A Study on Computer Simulation and User Experience Evaluation for Product Interface Design from the Perspective of Human-Computer Interaction
Abstract
The current user interface design processes do not include early quantitative estimates of how users interact with and experience aninterface. Therefore, when poor usability and unsatisfactory user experience are discovered, the issues often emerge only after the product has been released. This paper proposes using an interface design analysis method that incorporates insight into user interface interaction modeling, computer simulation, and user experience evaluation within a human-computer interaction context. By formally modeling the interface structure, user tasks, and operational behaviors, computer simulations may be used to predict the user’s path, the success of their task completion, and the distribution of errors.The simulation results are then validated against multi-dimensional user experience evaluation indicators. This enables the systematic evaluation and
optimization of interface design during the early stages of development. Experimental results show that the simulated user operation paths maintain 88% consistency with real user behavior under interface scheme S1, with the lowest average completion time for core tasks at 32 seconds; in S5, the highest error frequency is 8.1%. After simulation-driven optimization, task completion time is reduced to 32–44 seconds, and the overall user experience score improves to above 4.0/5. The research results demonstrate that the proposed method provides a model- and data-driven approach for early-stage validation and experience evaluation during the design of an interface.
Keywords: human-computer interaction modeling; interface interaction simulation; user experience prediction; operational path simulation; task performance evaluation
Cite As
H. Wang, Z. Qu, "A Study on Computer Simulation and User Experience Evaluation for Product Interface Design from the Perspective of Human-Computer Interaction", Engineering Intelligent Systems, vol. 34 no. 4, pp. 441-453, 2026.
