In this study, we examined the application of neurostructural principles to the design of public spaces on university campuses to optimize students’ learning efficiency, social interactions, and psychological well-being. Using Hainan University in China as a case study, a descriptive analysis was used to evaluate the case study design of the data. Data on students’ preferences for and satisfaction with public learning spaces (libraries, student centers, and open learning areas) were also collected through a questionnaire. The questionnaire was based on the four stages of the AIDA (Attention, Interest, Desire, and Action) model and covered basic information about the participants and their first impressions of the learning spaces, design element preferences, emotional and cognitive influences, and willingness to participate in improving the design of campus spaces. Data were analyzed using quantitative methods, including frequency analysis and score aggregation, to assess the students’ satisfaction with the existing design elements of the learning space and their suggestions for potential improvements. A random sample of students enrolled at Hainan University was used to ensure that the data were representative. The results of the study indicate that the rational allocation of natural light, the optimization of the acoustic environment, the adoption of soothing color schemes, and flexible spatial layouts are effective at relieving students’ psychological stress, enhancing their academic performance, and facilitating social interactions. Some of the existing designs are already in line with neurostructural principles, but there is still room for improvement, especially in terms of color schemes and spatial configurations. Students have positive attitudes towards participating in campus space improvement, with especially high interest in light optimization, spatial layout, and the use of natural materials. This study verifies the effectiveness of using neural structure principles in campus public spaces by establishing an empirical model, proves its positive effect on the quality of the campus environment and students’ well-being, and provides empirical evidence and theoretical support for future campus design.