
Research on College Students’ Course Selection Recommendation Model Based on Big Data and Cloud Computing
Author(s) -
Fei Su,
Jian-Yuan Tang,
Zhe Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1982/1/012203
Subject(s) - cloud computing , computer science , selection (genetic algorithm) , course (navigation) , process (computing) , relevance (law) , scheme (mathematics) , big data , order (exchange) , online course , key (lock) , management system , engineering management , knowledge management , mathematics education , artificial intelligence , engineering , finance , data mining , operations management , computer security , psychology , mathematical analysis , mathematics , law , political science , economics , aerospace engineering , operating system
When students choose courses online, they need to compare and analyze the difficulty of courses, professional relevance and interest, so as to make choices. Therefore, the decision-making process of course selection is the decisive link of online course selection. In the educational administration management system, the course selection system directly faces students and serves them. According to the past management experience, this system involves many links, including majors, teachers, courses, credits, teaching places, students and so on. By means of modern information technology, it is an important measure in the reform of higher education and teaching to integrate the course selection under the credit system with the information network, and to develop an online course selection system for students that adapts to the credit system management mode, which is also the key to ensure the smooth implementation of the credit system teaching reform. In order to improve the optimal allocation performance of students’ course selection and improve the utilization efficiency of course resources, a design method of students’ optimal course selection scheme model based on big data analysis and cloud computing technology is proposed.