行为和自我效能调节训练中的虚拟现实模拟学习:结构方程建模方法

IF 3.2 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING Frontiers in virtual reality Pub Date : 2023-10-23 DOI:10.3389/frvir.2023.1250823
S. M. Ali Mousavi, Wendy Powell, Max M. Louwerse, Andrew T. Hendrickson
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引用次数: 0

摘要

导读:人们对虚拟现实(VR)在学习中的应用越来越感兴趣,但不同的研究报告了其影响和有效性的不同发现。当前的论文在结果中解决了这种异质性。此外,与大多数研究相反,我们使用了实际用于工业的VR应用程序,从而解决了研究结果的生态有效性。研究方法与结果1:在两项研究中,我们探讨了工业VR安全培训应用程序对学习的影响。在我们的第一项研究中,我们检查了交互式VR和被动监视器观看。使用单变量、比较和相关分析方法,研究表明交互式VR的自我效能感和知识得分显著增加,但与被动监视器观看相比没有显著差异。然而,与被动监控观看不同,虚拟现实条件显示学习收益与自我效能之间存在正相关关系。研究2的方法和结果:在我们随后的研究中,结构方程模型(SEM)证明了自我效能感和用户的模拟表现预测了VR的学习收益。我们进一步发现,虚拟现实硬件体验通过自我效能感和用户模拟性能因素间接预测学习收益。两项研究的结论/讨论:最后,这些研究的结果表明,自我效能感在解释学习收益方面的核心作用,从学术虚拟现实任务推广到工业培训中使用的任务。此外,这些结果指出了虚拟现实的行为标记是学习的指示。
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Behavior and self-efficacy modulate learning in virtual reality simulations for training: a structural equation modeling approach
Introduction: There is a rising interest in using virtual reality (VR) applications in learning, yet different studies have reported different findings for their impact and effectiveness. The current paper addresses this heterogeneity in the results. Moreover, contrary to most studies, we use a VR application actually used in industry thereby addressing ecological validity of the findings. Methods and Results of Study1: In two studies, we explored the effects of an industrial VR safety training application on learning. In our first study, we examined both interactive VR and passive monitor viewing. Using univariate, comparative, and correlational analytical approaches, the study demonstrated a significant increase in self-efficacy and knowledge scores in interactive VR but showed no significant differences when compared to passive monitor viewing. Unlike passive monitor viewing, however, the VR condition showed a positive relation between learning gains and self-efficacy. Methods and Results of Study2: In our subsequent study, a Structural Equation Model (SEM) demonstrated that self-efficacy and users’ simulation performance predicted the learning gains in VR. We furthermore found that the VR hardware experience indirectly predicted learning gains through self-efficacy and user simulation performance factors. Conclusion/Discussion of both studies: Conclusively, the findings of these studies suggest the central role of self-efficacy to explain learning gains generalizes from academic VR tasks to those in use in industry training. In addition, these results point to VR behavioral markers that are indicative of learning.
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来源期刊
CiteScore
5.80
自引率
0.00%
发文量
0
审稿时长
13 weeks
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