The construction industry has struggled with a disappointing safety record, with workers often failing to identify hazards on construction sites. While virtual reality (VR) training has shown promise in improving hazard recognition skills, it is essential to address not only the ability to identify hazards but also the factors influencing workers' decision to report them. Research has revealed that workers often fail to recognize hazards when they perceive them as low-risk, leading to unreported hazards and persistent safety risks. Anticipatory emotions play a crucial role in driving risk aversion, but construction novices lack the emotional experiences necessary for developing such anticipatory emotions. Consequently, they may engage in careless and risk-friendly behavior. To address this issue, hazard recognition training should incorporate immersive and emotionally arousing VR experiences. This dissertation focuses on the development of emotionally arousing and realistic construction-specific simulations to assess their impact on construction novices. The research explores the aspects of a simulation that facilitate emotional arousal and identifies features that enhance the sense of presence for construction practitioners within a virtual construction environment. Subsequently, the developed VR experience is tested on construction novices. The results indicate that the VR experience, based on the findings of this research, effectively elicits significant arousal in participants, as evidenced by galvanic skin response (GSR) data. Thematic analysis of participant feedback further supports the physiological data, with participants reporting a realistic and emotional experience that immersed them in hazardous conditions on a construction site. Ultimately, this research contributes by identifying the crucial aspects necessary for developing construction-specific VR experiences that elicit arousal from participants, ensuring an immersive and emotionally engaging hazard recognition training. By incorporating such training methods, the construction industry can improve workers' hazard identification and reporting behaviors, thereby enhancing overall safety in construction sites.

The country is facing infrastructure crises simultaneous with a labor shortage in fields related to construction management and engineering. These challenges necessitate better and quicker preparation of the incoming workforce so they are prepared to take on responsibilities with more skill and efficiency than has been expected previously. Educators can play a key role in equipping the leaders of this upcoming generation to deal with these challenges. If students are expected to graduate with more preparation and expertise, then educators must also adjust the ways in which they teach. There are many ways that these changes can be accomplished, and researchers play a critical role in exploring new classroom techniques and technologies that may improve the way education is delivered. This dissertation focuses on a high-impact emerging technology, augmented reality (AR), as a training mechanism for students that has the potential to play a crucial role in enhancing the way construction education is delivered. First, this research explores what skills and competencies are most frequently reported as critical needs by industry members by thematically coding open-ended responses of construction internship supervisors. Leveraging the results of this data, this research explores the viability of utilizing AR to simulate hands-on training and authentic learning in ways that target these skills and competencies. The research presented in this dissertation consists of a series of subject tests involving custom-developed augmented reality applications. These full-scale, highly interactive construction mixed reality applications are designed to expose students to simulations of high-impact learning experiences but without the recurring costs of physical materials. Student behaviors and performance during these subject tests are thematically coded to reveal student behaviors and perceptions that contribute to learning objectives. The results of this research demonstrate high potential for AR as an educational tool while also suggesting best practices for creating and implementing these types of activities based on surprising and sometimes counterintuitive student behaviors during these AR experiences.

The construction industry has been growing over the past few years, but it is facing numerous challenges, related to craft labor availability and declining productivity. At the same time, the industry has benefited from computational advancements by leveraging the use of Building Information Modeling (BIM) to create information rich 3D models to enhance the planning, designing, and construction of projects. Augmented Reality (AR) is one technology that could further leverage BIM, especially on the construction site. This research looks at the human performance attributes enabled using AR as the main information delivery tool in the various stages of construction. The results suggest that using AR for information delivery can enhance labor productivity and enable untrained personnel to complete key construction tasks. However, its usability decreases when higher accuracy levels are required. This work contributes to the body of knowledge by empirically testing and validating the performance effects of using AR during construction tasks and highlights the limitations of current generation AR technology related to the construction industry. This work serves as foundation of future industry-based AR applications and research into potential AR implementations.

The semiconductor manufacturing business model provides unique challenges for the design and construction of supporting fabrication facilities. To accommodate the latest semiconductor processes and technologies, manufacturing facilities are constantly re-tooled and upgraded. Common to this sector of construction is the retrofit project environment. This type of construction project introduces a multitude of existing conditions constraints and functions entirely differently than traditional new-build projects. This facility conversion process is further constrained by owner needs for continuous manufacturing operations and a compressed design/construction schedule to meet first-to-market milestones.

To better control the variables within this project environment, Building Information Modeling (BIM) workflows are being explored and introduced into this project typology. The construction supply-chain has also increased their focus on offsite construction techniques to prefabricate components in a controlled environment. The goal is to overlap construction timelines and improve the productivity of workers to meet the increasingly demanding schedules and to reduce on-site congestion. Limited studies exist with regards to the manufacturing retrofit construction environment, particularly when focusing on the effectiveness of BIM and prefabrication workflows. This study fills the gap by studying labor time utilization rates for Building Information Modeling workflows for prefabrication of MEP (mechanical/electrical/plumbing) and process piping equipment in a retrofit construction environment.

A semiconductor manufacturing facility serves as a case-study for this research in which the current state process for utilizing BIM for prefabrication is mapped and analyzed. Labor time utilization is studied through direct observation in relation to the current state modeling process. Qualitative analysis of workflows and quantitative analysis of labor time utilization rates provide workflow interventions which are implemented and compared against the current state modeling process.

This research utilizes a mixed-method approach to explore the hypothesis that reliable/trusted geometry is the most important component for successful implementation of a BIM for prefabrication workflow in a retrofit environment. The end product of this research is the development of a prefaBIM framework for the introduction of a dynamic modeling process for retrofit prefabrication which forms the basis for a model-based delivery system for retrofit prefabrication.