Reform and Practice of College Japanese Test Mode Using Big Data Analysis

Abstract

With the acceleration of economic globalization, the demand for Japanese professionals is also increasing. In view of this situation, this paper puts forward a set of college Japanese test systems. A college Japanese teaching model based on big data is established, and an improved clustering algorithm is proposed by comparing correlation analysis and data mining techniques. Aiming at the phenomenon that ACA (ant colony algorithm) cannot guarantee that all data objects are acquired and collected by ants and the same data object can be accessed repeatedly, this paper puts forward some corresponding improvements. The clustering results show that the clustering accuracy of the algorithm is 80%. This proves the rationality and feasibility of dynamically evaluating students’ achievements based on clustering algorithm, and it is of great significance to introduce data mining into the teaching environment.

The Evaluation Algorithm of English Teaching Ability Based on Big Data Fuzzy K-Means Clustering

“…Big data is also a technology platform, through which a series of tasks such as collecting, preprocessing, and managing big data can be completed. Education big data refers to the data collected by educational administrative departments, schools, internship and training enterprises, virtual learning communities, social organizations, and other educational related institutions in all educational and learning activities (Huo, 2022). The generated data has obvious hierarchical, temporal, and situational characteristics.…”