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With the development of technology, strengthening the legal education system in universities is crucial for teaching effectiveness. This positively impacts college students’ internship work and reduces the boredom in law classes. Strengthening the legal education system in universities can also enhance students’ interest in learning and ability to learn independently. Optimizing university law classrooms’ teaching efficiency more quickly is another significant effect of strengthening the university law education system (Darmon & Le Texier, 2016). Law education is an integral part of China’s education system. It is an essential task for law educators to actively explore and practice new and suitable instructional methods (Cheah, 2017). The convenience brought by the Internet provides more choices for the study of law courses, and the growth of big data provides us with more possibilities (Ohlhausen, 2016). By collecting students’ learning behavior data, we can infer their learning progress, learning status, and learning status so that the school can have a more intuitive understanding of students’ information and provide guidance for their better learning (Taylor & Taylor, 2022). Driven by big data, students strengthen their existing knowledge and ask new questions through case screening, case discussion, case analysis, or other interactive methods.
In the teaching of law, we must carry out teaching reform according to its laws and training objectives, combined with the characteristics of the course, and seek breakthroughs in instructional methods (Wang et al., 2022). The theory of law course is professional and practical, requiring students to have a solid theoretical foundation, combine theory with practice, and improve their legal practice ability (Rasulov, 2021). In the traditional online instructional platform, teachers organize teaching according to instructional progress, and students can only learn according to the pre-set learning path. The system does not play the role of teachers’ immediate guidance and regulation and cannot realize individualized teaching (Meier, 2016). The law case base and laws and regulations driven by big data will comprehensively strengthen students’ practical training. The innovation of law case instructional mode driven by big data makes personalized learning possible. In this article, a learner data mining (DM) method based on improved fuzzy C clustering (FCM) algorithm for an online instructional platform is proposed, and the statistics of legal big data are summarized by combining cluster analysis and SPSS (Statistical Package for the Social Science) statistical methods, to provide better targeted teaching schemes and case resources for law case teaching and promote the innovation of law case instructional mode. In the teaching process of law class, teachers will adopt the Case method according to the teaching content and purpose. Through the Case method, students can deeply analyze the legal situation of specific events and focus on developing their practical ability. The Case method can also improve students’ problem-solving ability through independent thinking and teamwork. Students can combine theory with practice from the Case method to improve application skills and professional ability.