Abstract

More and more online learning apps are emerging, thanks to the development of Internet plus education and online learning platforms. Learning efficacy is the leading impactor of online learning participation. To avoid inefficiency and poor effect of online learning, it is necessary to explore the theory on the relationship between self-efficacy improvement and online learning participation. This paper examines the influence of self-efficacy improvement on online learning participation. Firstly, a general normal distribution map was drawn for self-efficacy. Then, a prediction model was established for participation based on the series of online learning behaviors. In addition, the k-means clustering (KMC) algorithm was optimized by information entropy, and the flow of the improved KMC was explained. The proposed model was proved valid through experiments.

Details

Title
Influence of Self-efficacy Improvement on Online Learning Participation
Author
Li, Geng
Pages
118-132
Section
Papers
Publication year
2022
Publication date
2022
Publisher
International Association of Online Engineering (IAOE)
ISSN
18630383
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2666916984
Copyright
© 2022. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.