The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

Background: Traditional education in neurosurgery primarily relies on observation, giving residents and interns limited opportunities for clinical practice. However, the development of 3D printing has the potential to improve this situation. Based on bibliometrics, we analyze the application of 3D printing technology in neurosurgery medical education and surgical training. Methods: We searched the publications in this field in Web of Science core collection database from September 2000 to September 2023. VOS viewer, Citespace and Microsoft Office Excel were used to visually analyze and draw knowledge graphs. Results: A total of 231 articles and reviews were included. The United States is the country with the largest volume of articles and Mayo Clinic is the leading organization in this field. Partnership between countries, authors and institutions is also presented. World Neurosurgery is the journal with the highest number of publications. The top three key words by occurrence rate are “3D printing”, “surgery” and “simulation”. Conclusions: In recent years, more and more attention has been paid to the research in this field. According to bibliometric analysis, “accuracy” and “surgery simulation” are the research focuses in this field, while “augment reality” is the potential research target.