| Abstract |
The paper explores virtual worlds as an innovative training platform for upskilling and reskilling smart city professionals, comprising technicians and engineers. Focusing on developing soft skills, the study presents findings from the pilot of a virtual training which was part of a comprehensive tech skills program that also included transversal skills, namely soft, entrepreneurial and green skills. Moreover, the paper describes the methodological approach adapted for the design and the use of the soft skills’ virtual world during the online multi-user sessions, and depicts the technical infrastructure used for its implementation. The virtual world was assessed with a mixed-methods approach, combining a specially designed evaluation questionnaire completed by 27 trainees with semi-structured interviews conducted with instructors. Quantitative data were analyzed to assess satisfaction, perceived effectiveness, and the relationship between curriculum design, support, and instructional quality. Qualitative feedback provided complementary insights into learner experiences and implementation challenges. Findings indicate high levels of learner satisfaction, particularly regarding instructor expertise, curriculum organization, and overall engagement. Statistical analysis revealed strong correlations between course structure and perceived training quality, while prior familiarity with virtual environments showed no significant impact on outcomes. Participants appreciated the flexibility, interactivity, and team-based nature of the training, despite minor technical issues. This research demonstrates the viability of VWs for soft skills development in technical professions, highlighting their value as an inclusive, scalable, and experiential training solution. Its novelty lies in applying immersive technology specifically to smart city training, a field where such applications remain underexplored. The findings support the integration of virtual environments into professional development strategies and inform best practices for future implementations. © 2025 by the authors. |
