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.

The study of metaphor has a long history, and it has gradually been taken seriously from the very beginning of Aristotle of ancient Greek. In 1980, American scholars George Lakoff and Mark Johnson published the book Metaphor We Lived By jointly, from which metaphor began to be known as a way of cognition. The differences in languages and cultures, together with the complicated working mechanism of metaphor, post a great challenge in translating metaphor in literary work. This paper analyzes example sentences taken from Chinese classical works. By comparing these sentences with their English translations, we can have a glimpse of the translation strategies often used in rendering metaphor.

Mind map is a new way of thinking that visualizes and visualizes radioactive thinking. The application of mind map in teaching is consistent with the expression of "development of thinking ability" in the "Chinese Curriculum Standards". Its concise construction and clear expression can, on the one hand, convey the ideas of language expressors more quickly and quickly, and on the other hand. On the one hand, it can make the language receiver easier and clearer to understand the message the other party wants to convey.This paper analyzes the application rules of mind map in classroom teaching, and expounds the application strategy of mind map in primary Chinese oral communication teaching from three aspects: picture-text combination, picture-introduction, and picture-introduction. The effective development of primary school students' innovative thinking and logical ability promotes the effective improvement of primary school students' oral communication skills.

Based on the different cultural background, the dissertation mainly talks about the catering culture in the East and the West from the aspects of people’s concepts, eating ingredients, cooking methods, food names and table manners. Through the comparisons, it allows people to know more about the different eating habits and regional characteristics, which promote cross-cultural communication. In addition, China, as a country which is famous for her delicacies, is introduced chiefly. Then some popular restaurants or snack bars will be mentioned in order to analyze today’s food tendency. With the development of our society, the combination of the Eastern and Western food culture will still continue.

Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.