Traditional methods of teaching complex concepts, including railway signaling, often fall short in accommodating different learning styles, providing real-world examples, and offering hands-on experience. Virtual Reality (VR) can address these limitations by providing a personalized, immersive, and interactive learning experience with tangible examples of abstract concepts. Such an approach could benefit non-expert stakeholders, who need a quick and easy understanding of complex technical concepts.

The research question is, how can Virtual Reality improve learning outcomes of railway signaling concepts for non-experts compared to traditional learning methods? A case study was conducted to investigate the efficacy of VR. Fourteen participants were assigned to two learning conditions: traditional (web experience designed by Alstom) or VR. The learning materials used the same text and information for both conditions. Each participant was given a knowledge test after the learning phase. Qualitative data was obtained through interviews.

Quantitative data was collected through questionnaires, which were analyzed using descriptive statistics and Analysis of Variance (ANOVA) to determine statistical significance. On the other hand, qualitative data was obtained through interviews and analyzed using thematic analysis to identify three main themes: Visualization, Memorization, and User Experience.

The VR artefact scored higher in vocabulary recall speed, correctness, and usability compared to traditional methods. However, there were insignificant results in the SUS (System Usability Scale) questionnaire, indicating a possibility of coincidence. The findings suggest that VR significantly improved the visualization of railway signaling concepts and was more effective than traditional methods for visual memorization. However, it did not contribute to memorizing textual information. This study contributes to the existing knowledge and reinforces previous findings while offering in-depth insight into how VR visualization capabilities can enhance the learning outcomes of railway signaling compared to traditional methods.