In recent years, the rural homestay has developed rapidly against the background of rural-revitalization policies. However, in early 2020, COVID-19 broke out in China, and the homestay industry was faced with a great challenge. It was difficult for self-employed homestays to resist the risks of the pandemic. As a result, defective operation and business failure occurred in some regions. However, rural homestays with a background in the brand, chain and cluster development mode persisted in the market with a diversity of operation principles. This paper tries to set up an evaluation system for understanding the occupancy needs of tourists, in order to improve the ability of rural homestays to resist risks. The article offers a methodology for assessing the tourist experience of rural homestays in coastal areas, with homestays in Dapeng New District of Shenzhen taken as the research objectives. Then, the evaluation system of rural homestays is set up from the perspective of tourist experience. Based on the results of a questionnaire survey and interviews of operators, this paper proposes the tourist experience–importance analysis in Jiaochangwei and Xichong by the importance–performance analysis (IPA) method. Finally, it suggests policy recommendations that can resist high risk based on tourist experience, for the sustainable development of rural homestays in China.

The campus courtyards in the Lingnan area are commonly used spaces. Therefore, their thermal comfort is highly important for improving user satisfaction. This study conducted field research on 18 courtyards in four universities in Lingnan to explore the effects of their architectural design factors on the thermal environment. Relevant studies have proved that courtyards are cost-effective in microclimate regulation, and individual factors such as the scale and openness of the courtyards have also been shown to have an effect on the thermal comfort of the courtyards. This study synthesizes multidimensional architectural design factors to explore and analyze the thermal environments of college courtyards. Physiologically equivalent temperature (PET) is selected as the thermal comfort evaluation index for the study and the conclusions are as follows: (1) The thermal environment is the most important factor influencing visitors to the courtyards (22%), and good thermal comfort improves the efficiency of using the college courtyards; (2) the courtyards have a positive microclimate regulating function, and a cooling effect occurs in 80% of them; and (3) the floor location, type, orientation, and sky view factor (SVF) of the courtyards are the main design factors affecting the thermal environment and PET. The first three factors were negatively correlated with PET (p < 0.05),and SVF was positively correlated with PET (p = 0.651). Passive courtyard design strategies are presented based on the findings of this study.

Traditional settlements exhibit remarkable climatic adaptability, representing a form of “Morphological Intelligence” developed over centuries. However, this inherent, physics-based wisdom remains underutilized in contemporary urban planning and design. This systematic review aims to decode such intelligence by analyzing the relationship between the morphological characteristics of traditional settlements and their thermal performance. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, literature retrieval and evaluation were conducted via the databases of Web of Science, Scopus, and China National Knowledge Infrastructure (CNKI) for articles published during 2004~2024. A total of 82 related articles with available full texts were selected from 1227 records for in-depth analysis, including peer-reviewed journal articles and reputable conference publications. This study first presents an overview of bibliometric and methodological landscapes, revealing that research is increasingly concentrated in Asia’s tropical and subtropical climates, predominantly employing case studies and computational simulations. Secondly, we synthesize a few key climate-adaptive morphological features across macro- (e.g., settlement layout), meso- (e.g., street canyon geometry), and microscales (e.g., courtyards). The findings illustrate a reliance on methods and metrics developed for modern urban contexts, which could not fully capture the specific morphological characteristics of traditional settlements. Most importantly, this study summarizes four core principles of “Morphological Intelligence” in traditional settlements, i.e., strategic solar control, facilitated natural ventilation, use of thermal mass, and integration of natural elements and creation of thermal buffer zones. By identifying the limitations of existing investigations, this study highlights a few directions for future studies, including conducting more systematic multi-scalar integrated analysis, focusing on the development of dedicated quantitative metrics and analytical frameworks, delving into more mechanism-oriented investigation, assessing morphological resilience under urbanization, and translating principles into contemporary design guidelines. This study provides a foundational framework for translating the “Morphological Intelligence” of traditional settlements into actionable, evidence-based strategies for resilient and energy-efficient urban planning and design amidst climate change.

High-density school design has become an important challenge in rapidly urbanizing cities, where land scarcity, increasing educational demand, and evolving pedagogical models generate multiple and interrelated design constraints. Although a wealth of design experience has accumulated through the execution of numerous school planning projects, this knowledge remains fragmented across architectural publications and project narratives. Existing studies have primarily focused on evaluating built environments or individual cases, and limited attention has been paid to how dispersed architectural design reasoning can be systematically extracted, organized, and represented. This study was conducted to explore how AI-assisted semantic modeling can support the extraction and organization of architectural design knowledge from large-scale design discourse through a human–AI collaborative interpretation framework. Using a corpus of 330 documents reporting school design in Shenzhen published between 2017 and 2024, the proposed framework integrates BERTopic-based semantic modeling, scenario–strategy coding, network analysis, and document-based architectural interpretation to establish a continuous workflow from architectural discourse to structured knowledge representation and spatial interpretation. The results reveal a density-conditioned knowledge structure consisting of six interconnected design agendas, 25 recurrent design scenarios, 44 original design strategies, 17 core strategies, four strategy clusters, and four document-supported spatial response patterns. The findings demonstrate that high-density school design knowledge is organized through recurring problem–strategy relationships rather than isolated project solutions. Through human–AI collaborative interpretation, fragmented design narratives are transformed into hierarchical representations linking design concerns, scenarios, strategies, and spatial organizations. The aim of the proposed framework is not to automate architectural decision-making or generate implementation-ready design solutions but to provide a methodological foundation for AI-assisted architectural knowledge retrieval, knowledge representation, and future multimodal design intelligence systems.