Generative AI (GenAI) is rapidly transforming creative fields, raising critical questions about its impact on artistic identity and authorship, which also influence art education. While studies have explored GenAI adoption, the diversity of art students’ subjective perspectives on collaborating with these tools remains under-examined. This study uses Q methodology, a mixed-methods approach to investigating subjectivity, to explore the distinct perspectives art students hold regarding their creative identity when collaborating with GenAI. We conducted a Q study with 40 university students from various art-related disciplines (e.g., visual arts, design, music, animation) across different academic levels. Participants sorted 42 statements reflecting diverse viewpoints on GenAI collaboration, authorship, ethics, and creative control. By-person factor analysis revealed five distinct perspectives: (1) Human-centered directors, who treat GenAI as a tool under strong human intention; (2) Authorship guardians, who resist AI co-authorship and prioritise authenticity and ethical boundaries; (3) Conflicted co-creators, who use GenAI but struggle with ownership, disclosure, and earned pride; (4) Pragmatic integrators, who adopt GenAI for workflow efficiency while keeping craft expertise central; and (5) Enthusiastic explorers, who embrace AI’s creative possibilities, open to co-agency and novel expression. These findings offer a nuanced typology of student viewpoints, moving beyond simple acceptance or rejection. We further propose a two-dimensional framework that maps these perspectives according to students’ openness to GenAI and their sharing of creative agency with it. This research contributes empirical insights into how art students negotiate creative identity with GenAI, provides a valuable framework for educators to develop tailored pedagogical strategies addressing diverse student needs and concerns, and offers implications for designing more human-centered GenAI tools for creative practice.

In urban regeneration, ecological space optimization is key for megacities to improve livability. Existing studies rely heavily on single-scale indicators such as green coverage to characterize park provision, while the multidimensional associations and spatial spillovers of park systems remain underexamined. Based on three-wave panel (2018, 2022, and 2025) data from 20 districts in Chengdu—China’s first Park City Demonstration Zone—this study constructs a four-dimensional park system index (land development intensity, supporting facility density, spatial equity, supply scale) and applies spatial Durbin models. Results show a core–periphery pattern in both park systems and livability, with park construction expanding into suburban areas faster than livability improves. Beyond these spatiotemporal patterns, the local associations between individual park dimensions and livability are multidimensional rather than uniformly positive: land development intensity and supply scale correlate positively with livability, whereas supporting facility density shows a negative association, likely reflecting, among other possible explanations, congestion-related externalities and facility-population mismatches in high-density areas. Spatial spillovers follow a “limited scale spillover, prominent configuration spillover” pattern, with spatial equity alone exhibiting significant positive cross-regional associations. This study expands park spillover research from scale-based to configuration-based perspectives and documents dimensionally differentiated park associations, providing a spatial equity viewpoint for building inclusive cities.

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