This research focuses on the cutting-edge topic of the in-depth integration of artificial intelligence and higher legal education. By employing qualitative research methods such as literature research, comparative research, case analysis, and interviews, it conducts an in-depth analysis of its innovative models, teaching efficacy, and ethical considerations. In terms of innovative models, the personalized learning model customizes learning plans with the help of intelligent platforms, but it faces issues regarding data privacy. The interdisciplinary integrated teaching model, although cultivating compound talents, encounters difficulties in terms of teaching staff. On the level of teaching efficacy, intelligent teaching tools enhance teaching efficiency. However, the homework grading system has limitations, and while the simulated teaching environment optimizes students’ practical abilities, it is restricted by equipment costs and technical maintenance. In terms of ethical considerations, the risks of algorithmic bias and data privacy and security are prominent. Moreover, excessive reliance on artificial intelligence may weaken the cultivation of students’ legal thinking and professional ethics. In response to these problems, a series of suggestions are put forward, including optimizing personalized learning paths, expanding the interdisciplinary integrated curriculum system, perfecting the functions of intelligent teaching tools, strengthening the construction of simulated teaching environments, establishing a mechanism to ensure algorithm fairness, enhancing data privacy and security protection, and promoting legal thinking and professional ethics education. The aim is to promote the healthy and sustainable development of the integration of artificial intelligence and higher legal education and cultivate new types of legal talents who can meet the needs of the era.
Dong et al. (Thu,) studied this question.
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