In an article recently published in the journal Sustainability, researchers proposed an artificial intelligence (AI) international legal education coupling-empowerment model to improve international law education.
Study: Empowering Legal Education: AI's Role in International Law. Image credit: Tualek Photography/Shutterstock
Importance of AI in legal education
In international law education, the conventional mode of teaching based on the curriculum teaching of teachers primarily focuses on one-way inculcation. However, the requirements of intellectualization must be fulfilled in the AI era to cultivate legal talents.
The advent of AI technology has significantly altered the form of knowledge dissemination pathways, access methods, and expression, providing new legal education development prospects and momentum. To realize a comprehensive transformation of the legal education system, AI can be integrated into the existing education system.
Thus, the conventional international law education teaching mode must be reformed, and a law education teaching model that matches the AI-driven talent training system must be constructed. Specifically, the challenges and impact of AI technology development on legal education must be considered while developing the model. Additionally, the cultivation of talents must focus on the conventional knowledge structure and applying AI technical processing methods to offer maximum convenience for educational work.
The proposed AI legal education model
In this study, researchers constructed an AI international legal education coupling-empowerment model to assess the coupling capability of AI in international legal education. The study involved using the Pearson product–moment correlation coefficient in correlation analysis, AI knowledge mapping implementation with the assistance of intelligent parenting, and applying the backpropagation neural algorithm in artificial neural networks (ANN) to establish a cognitive student model.
Initially, the Pearson correlation coefficient was applied to perform correlation analysis between various learning behaviors of learners and to determine the linear correlation between variables. Then, AI knowledge mapping was utilized to realize the intelligent parenting assistant function. Eventually, a backpropagation neural algorithm was applied in an ANN, coupled with cognitive theory, to construct a cognitive student model that reflects the cognitive ability and learning level of students.
Specifically, the cognitive student model could output the student's mastery of applications, skills, and concepts through the cognitive activity assessment values of the learner, which facilitates the creation of a coupled empowerment model of AI and international legal education.
In the AI knowledge graph, the knowledge mapping layer was responsible for developing the knowledge map using the data obtained in the data layer. Additionally, the Dialogue System Layer was based on the knowledge graph-provided structured domain knowledge and utilized AI technology to achieve the intelligent education assistant function.
The knowledge graph construction primarily included the definition of graph schema and knowledge fusion and acquisition. Based on the external environment, internal individual characteristics, and problem behavior information, the AI summarized the reasons for the problem's emergence and provided solution countermeasures, related cases, and relevant theoretical knowledge.
In the AI intelligent diagnostic system structure, the domain model stored the course's specialized knowledge taught to the students. This model could generate questions and provide proper answers to questions, as well as the problem-solving process.
Additionally, the diagnostic model analyzed the student's response using diagnostic rules to determine the student's existing knowledge or the misconceptions generated by the student and transferred this information to the student model's current state. Thus, in legal education, this teaching mode can provide intelligent teaching support and personalized learning experience and enable accurate assessment of learners/students. Researchers evaluated the effectiveness of the proposed AI-coupled empowerment model in the practical analysis through long-term impact and sustainability analysis, AI teaching coupling analysis, and system testing.
Significance of the study
Results obtained from the evaluation of the proposed AI-coupled empowerment education model demonstrated the model's effectiveness in practical teaching. In the teaching system test, the AI international law education model achieved 99.5% classification accuracy, and simultaneously, the algorithm ran for a short duration, which resulted in more accurate mining of the learning knowledge for the user in a short period.
In the coupling analysis, the average number of visits was 128 in the experimental class, and the student's final score who had watched the video for the longest time was 13 points more than the control class. A situation was also observed where the submission rate was 100% for three assignments. Thus, coupling AI and legal education to empower development could assist teachers in reducing mechanical repetitive labor.
In the long-term impact and sustainability analysis, the career development of the experimental group students displayed an advantage based on the employment rate, which increased rapidly from 75% to 100%, and these students realized a 95% success rate in the fourth year, which indicated the AI-coupled empowerment model's sustainability in actual law practice.
Overall, the findings of this study demonstrated that AI technology provides a novel approach to international law education through the efficient use of educational resources and improves students' employment rate and performance.
Predicting Upper Secondary Education Dropout Using Machine Learning