The US manufacturing industry is currently facing a welding workforce shortage which is largely due to inadequacy of widespread welding training. To address this challenge, we present a Virtual Reality (VR)-based training system aimed at transforming state-of-the-art-welding simulations and in-person instruction into a widely accessible and engaging platform. We applied backward design principles to design a low-cost welding simulator in the form of modularized units through active consulting with welding training experts. Using a minimum viable prototype, we conducted a user study with 24 novices to test the system’s usability. Our findings show (1) greater effectiveness of the system in transferring skills to real-world environments as compared to accessible video-based alternatives and, (2) the visuo-haptic guidance during virtual welding enhances performance and provides a realistic learning experience to users. Using the solution, we expect inexperienced users to achieve competencies faster and be better prepared to enter actual work environments.

Augmented/Virtual reality and video-based media play a vital role in the digital learning revolution to train novices in spatial tasks. However, creating content for these different media requires expertise in several fields. We present EditAR, a unified authoring, and editing environment to create content for AR, VR, and video based on a single demonstration. EditAR captures the user’s interaction within an environment and creates a digital twin, enabling users without programming backgrounds to develop content. We conducted formative interviews with both subject and media experts to design the system. The prototype was developed and reviewed by experts. We also performed a user study comparing traditional video creation with 2D video creation from 3D recordings, via a 3D editor, which uses freehand interaction for in-headset editing. Users took 5 times less time to record instructions and preferred EditAR, along with giving significantly higher usability scores.

Augmented reality (AR) is an efficient form of delivering spatial information and has great potential for training workers. However, AR is still not widely used for such scenarios due to the technical skills and expertise required to create interactive AR content. We developed ProcessAR, an AR-based system to develop 2D/3D content that captures subject matter expert’s (SMEs) environment-object interactions in situ. The design space for ProcessAR was identified from formative interviews with AR programming experts and SMEs, alongside a comparative design study with SMEs and novice users. To enable smooth workflows, ProcessAR locates and identifies different tools/objects through computer vision within the workspace when the author looks at them. We explored additional features such as embedding 2D videos with detected objects and user-adaptive triggers. A final user evaluation comparing ProcessAR and a baseline AR authoring environment showed that, according to our qualitative questionnaire, users preferred ProcessAR.

Augmented Reality (AR) has become a valuable tool for education and training processes. Meanwhile, cloud-based technologies can foster collaboration and other interaction modalities to enhance learning. We combine the cloud capabilities with AR technologies to present Meta-AR-App, an authoring platform for collaborative AR, which enables authoring between instructors and students. Additionally, we introduce a new application of an established collaboration process, the pull-based development model, to enable sharing and retrieving of AR learning content. We customize this model and create two modalities of interaction for the classroom: local (student to student) and global (instructor to class) pull. Based on observations from our user studies, we organize a four-category classroom model which implements our system: Work, Design, Collaboration, and Technology. Further, our system enables an iterative improvement workflow of the class content and enables synergistic collaboration that empowers students to be active agents in the learning process.