Algorithm Research on the Analysis of College Student Score

Abstract

This paper focuses on three algorithms based on analysis of variance (ANOVA), cluster analysis (CA) and factor analysis (FA) to analyse student scores, and uses FA-based algorithm to objectively evaluate students. Firstly, the ANOVA-based algorithm was adopted to study whether the differences in majors have a significant impact on the students' scores of advanced mathematics by selecting the scores of the 303 students in the four different majors from 4 different classes and departments of Grade 2013-2015. Meanwhile, using the compulsory courses scores of the 50 students of Grade 2013 in their freshmen year of the Oil and Gas Storage and Transportation Engineering Department of the Mechanical Engineering College. Meanwhile, the CA-based algorithm was applied to classify the students and formulate corresponding plans for different types of students, in order to improve students' performance. In addition, the FA-based algorithm was used to find out the main factors affecting the scores of students in various courses, obtain the composite scores by calculating the factor scores, and further make comprehensive evaluation of the students. Finally, it's verified that the three algorithms are feasible through the experiments. This shall be great significance for the student score evaluation and teaching research.

Intelligent Technology-Based Improvement of Teaching Ability of Professional Courses in Art Design

“…It is also an important guarantee and basic condition for improving the quality and teaching effect of modern education. For this, many researchers have discussed and analyzed the improvement of teachers' teaching ability from different perspectives, which have a very good guiding role in improving the teaching ability [1][2][3][4]. The improvement of teachers' teaching ability is a complex and dynamic system.…”