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.

Academic integrity has been at the centre of the discussion of the adoption of Chat GPT by academics in their research. This study explored how academic integrity mitigates the desire to use ChatGPT in academic tasks by EFL Pre-service teachers, in consideration of the time factor, perceived peer influence, academic self-effectiveness, and self-esteem. The study utilized web-based questionnaires to elicit data from 300 EFL Pre-service teachers across educational fields drawn from different schools across the world. Analysis was conducted using relevant statistical measures to test the projected four hypotheses. The findings provide evidence in support of Hypothesis 1, with a statistically significant path coefficient (β) of 0.442, a t-value of 3.728, and a p-value of 0.000. The hypothesis acceptance implies that when academic integrity improves, the impact of the time-saving aspect of the use of ChatGPT Across educational fields study decreases. This suggests that EFL Pre-service teachers who have a firm dedication to academic honesty are less influenced by the tempting appeal of ChatGPT’s time-saving features, highlighting the ethical factors that influence their decision-making. The data also provide support for Hypothesis 2, indicating a substantial inverse relationship with a path coefficient (β) of 0.369, a t-value of 5.629, and a p-value of 0.001. These findings indicate that stronger adherence to academic integrity is linked to a diminished effect of colleagues on the choice to use ChatGPT in Academic tasks. The results suggest that a firm dedication to academic honesty serves as a protective barrier against exogenous pressures or influences from colleagues when it comes to embracing cutting-edge technology. However, in general, these findings revealed there was a negative association between academically related factors (e.g., time factor, sense of peer pressure, language study self-confidence, and academic language competence), as well as an attitude toward adoption of ChatGPT and commitment towards academic integrity.