Extended reality (XR) technologies are gaining traction in technical education due to their potential for creating immersive and interactive training environments. This study presents the development and empirical evaluation of X-RAPT, a collaborative VR-based platform designed to train students in industrial robotics programming. The system enables multi-user interaction, cross-platform compatibility (VR and PC), and real-time data logging through a modular simulation framework. A pilot evaluation was conducted in a vocational training institute with 15 students performing progressively complex tasks in alternating roles using both VR and PC interfaces. Performance metrics were captured automatically from system logs, while post-task questionnaires assessed usability, comfort, and interaction quality. The findings indicate high user engagement and a distinct learning curve, evidenced by progressively shorter task completion times across levels of increasing complexity. Role-based differences were observed, with main users showing greater interaction frequency but both roles contributing meaningfully. Although hardware demands and institutional constraints limited the scale of the pilot, the findings support the platform’s potential for enhancing robotics education.

This work details the design, technical deployment, and empirical validation of X-MAIN (eXtended Reality for Maintenance and Inspection Training), an Extended Reality (XR) environment designed for preventive maintenance and safety protocols in industrial robotics. By replacing physical robotic cells with a safe and highly repeatable virtual workshop, X-MAIN enables learners to perform hands-on tool manipulation and fault diagnostics without relying on physical hardware availability or real-time supervision. The framework is structured into a Simulation Zone for operational checks and a Maintenance Zone for hands-on tasks, governed by a generic, rule-matrix pair-based interaction model that formalizes user actions as tool–target pairs across Virtual Reality (VR) and desktop deployments. To evaluate its efficacy, a counterbalanced cross-over pilot study was conducted with a cohort of $N=23$ technical vocational students in immersive VR mode. Quantitative results demonstrate statistically significant technical knowledge acquisition. System usability assessments yielded a highly favorable Net Promoter Score of $8.6/10$, while subjective workload mapping via an adapted NASA-TLX index confirmed low frustration levels and optimal cognitive engagement. Automated event-driven telemetry further substantiates system efficacy through low procedural error rates and high diagnostic accuracy (75.8%).