This study utilized the application of authentic Virtual Reality (VR) to replicate the real-world complex system scenarios of a large retail supply chain. The proposed VR scenarios were developed based on an established systems thinking instrument that consists of seven dimensions: level of complexity, independence, interaction, change, uncertainty, systems’ worldview, and flexibility. However, in this study, we only developed the VR scenarios for the first dimension, level of complexity, to assess an individual’s Systems Thinking Skills (STS) when he or she engages in a turbulent virtual environment. The main objective of this study was to compare a student’s STS when using traditional ST instruments versus VR scenarios for the complexity dimension. The secondary aim was to investigate the efficacy of VR scenarios utilizing three measurements: Simulation Sickness Questionnaire (SSQ), System Usability Scale (SUS), and Presence Questionnaire (PQ). In addition to the three measures, NASA TLX assessment was also performed to assess the perceived workload with regards to performing the tasks in VR scenarios. The results show students’ preferences in the VR scenarios are not significantly different from their responses obtained using the traditional systems skills instrument. The efficacy measures confirmed that the developed VR scenarios are user friendly and lie in an acceptable region for users. Finally, the overall NASA TLX score suggests that users require 36% perceived work effort to perform the activities in VR scenarios.

The focus of computer systems in the field of visual analytics is to make the results clear and understandable. However, enhancing human-computer interaction (HCI) in the field is less investigated. Data visualization and visual analytics (VA) are usually performed using traditional desktop settings and mouse interaction. These methods are based on the window, icon, menu, and pointer (WIMP) interface, which often results in information clutter and is difficult to analyze and understand, especially by novice users. Researchers believe that introducing adequate, natural interaction techniques to the field is necessary for building effective and enjoyable visual analytics systems. This work introduces a novel virtual reality (VR) module to perform basic visual analytics tasks and aims to explore new interaction techniques in the field. A pilot study was conducted to measure the time it takes students to perform basic tasks for analytics using the developed VR module and compares it to the time it takes them to perform the same tasks using a traditional desktop to assess the effectiveness of the VR module in enhancing student’s performance. The results show that novice users (Participants with less programming experience) took about 50% less time to complete tasks using the developed VR module as a comrade to a programming language, notably R. Experts (Participants with advanced programming experience) took about the same time to complete tasks under both conditions (R and VR).

Signal detection in sports is fundamental to the organization and performance of both the individual athletes as well as the teams. Coaches and players often signal to each other to express plays or other relevant information. This research focuses on identifying the characteristics of successful signal implementation in a collegiate environment for American football and was conducted with inputs on play call design and signalling methods from an NCAA Division I football coaching staff. A comprehensive literature review approach was taken to extrapolate characteristics and factors that influence successful signal detection from a broad range of research. Key factors and characteristics were identified (i.e., physical and display characteristics, the environment, cueing, and signalling methods) through the review. Recommendations were made on factor implementation to enhance play call signal detection. Recommendations from the analysis to the football coaching staff include reduction of background noise, high contrast signals and signalling coach attire, cueing student-athletes to signal locations, and information for optimizing overall visual conspicuity of signals. Additional information is provided on encryption techniques and novel signalling methods. Results of this research will be used to ensure play call signals in the football environment are conspicuous and easily interpretable to the intended student-athletes.

Digital twin technologies provide new opportunities for visualizing, analyzing, and managing complex physical systems; however, effective methods are needed to transform digital twin data into immersive environments that support human interaction and decision-making. This study presents the development of a Digital Twin Immersive Environment (DTIE) prototype for facility visualization and analysis at the U.S. Army Corps of Engineers Engineering Research and Development Center (ERDC) in Vicksburg, Mississippi. A photogrammetry-based workflow was used to capture the facility interior and generate a dense three-dimensional point cloud, while a separate Gaussian splat reconstruction was generated from the same image dataset. The Gaussian splat representation was spatially aligned with Revit-derived CAD geometry to provide complementary geometric and photorealistic representations within the immersive environment. A virtual reality (VR) environment was developed with a user interface (UI) supporting ray-cast interaction, speech-to-text data entry, multi-user collaboration, switching between CAD and Gaussian splat representations, in-scene web browsing, and occupant movement simulation. The resulting DTIE prototype demonstrates the technical integration of complementary CAD and Gaussian splat representations with immersive interaction capabilities for facility digital twins. The environment operated at approximately 71.8 FPS under the reported Meta Quest 2 configuration. This work establishes a prototype framework for future investigation of collaborative visualization, scenario analysis, and decision-support applications for complex infrastructure systems.