The representation of visual hierarchy remains a central concern in contemporary design research and practice. Current design guidelines advocate establishing hierarchical relationships through dimensions such as size or distance, yet concrete and effective integration strategies remain elusive. This study, grounded in Gestalt principles, investigates the impact of design layouts on hierarchical perception under the interaction of proximity and similarity. This experiment systematically controls the size (1:1, 1:3/4 and 1:1/2, respectively) and distance (namely 1/4 R, 1/2 R, 3/4 R, 1 R, 5/4 R and 3/2 R) of two circular objects, employing a 3 × 6 two-way ANOVA. The results indicate that the interaction between size and distance can exert a significant influence on the perception of hierarchy. Among these factors, structural type emerges as the dominant element shaping hierarchical perception, with overlapping structures showing pronounced hierarchical suggestive characteristics that significantly outperform tangential and separated structures. Size can partially regulate this effect. When dimensions are equal, tangential and separated structures show no significant difference in perceived hierarchy. However, with the aid of size disparity, the hierarchical sense of separated structures can be markedly enhanced, yielding an effect stronger than that produced by shared edges.

1. The significance of user experience as the pivotal element of human-computer interaction is progressively mounting, and numerous organizations regard user-centered design (UCD) strategies as the...

The interface design of conversational AI mobile applications is shaped by natural language interaction, multi-turn feedback, and dynamically generated content. While these features may reduce certain operational barriers, they can also create new difficulties for older adults in understanding system functions, judging generated results, and recovering from interaction errors. To address these challenges, this study integrates the KANO model and the Analytic Hierarchy Process (AHP) to develop a systematic framework for analyzing interface requirements in conversational AI mobile applications for older users. Field surveys and semi-structured interviews were first conducted to identify 15 interface design requirements. These requirements were then classified through a KANO questionnaire into must-be, one-dimensional, attractive, and indifferent categories, with no reverse requirements identified. On this basis, an AHP hierarchy was established to determine the relative priority of each requirement. The results show that clear functional explanations, interface simplicity, absence of advertising interference, voice interaction, and error-tolerant interaction design are the key factors influencing older adults’ experience with conversational AI interfaces. Basic usability requirements mainly reduce barriers to use, while functional explanations and voice interaction help older users understand system capabilities and task procedures. Error-tolerant interaction further enhances users’ sense of security and control in dynamic and uncertain conversational contexts. These findings suggest that age-friendly design for conversational AI mobile applications should not be limited to isolated adjustments of fonts, icons, or colors. Instead, it should adopt a systematic approach centered on low-complexity interfaces, clear task guidance, interpretable feedback, and recoverable interactions. Based on the classification and weighting results, this study proposes an interface design framework for age-friendly conversational AI mobile applications, providing a reference for requirement analysis, interface optimization, and design decision-making.