A Self-Control Analysis Method of University Students Based on Campus Big Data

Abstract

Nowadays, the analysis of university students is the main concern of educational institutions. In this paper, we investigate the problem of analysing students’ self-control ability. Our model focuses on the process of feature extraction, and then classification algorithms are applied. We propose the concept of behaviour chain to model the behavior of student. On this basis, we propose a spatial periodic feature extraction method based on the longest common sub-sequence(LCS). And we extract some statistics features from consumption data, access control data and others. Our model SCA(Self-Control Analysis) performs with the precision of 0.72, the recall of 0.78 and the Fl-score of 0.74. It means that it’s possible to analyse student’ self-control ability with campus big data.