Relevance Analysis of Online Course Development on Education Platform and Significance of Teaching Reform Research Based on Collaborative Filtering Algorithm

DOI

10.2991/978-94-6463-012-1_48How to use a DOI?

Keywords

Medical Big Data Mining; Scientific Research Training; Undergraduates; Collaborative Filtering Algorithm

Abstract

Based on the rapid development of internet and education, online education platforms have also followed the pace of the times and achieved great success, among which Rain Classroom, Tencent Classroom, Learning Pass, MOOC and other platforms are almost mandatory for educational institutions to use during the epidemic prevention and control period, combined with QQ and WeChat for data preparation and schedule notification arrangement, achieving the effect of both epidemic prevention and teaching. With the prevention and control of the epidemic in China, the normal offline schooling has now started nationwide, and the active time of the users of the education platform has decreased. Data mining, data analysis, and the calculation of the user attrition rate of the education platform and making course correlation recommendations have played a decision-making role in promoting the development of the education platform model and the reform of the education model at this stage. Method: The collaborative filtering algorithm of the base model is based on the information of user preferences, trained into a complete model, and then based on the information of user preferences to make predictive recommendations and define the user churn rate calculation method. Results: We obtained the thermal distribution of user logins in each region calculated the percentage of user churn, the binary relationship between users and courses, and the ten most searched and welcomed courses. Conclusion: Based on the similarity of behavior between users and courses, there is a potential connection between different courses.

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  - Yuan-Nong Ye
AU  - Min Wang
AU  - Shuai Jin
AU  - Meng-Ya Huang
PY  - 2022
DA  - 2022/12/09
TI  - Relevance Analysis of Online Course Development on Education Platform and Significance of Teaching Reform Research Based on Collaborative Filtering Algorithm
BT  - Proceedings of the 2022 International Conference on Educational Innovation and Multimedia Technology (EIMT 2022)
PB  - Atlantis Press
SP  - 432
EP  - 439
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-012-1_48
DO  - 10.2991/978-94-6463-012-1_48
ID  - Ye2022
ER  -