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1. Performance-Driven VR Learning for Robotics

   Vassigh, Shahin; Bogosian, Biayna; Peterson, Eric (January 2024, Springer)

   Yan, C; Chai, H; Sun, T; Yuan, PF (Ed.)

   Abstract. The building industry is facing environmental, technological, and economic challenges, placing significant pressure on preparing the workforce for Industry 4.0 needs. The fields of Architecture, Engineering, and Construction (AEC) are being reshaped by robotics technologies which demand new skills and creating disruptive change to job markets. Addressing the learning needs of AEC students, professionals, and industry workers is critical to ensuring the competitiveness of the future workforce. In recent years advancements in Information Technology, Augmented Reality (AR), Virtual Reality (VR), and Artificial Intelligence (AI) have led to new research and theories on virtual learning environments. In the AEC fields researchers are beginning to rethink current robotics training to counteract costly and resource-intensive in-person learning. However, much of this work has been focused on simulation physics and has yet to adequately address how to engage AEC learners with different learning abilities, styles, and diverse backgrounds.This paper presents the advantages and difficulties associated with using new technologies to develop virtual reality (VR) learning games for robotics. It describes an ongoing project for creating performance driven curriculum. Drawing on the Constructivist Learning Theory, the affordances of Adaptive Learning Systems, and data collection methods from the VR game environment, the project provides a customized and performance-oriented approach to carrying out practical robotics tasks in real-world scenarios. 

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2. A Review of Extended Reality (XR) Technologies for Manufacturing Training

   https://doi.org/10.3390/technologies8040077  

   Doolani, Sanika; Wessels, Callen; Kanal, Varun; Sevastopoulos, Christos; Jaiswal, Ashish; Nambiappan, Harish; Makedon, Fillia (December 2020, Technologies)

   Recently, the use of extended reality (XR) systems has been on the rise, to tackle various domains such as training, education, safety, etc. With the recent advances in augmented reality (AR), virtual reality (VR) and mixed reality (MR) technologies and ease of availability of high-end, commercially available hardware, the manufacturing industry has seen a rise in the use of advanced XR technologies to train its workforce. While several research publications exist on applications of XR in manufacturing training, a comprehensive review of recent works and applications is lacking to present a clear progress in using such advance technologies. To this end, we present a review of the current state-of-the-art of use of XR technologies in training personnel in the field of manufacturing. First, we put forth the need of XR in manufacturing. We then present several key application domains where XR is being currently applied, notably in maintenance training and in performing assembly task. We also reviewed the applications of XR in other vocational domains and how they can be leveraged in the manufacturing industry. We finally present some current barriers to XR adoption in manufacturing training and highlight the current limitations that should be considered when looking to develop and apply practical applications of XR. 

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3. Holographic Learning Environment for Bridging the Technical Skill Gap of the Future Smart Construction Engineering Students

   Ogunseiju, Omobolanle; Akanmu, Abiola; Bairaktarova, Diana (January 2020, Enabling the Development and Implementation of Digital Twins: Proceedings of the 20th International Conference on Construction Applications of Virtual Reality)

   Dawood, Nashwan; Rahimian, Farzad P.; Seyedzadeh, Saleh; Sheikhkhoshkar, Moslem (Ed.)

   The growth in the adoption of sensing technologies in the construction industry has triggered the need for graduating construction engineering students equipped with the necessary skills for deploying the technologies. One obstacle to equipping students with these skills is the limited opportunities for hands-on learning experiences on construction sites. Inspired by opportunities offered by mixed reality, this paper presents the development of a holographic learning environment that can afford learners an experiential opportunity to acquire competencies for implementing sensing systems on construction projects. The interactive holographic learning environment is built upon the notions of competence-based and constructivist learning. The learning contents of the holographic learning environment are driven by characteristics of technical competencies identified from the results of an online survey, and content analysis of industry case studies. This paper presents a competency characteristics model depicting the key sensing technologies, applications and resources needed to facilitate the design of the holographic learning environment. A demonstrative scenario of the application of a virtual laser scanner for measuring volume of stockpiles is utilized to showcase the potential of the learning environment. A taxonomic model of the operational characteristics of the virtual laser scanner represented within the holographic learning environment is also presented. This paper contributes to the body of knowledge by advancing immersive experiential learning discourses previously confined by technology. It opens a new avenue for both researchers and practitioners to further investigate the opportunities offered by mixed reality for future workforce development. 

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4. Competencies for human–robot collaboration in the construction industry: perspectives from academia and industry

   https://doi.org/10.1007/s41693-025-00156-y  

   Olukanni, Ebenezer; Akanmu, Abiola; Jebelli, Houtan; Ammar, Ashtarout; Okunola, Akinwale (December 2025, Construction Robotics)

   Abstract Robotic automation in construction has created the need for new competencies that will enable the workforce to engage with robots safely and effectively. However, differing perceptions between industry professionals and academia make aligning academic programs with industry needs challenging. This study evaluates these perceptions to guide the design of HRC training programs. A three-round Delphi study was conducted separately with panels of industry professionals and academic experts to assess their views on HRC competencies in construction. The findings revealed that both panels identified human–robot interfaces, HRC safety and standards, robot control systems, and construction robot applications as the top five HRC knowledge areas. Industry professionals also emphasized task planning knowledge, while academic experts focused on HRC ethics. Key HRC skills include effective communication, safety management, technical proficiency, and compliance with regulations and standards, with industry professionals prioritizing proficiency in task planning and academics emphasizing human–robot interface proficiency. Both expert panels prioritized teamwork, continuous learning, problem-solving, communication, and adaptability as top-rated HRC abilities. This study contributes to knowledge by defining key HRC competencies and identifying differences in priorities between industry and academia. These insights can guide the development of academic curricula that better align with industry needs, supporting the creation of training programs that equip the workforce with the competencies required for safe and effective robotic collaboration. The study also promotes collaboration between industry and academia, fostering innovation in HRC and robotics in construction. Future research directions are proposed to explore innovative training methods to equip the future workforce with HRC competencies. 

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5. Data science skills and domain knowledge requirements in the manufacturing industry: A gap analysis

   https://doi.org/10.1016/j.jmsy.2021.07.007  

   Li, Guoyan; Yuan, Chenxi; Kamarthi, Sagar; Moghaddam, Mohsen; Jin, Xiaoning (July 2021, Journal of Manufacturing Systems)

   Manufacturing has adopted technologies such as automation, robotics, industrial Internet of Things (IoT), and big data analytics to improve productivity, efficiency, and capabilities in the production environment. Modern manufacturing workers not only need to be adept at the traditional manufacturing technologies but also ought to be trained in the advanced data-rich computer-automated technologies. This study analyzes the data science and analytics (DSA) skills gap in today’s manufacturing workforce to identify the critical technical skills and domain knowledge required for data science and intelligent manufacturing-related jobs that are highly in-demand in today’s manufacturing industry. The gap analysis conducted in this paper on Emsi job posting and profile data provides insights into the trends in manufacturing jobs that leverage data science, automation, cyber, and sensor technologies. These insights will be helpful for educators and industry to train the next generation manufacturing workforce. The main contribution of this paper includes (1) presenting the overall trend in manufacturing job postings in the U.S., (2) summarizing the critical skills and domain knowledge in demand in the manufacturing sector, (3) summarizing skills and domain knowledge reported by manufacturing job seekers, (4) identifying the gaps between demand and supply of skills and domain knowledge, and (5) recognize opportunities for training and upskilling workforce to address the widening skills and knowledge gap. 

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