Ecological Informatics (Sep 2024)
Exploring the impact of university green spaces on Students' perceived restoration and emotional states through audio-visual perception
Abstract
A growing body of evidence suggests that university green space (UGS) can substantially enhance students' perceived restoration. This study employed virtual reality technology to assess the characteristics of audio-visual elements in three types of UGS, then utilized Peason correlation analysis and structural equation modeling (SEM) to explored environmental audio-visual perception, perceived restoration, and their associations with emotional state. Findings indicate that: (1) Within the same UGS type, the dominance of different audio-visual elements was relatively consistent across various locations. However, there were differences among different UGS types: artificial sounds were dominant in Commuter Green Spaces, while natural sounds were more prominent in Natural Green Spaces, and the perception trends for visual elements were similar to those of the sound sources. (2) Soundscape pleasantness was significantly positively correlated with three dimensions of perceived restoration and positive emotion, negatively correlated with negative emotion, and had similar findings to soundscape pleasantness in visual perception and soundscape eventfulness. (3) The SEM results showed that soundscape pleasantness and eventfulness could directly influence visual perception and positive emotion. In addition, our study also found a cascading mediating effect with visual perception and perceived restoration as core elements. These findings deepen our understanding of how audio-visual perceptions influence emotional restoration and well-being, potentially enhancing both student experiences and the quality of UGS. Furthermore, the findings underscore the complexities involved in perception assessment, influenced by variations in social backgrounds, cultural factors, and individual characteristics. This emphasizes the need for future research to consider these variables comprehensively, aiming to provide a deeper understanding of the specific physical attributes of restorative environments.