Usability and UX Evaluation in a Mixed Reality Puzzle Game Using Questionnaires

Background: Mixed Reality (MR) technologies present unique usability and user experience (UX) challenges, particularly in gesture-based interaction and spatial perception. Puzzle games in MR environments rely heavily on intuitive control and immersive feedback to maintain user engagement. Purpose: This study aims to evaluate the usability and UX of the Cubism puzzle game in an MR context, comparing different standardized instruments to capture user perceptions and identify specific interaction issues. Methods: The evaluation was conducted during a usability and UX workshop, where participants used Meta Quest 2 and Meta Quest 3 headsets. Participants were divided into two groups: Group A completed the UUXE-ToH v4 questionnaire, while Group B answered the USE, Slater-Usoh-Steed (SUS), and UEQ questionnaires. In addition to quantitative assessments, participants reported issues, which were classified and analyzed thematically. Results: Cubism was positively evaluated in terms of learnability, memorability, and satisfaction. However, notable challenges were identified in object manipulation, gesture accuracy, and error recovery. Immersion and presence scores were comparatively lower, particularly in SUS, suggesting limited perceptual integration of virtual objects into the real environment. Interaction precision and environmental coherence were also affected by hardware limitations, especially on devices with monochrome passthrough. Conclusion: The findings highlight specific usability and UX limitations in MR puzzle games and illustrate how different instruments (applied to distinct groupings of participants) captured complementary aspects of the experience. Although no direct statistical comparison was performed, indirect analysis suggests varying diagnostic contributions across instruments. These findings suggest that multidimensional evaluation frameworks (either through a single comprehensive instrument or a combination of focused tools) can provide richer insights for guiding design improvements and identifying usability and UX issues in MR applications.