.872061 Text en Copyright © 2022 Rao, Chandra and Dutt. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Rao, Akash K. Chandra, Sushil Dutt, Varun Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks |
title | Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks |
title_full | Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks |
title_fullStr | Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks |
title_full_unstemmed | Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks |
title_short | Learning from feedback: Evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks |
title_sort | learning from feedback: evaluation of dynamic decision-making in virtual reality under various repetitive training frameworks |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9706391/ https://www.ncbi.nlm.nih.gov/pubmed/36457906 http://dx.doi.org/10.3389/fpsyg.2022.872061 |
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