The Big Data Application of Law Case Library Research on the Path of Administrative Law Teaching and Practical Assistance

Amid the dual imperatives of digital rule of law and educational transformation, administrative law teaching faces structural challenges such as fragmented case resources, inaccurate retrieval, and a persistent disconnect between theory and practice. These challenges become more pronounced when legal education must address complex engineering-related regulatory scenarios, including data governance, industrial compliance, communication infrastructure, and specialized technical disputes. Big data technology, with its advantages in massive data integration, correlation mining, intelligent analysis, and prediction, provides technical support for upgrading legal case libraries and integrating administrative law teaching with practice. This study proposes a big-data-enabled administrative law case library and examines its application path in teaching and practical assistance. The case library integrates multi-source judicial, administrative, and teaching resources, supports precise retrieval and correlation analysis, and provides intelligent functions such as similar-case recommendation, judgment-logic visualization, and risk warning. By linking case resources with teaching tasks and practical legal workflows, the system helps solve the problems of outdated cases, shallow analysis, and insufficient skill training in traditional teaching. The study indicates that a big data legal case library can improve resource utilization, strengthen legal application ability, and support the coordinated development of administrative law education and practice.