Objective Nature education has been widely recognized as an effective approach to enhancing public ecological literacy and promoting sustainable development; however, most existing research and practice have primarily focused on children. In the context of China’s efforts to promote all-age friendly urban development, nature education needs to transition from a “child-friendly” to an “all-age friendly” model to better address the diverse and differentiated needs of populations across different age groups. Current nature education programs are often designed from the perspective of resource provision and park management, which may lead to a mismatch with visitors’ spontaneous recreational experiences. This study adopts an all-age perspective and utilizes user generated content (UGC) to construct an indicator system encompassing the content, objectives, and target groups of all-age nature-based recreational experience. Co-word analysis and an improved SnowNLP model were applied to assess public perceptions and sentiments of nature-based recreational experience in country parks. Specifically, the study aims to: 1) examine the overall status of nature education and nature-based recreational experiences in country parks. 2) assess the preference patterns and satisfaction levels of all-age groups for various nature-based recreational activities. 3) compare park perceptions and evaluations across different population perspectives, explore underlying causes, and propose targeted optimization strategies to support the development of an all-age friendly urban nature education system.
Methods This study focused on 29 country parks in Beijing, following a four-step research framework: 1) Social media data for 29 country parks were collected from the Dianping platform using Python and preprocessed. Based on Jieba word segmentation and following the Nature Education Guideline, three schemes were developed: one for indicative dimensions of nature education, one for nature-based recreational experience content, and one for objectives and target audiences. Dedicated lexicons were also constructed to support these schemes. 2) Assessment of the status of nature-based recreational experiences in country parks. Based on a dictionary of target terms related to nature-based recreational experience, relevant review texts were extracted to identify the types of nature-based recreational experience content preferred by the public in each country park. Subsequently, the performance of three sentiment analysis models was evaluated, and the optimized SnowNLP model with the best overall performance was employed to quantitatively assess public satisfaction levels. 3) Assessment of the status of nature-based recreational experiences for all age groups. Comments related to different age groups were further extracted using the audience lexicon. Co-word analysis combined with sentiment analysis was employed to examine differences in preference patterns and satisfaction levels across age groups. 4) Cluster analysis from an all-age perspective. Cluster analysis was conducted to explore patterns of park groups based on all-age preference patterns and satisfaction levels, and park cluster maps were generated to reveal potential functional similarities and differences in nature education from an all-age perspective.
Results The results indicated that 1) Among all collected comments, 86.20% of the comments contained text segments corresponding to the nature-based recreational experiences within the nature education content scheme, whereas only 17.22% explicitly included indicative terms related to nature education. This suggests that visitors frequently engage in diverse spontaneous nature-based recreational experiences, while explicit references to organized nature education activities remain relatively limited. 2) Comments related to nature-based recreational experiences across all country parks showed higher satisfaction scores than overall park comments, indicating the significant positive emotional effects of nature-based recreational experience activities on visitors. In addition, park size classes and administrative levels exhibited differentiated associations with visitors’ perception and evaluation characteristics. 3) The public demonstrated stronger preferences for experiential and life-oriented objectives, such as “plant observation” and “physical activities”, while expressing relatively low interest in abstract or knowledge-oriented topics like “green development” and “green lifestyles”. 4) Preferences for different nature-based recreational experience objectives varied significantly and exhibited clear group-specific patterns. 5) Overall satisfaction with nature-based recreational experience activities remained consistently high and relatively stable across all groups, with visitors traveling with friends reporting comparatively higher levels of satisfaction.
Conclusion This study adopts a public-oriented perspective and utilizes UGC data to examine the characteristics of all-age nature education in Beijing’s country parks. The findings demonstrate significant differences in preference patterns and satisfaction levels for nature-based recreational experiences across age groups and companionship types. Based on these findings, the study proposes strategies such as enhancing public awareness of nature education, designing differentiated educational activities, and improving the overall environmental quality of parks, with the aim of fully leveraging their recreational and educational potential and strengthening their all-age educational functions. The methods and findings also provide empirical evidence and practical guidance for urban park managers and planners, offering a transferable framework for building age-inclusive urban nature education systems. Furthermore, designing differentiated nature education activities based on the interests, preferences, and emotional orientations of all-age groups can effectively enhance participation willingness among different populations. Accordingly, this research offers targeted recommendations for optimizing the allocation of urban nature education resources and improving both public engagement and educational outcomes. Future research may refine this work by improving data acquisition processes and algorithmic models, thereby enabling a more nuanced understanding of the diverse nature education needs across different population groups.
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