Big Data Analysis of Online Teaching of Finance Major in University Based on Questionnaire Star

DOI

10.2991/978-94-6463-230-9_5How to use a DOI?

Keywords

big data; online teaching; satisfaction

Abstract

In order to find out the problems existing in the online teaching, this paper has collected questionnaires in a university finance major to conduct a big data analysis, and used them to understand the satisfaction degree of the students to the online teaching, and continue to improve the quality of online teaching. The big data analysis was carried out from six aspects: overall satisfaction, satisfaction of teachers’ online teaching level, satisfaction of specific categories of online teaching, selection of teaching platforms and comparison of online teaching and offline teaching effects. It made an in-depth analysis of online teaching in a university’s financial profession.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Tieping Wang
PY  - 2023
DA  - 2023/09/04
TI  - Big Data Analysis of Online Teaching of Finance Major in University Based on Questionnaire Star
BT  - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
PB  - Atlantis Press
SP  - 28
EP  - 33
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-230-9_5
DO  - 10.2991/978-94-6463-230-9_5
ID  - Wang2023
ER  -