| Popis: |
Aiming at the problems of imperfect information management platform and Low quality of excavation, a combined algorithm of student behavior analysis based on clustering and association rules algorithm is proposed. Firstly, K-mediods algorithm is used to cluster the student behavior data, and the clustering results are discretized. Then, the association between student behavior and performance is analyzed by Eclat algorithm to extract important rules. Finally, combined with the results of the two algorithms, the behavior factors affecting students' performance are analyzed comprehensively. The analysis results show that the use of the above-mentioned combined algorithm not only improves the quality of the mining results, but also provides guidance and suggestions to teachers' teaching work and students' learning conditions through the mining results. |
