A User-Centered Evaluation of a VR HMD-Based Harvester Training Simulator

Skilled operation of forestry harvesters is essential for ensuring safety, efficiency, and sustainability in logging practices. However, conventional training methods are often prohibitively expensive and limited by access to specialized equipment. This study delivers one of the first user-centered validations of a low-cost, VR HMD-based forestry harvester simulator, directly addressing access and scalability barriers in training. With 26 participants, we quantify cognitive load, usability, user experience, and simulator sickness using established instruments. An increase in cognitive load was seen from baseline tutorial to each training module (NASA-TLX: 18.65→34.26→38.43; rm-ANOVA, p < 0.001). Usability was ‘Good’ (with a mean SUS score: 76.63), hedonic UX ranked in the top decile (UEQ-S), and simulator sickness was moderate (mean SSQ score: 28.91), while task success remained high across all modules. These results indicate early-stage feasibility and usability of a low-cost VR HMD harvester simulator for student-focused introductory instruction, and they provide actionable design guidance (e.g., managing extraneous load, comfort safeguards) advancing evidence-based VR HMD-based training in the forest engineering and harvesting domain. Our findings validate the potential of VR-HMD as a tool for forestry education capable of addressing training accessibility gaps and enhancing learner motivation through immersive experiential learning.