Evaluating Multiple Levels of an Interaction Fidelity Continuum on Performance and Learning in Near-Field Training Simulations
Evaluating Multiple Levels of an Interaction Fidelity Continuum on Performance and Learning in Near-Field Training Simulations
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DOI：
10.1109/tvcg.2018.2794639
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发表时间：
2018-04-01
影响因子：
5.2
通讯作者：
Babu, Sabarish V.
中科院分区：
文献类型：
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作者：
Bhargava, Ayush;Bertrand, Jeffrey W.;Babu, Sabarish V.
随着头盔显示器(HMD)和跟踪技术的成本迅速下降，各种虚拟现实应用正被广泛应用于教育和培训。硬件的进步在很大程度上支持在虚拟环境中复制真实世界的交互，为商业级应用程序铺平了道路，这些应用程序以极低的成本提供安全且无风险的培训环境。但这也要求开发更内在的交互技术，并以更全面的方式对其进行经验评估。尽管有大量以前的研究考察了选定的交互保真度水平对性能的好处，但很少有研究在真实世界技能培训应用程序的背景下，研究具有多个系统实例的交互保真度连续(IFC)中保真度的组成成分及其对性能和学习的各自影响。我们的工作描述了几年来进行的一项大型受试者间调查，该调查利用交互保真度的六个离散水平上的双手交互隐喻来教授虚拟现实中近场空间交互任务中的基本精密计量概念。对数据进行的综合分析比较和对比了六种不同的条件及其对成绩和学习结果的总体影响，得出了国际金融公司不同申请点之间的结果模式。对于部分绩效变量，研究结果表明，较简单的限制性交互隐喻和保真度较高的交互隐喻的表现优于中等保真度的交互隐喻。根据这些结果，为沉浸式虚拟环境中的空间交互隐喻开发人员创建了一套通用指南，用于精确的精细运动技能训练模拟。
With costs of head-mounted displays (HMDs) and tracking technology decreasing rapidly, various virtual reality applications are being widely adopted for education and training. Hardware advancements have enabled replication of real-world interactions in virtual environments to a large extent, paving the way for commercial grade applications that provide a safe and risk-free training environment at a fraction of the cost. But this also mandates the need to develop more intrinsic interaction techniques and to empirically evaluate them in a more comprehensive manner. Although there exists a body of previous research that examines the benefits of selected levels of interaction fidelity on performance, few studies have investigated the constituent components of fidelity in a Interaction Fidelity Continuum (IFC) with several system instances and their respective effects on performance and learning in the context of a real-world skills training application. Our work describes a large between-subjects investigation conducted over several years that utilizes bimanual interaction metaphors at six discrete levels of interaction fidelity to teach basic precision metrology concepts in a near-field spatial interaction task in VR. A combined analysis performed on the data compares and contrasts the six different conditions and their overall effects on performance and learning outcomes, eliciting patterns in the results between the discrete application points on the IFC. With respect to some performance variables, results indicate that simpler restrictive interaction metaphors and highest fidelity metaphors perform better than medium fidelity interaction metaphors. In light of these results, a set of general guidelines are created for developers of spatial interaction metaphors in immersive virtual environments for precise fine-motor skills training simulations.