Chenyue Hong1, Zejun Hou1, Yahui Meng1* and Timothy Chen2
1Guangdong University of Petrochem Technol, Sch Sci, Peoples R China
2Division of Engineering and Applied Science, California Institute of Technology, Pasadena, USA
*Corresponding Author: Yahui Meng, Guangdong University of Petrochem Technol, Sch Sci, Peoples R China. Email: email@example.com; Timothy Chen, Division of Engineering and Applied, Email: firstname.lastname@example.org
Received: June 02, 2021; Published: October 11, 2021
Because the comprehensive evaluation system of College Students’ performance is not perfect, most schools take the examination results as the only standard to evaluate students, leading to the contemporary college students can only cope with the examination and lack of independent thinking ability and innovation. In this paper, principal component analysis and cluster analysis are used to evaluate students’ performance. Taking the real performance of 39 students in class 1 of information and computing science of Science College of Guangdong University of Petrochemical Technology in 2020-2021-1 semester as the evaluation object, this paper uses MATLAB software combined with two analysis methods to analyze more information about students’ performance, so as to evaluate students’ performance more scientifically, accurately, fairly and fairly..In this paper, principal component analysis and cluster analysis can help teachers improve their teaching quality and teach students in accordance with their aptitude. Through principal component analysis, from the perspective of professional courses and non professional courses, we can give students a relatively clear direction of employment or postgraduate entrance examination, help students find their strengths, and pursue innovative, unique and personalized development.
Keywords: Academic Courses; Principal Component Analysis; Cluster Analysis; MATLAB
Citation: Yahui Meng., et al. “Evaluation of a Hybrid Principal Component Analysis and Cluster Analysis on Students' Learning Achievement and Motivation on Academic Courses". Acta Scientific Computer Sciences 3.10 (2021): 02-05.
Copyright: © 2021 Yahui Meng., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.