Open AccessAnalysis and Research Based on Method of Questionnaire Survey and the Algorithm of Big Data Analysis
Author(s) -
Fuliu Xiao,
Bei Song,
Kun Liu,
Changzheng Qu
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 - 10.1088/1742-6596/1813/1/012040
Subject(s) - economic shortage , adaptation (eye) , computer science , online learning , questionnaire , mathematics education , online teaching , big data , medical education , multimedia , psychology , sociology , data mining , medicine , social science , linguistics , philosophy , neuroscience , government (linguistics)
During the COVID-19 epidemic, the whole country suspended classes in schools without stopping studying. Under this circumstance, online teaching experienced a breakthrough development. This paper uses the method of questionnaire survey and the algorithm of big data analysis, and this paper explores the general situation of online teaching in local colleges and universities in southwest Guangxi which face challenges in online learning due to the relative shortage of educational resources and remote geographical location. This paper analyzes the supporting conditions, problems and shortcomings of online teaching in local colleges and universities in southwest Guangxi. Suggestions are also proposed on four aspects to improve online teaching and learning experiences, which are establishing the basis of online teaching conditions, strengthening the basic rules of online classroom management, improving teachers and students’ adaptation to online environment, and guiding students to improve independent learning ability.