Deep synthesis technologies，exemplified by DeepSeek，are injecting powerful momentum into modern science communication，guiding the public’s understanding of science into a new normal. They are propelling public cognitive paradigms from “tool-assisted” to a novel stage of “cognitive enhancement”. However，this technological leap is not entirely smooth. While presenting numerous opportunities，it also harbors cognitive risks. This inherent tension reveals that while the public benefits from enhanced cognitive efficiency，expanded cognitive horizons，and transformed knowledge transmission paradigms through algorithmic tools like DeepSeek，they simultaneously face risks of cognitive displacement which includes systemic degradation of critical thinking，pathological fixation of cognitive dependencies，and hierarchical rigidification of cognitive disparities due to “cognitive outsourcing”. Faced with the technological empowerment value and potential cognitive risks demonstrated by tools like DeepSeek in AI science popularization，we must pursue a rational dialectical thinking dimension to advance development，constructe a three-dimensional collaborative framework integrating technology，cognition，and ethics. By restructuring critical thinking training mechanisms，refining technical usage standards，and strengthening social equity safeguards，we can foster a new ecosystem for AI science communication characterized by human-machine symbiosis and inclusive sharing，ensure technological capabilities genuinely serve the comprehensive development of the public as DeepSeek and similar deep synthesis service algorithms integrate with modern science communication.

The burgeoning of generative artificial intelligence is reshaping the paradigm of scientific knowledge dissemination，while its derivative phenomenon of “knowledge hallucination” profoundly deconstructs the foundational credibility of scientific communication. Drawing upon Latour’s actornetwork theory analytical framework，this paper posits AI knowledge hallucination as a product of systemic distortion or “betrayal” within the translation process. This occurs within a heterogeneous actornetwork due to the divergence of objectives and conflicts of interest among key actors. This phenomenon stems from four structural dysfunctions：Source networks suffer contamination from diachronic biases in data inscription and algorithmic goal alienation；Error-correction networks face institutional feedback deficits and temporal asynchrony conflicts hindering rectification; Translation chains endure professional discourse dimensionality loss and technical violence from cross-contamination within heterogeneous knowledge networks；Accountability networks descend into governance vacuums due to technological black-box obscurity and fragmented responsibility. To address these issues，this paper proposes a four-dimensional path for collaborative governance：“Source Purification” fortifies data foundations through a multi-centre knowledge certification system and blockchain traceability technology；“Process Streamlining” builds a closed-loop error correction network leveraging intelligent monitoring systems and dynamic knowledge repositorie；“Translation Optimisation” ensures knowledge fidelity via context-aware algorithms and human-machine dual verification mechanisms；“Anchoring Accountability” clarifies responsibility boundaries among diverse stakeholders through legal empowerment and transparent algorithmic disclosure. This research deepens understanding of the socio-technical nature of AI knowledge hallucination，advancing the development of a robust，trustworthy “AI+Science Communication” ecosystem centred on human-machine collaboration.

The application of generative artificial intelligence in the field of science writing is burgeoning. While empowering science writing，it also introduces unique challenges，such as scientific inaccuracies of science popularization works，the identity and ability recognition of science writers，and the “limited autonomy” of the audience under the implicit dominance of technology. It is suggested to guide the responsible and sustainable development of generative AI-assisted science writing from several aspects：Adhering to the bottom line of the scientificity of science popularization works；Strengthening the subjectivity of “human” of science writers and emphasizing the organic integration of instrumental rationality and value rationality；Enhancing the scientific and digital literacy of the public and creating a new environment for science writing that suits the current situation.

Scientific practice teaching in kindergarten is a kind of teaching activity that emphasizes the multi-dimensional participation of children’s behavioral practices，cognitive exploration and social interaction. However，there are a lot of phenomena that preschool teachers equate science education with common sense education and scientific inquiry with hands-on operation at present. There is a serious tendency of experience and subjectivity in teachers’scientific practice teaching. As a teaching mode based on evidence and facts，evidence-based teaching has attracted much attention because it can improve the rational and scientific level of teaching.This study firstly explains the theory of evidence-based scientific practice teaching in kindergarten，and then reconstructs the whole process of the development and implementation of scientific practice activities by adopting the mode of evidence-based teaching. It is found that the evidence-based scientific practice teaching mode of kindergarten built on the basis of the best evidence can be effectively applied to the scientific practice teaching of kindergarten，and provides a certain support for narrowing the gap between science education theory and teaching reality. It is recommended to strengthen specialized learning of scientific teaching text content，construct personalized scientific practice teaching guidance based on“Internet+”，and carry out clinical practice of evidence-based scientific practice teaching，in order to support evidence-based scientific practice teaching in kindergartens.

This paper focuses on the synergistic developmental path between the scientificity and narrativity of science popularization. It systematically explains the mechanism for AIGC-driven synergistic optimization of scientificity and narrativity，analyzes the dual functions of AIGC in enhancing scientificity and optimizing communication，as well as the multidimensional issues behind its usage. Subsequently，it proposes corresponding optimization strategies for issues such as the detrimental effects of AI hallucinations on scientific rigor，the technical bottlenecks in generating highly complex scientific content，and the conflicts between instrumental rationality and value rationality. Namely，establishing multiple mechanisms to suppress AI hallucination generation，conduct narrative transformation for highly complex science popularization content，and build a synergy mechanism between instrumental rationality and value rationality.

