Exploring operator responses to Augmented Reality training: Insights from the SELFEX platform case study

Oscar Escallada^1*Ganix Lasa¹Maitane Mazmela Etxabe¹Dario La Carrubba²Enrica Bosani³Angel Dacal-Nieto⁴Marcos Villar García⁴

• ¹University of Mondragón, Mondragón, Spain
• ²MADE S.c.a.r.l., Milano, Italy
• ³Beko Europe Management SRL, Milano, Italy
• ⁴Centro Tecnológico de Automoción de Galicia, Porriño, Spain

Traditional training methods often fail to capture the nuanced expertise of experienced personnel, thus limiting the instructional quality for new staff. By introducing innovative training platforms like SELFEX, which utilizes augmented reality technology, this study explores a novel approach to knowledge transfer that allows junior operators to learn independently by mimicking the recorded performances of senior operators. The research methodology includes a comprehensive analysis of AR's functionality, benefits, and constraints, along with an empirical investigation into SELFEX's effectiveness in enhancing training satisfaction, perceived usefulness, and ease of use, as well as a flow state evaluation compared to conventional methods. The findings highlight AR's potential to provide immersive, interactive learning experiences that significantly improve understanding, engagement, and retention among trainees, especially novices. However, challenges in integrating AR technologies into professional workflows are also acknowledged, suggesting a need for user-friendly design and further research into AR's long-term impact on skill development and performance. This paper underscores the transformative potential of AR in revolutionizing industrial training practices, advocating for the development of accessible, efficient learning tools that cater to diverse user needs and facilitate the seamless transfer of expert knowledge.