From the perspective of gender，combined with relevant literature，this paper analyzes the related concept of women in science popularization contained in the current policies，regulations and academic research in the field of science popularization in China，and examines the main types and basic status of women in science popularization practices in China from the perspectives of women as the main body and the object of science popularization. It is contended that many significant achievements have been made in the cognition and practice of popular science for women in China. However，problems still exist，such as the ambiguous concept of women in science popularization，the insufficient initiative of female groups to participate in popular science activities，and the less attention paid to in-depth issues such as science and gender. Accordingly，more active explorations and reforms should be made at the levels of subsequent policy-making，academic research and practice of science popularization.

To strengthen the national capacity for science popularization and further implement the initiative to enhance the scientific literacy of all citizens，the China Association for Science and Technology（CAST），in collaboration with the National Bureau of Statistics，conducted the 14th national sample survey on Chinese civic scientific literacy in 2024. This survey provided critical data for the evaluation of the“Outline of the National Scheme for Scientific Literacy（2021—2035）”during the 14th Five-Year Plan period，as well as for achieving the goal of raising the proportion of citizens with scientific literacy to over 15% by 2025. The results show that the scientific literacy of Chinese citizens has been improving at an accelerating pace，with the proportion reaching 15.37% in 2024. The imbalance in scientific literacy development has been alleviated to some extent，and the population with basic scientific literacy is now substantial. The internet has further solidified its position as the primary channel for citizens to access scientific and technological information，while science and technology museums have demonstrated higher visitation and utilization efficiency among various science popularization infrastructures. Overall，Chinese citizens increasingly value science，adopt rational and pragmatic attitudes，and support innovation，with further improvements in critical thinking and scientific awareness. The development of artificial intelligence（AI）enjoys a strong public foundation，with citizens holding positive attitudes and ample confidence toward AI applications，though some concerns remain about job displacement.

With the widespread application of generative artificial intelligence in creative domains，AI is increasingly recognized as an autonomous co-creator，making human-AI co-creation a frontier topic in creativity research. Unlike conventional AI-assisted models，genuine human-AI co-creation requires humans to shift from task executors to “directors” and “gatekeepers”，maintaining proactive agency and leveraging their irreplaceable strengths in divergent thinking，contextual judgment，and authenticity control. However，current practices often fail to fully adhere to these critical boundaries，creative human-machine collaboration unleashs individual creative potential and promoting equality in creativity，and led to challenges accompanying the benefits concurrently，such as homogenization effects，weakened interpersonal collaboration，and copyright disputes. To promote sustainable development in human-AI co-creation，it is imperative to reshape public perceptions of creativity，advance evidence-based human-AI collaborative practices，systematically cultivate co-creation literacy，construct an ecosystem for human-human-AI co-creation，and establish ethical and institutional frameworks that balance democratization with incentives.

The primary school science education curriculum is the key focus for hatching students’scientific spirit and innovative quality in the new era. Looking at the historical development process，the curriculum policy of primary school science education from the beginning of the 20th century to now has experienced five stages：germination and attempt，foundation and exploration，adjustment and restoration，deepening and promotion，innovation and optimization，and has realized four transformations: In terms of value orientation，it has realized the transformation and regression from“instrumental value”to“intrinsic value”；in terms of target orientation，it has realized the iterative update from“serving social construction”to“developing scientific literacy”；in terms of content selection，it has realized the continuous improvement from“popularizing knowledge”to“comprehensive curriculum”. In the evaluation implementation，it has realized the gradual linkage from“one-way”education to“diversified”education. In the future，the standardization and innovation of the curriculum policy of primary school science education should insist on strengthening the overall planning and guiding the policy direction with a high position；Change the concept and practice，with the core quality as the guide to strengthen the moral and cultivate people’s goals；Pay attention to depth and integration，and promote the optimization and improvement of comprehensive course content；Pay attention to process and value-added，broaden the evaluation method and resource matrix.

This research takes the China Science and Technology Museum as the research object，and deeply studies how to use customer journey maps to enhance the audience's visiting experience. By analyzing the characteristics and behaviors of the audience，audience portraits were drawn. And then customer journey maps were created，covering the entire process of typical audiences visiting the China Science and Technology Museum. Results reveal that the customer journey map reveals the emotional fluctuations of the audience at key moments，especially dissatisfaction during ticket purchasing，dining，and leaving the museum. In response to these pain points，measures such as optimizing the ticket refund process，increasing dining space，and opening cultural and creative shops earlier were taken，and practice has proven that these measures effectively enhance the audience's visiting experience.Using customer journey maps to enhance audience experience is universal in the research of audience services in science and technology museums，and continuously iterated customer journey maps can provide support for improving the quality of audience services.